International Journal of Management Science and Information Technology
International Journal of Management Science and Information Technology (IJMSIT) is a free and open-access journal published by the Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia. IJMSIT is an open-access journal dedicated to the exploration of the impact of information technologies on managerial and organizational topics. The journal employs a multidisciplinary approach to develop comprehensive and theoretical frameworks for both researchers and practitioners in the fields of management and information technology. IJMSIT aims to stimulate research in emerging domains influenced by advancements in information technology and trends in management practices. Its readership includes academics from business and engineering schools, as well as managers interested in the application of quantitative methods in business. All published articles are assigned a digital object identifier (DOI) for easy reference. You can access the manuscript format from the author guidelines. Download Manuscript Template: Template (English)
Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia
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Comparative Forecasting and Inventory Analytics for Web-Basedd Fabric Stock Control: A Case Study at BKR Textile Kudus
This study develops a web-based Smart Inventory system that integrates inventory recording, demand forecasting, inventory analytics, and replenishment recommendations for fabric stock control at BKR Textile Kudus. A Research and Development approach using the Prototype model was combined with quantitative comparative forecasting. The dataset comprised 400 fabric items and 12 months of stock-out history. Four one-month-ahead methods were tested: three-month Moving Average (MA), Weighted Moving Average (WMA) with 1:2:3 weights, Single Exponential Smoothing (SES) with alpha = 0.30, and rolling three-point Linear Regression (LR)-were evaluated through rolling-origin backtesting using MAD, MSE, and MAPE. Across 14,400 forecast-actual comparisons, MA produced the lowest average errors, with MAD of 5.167 rolls, MSE of 36.881, and MAPE of 5.166%. Inventory analysis identified three Critical items, 78 Low-stock items, 157 Normal items, and 162 Overstock items. The principal contribution is the integration of item-level comparative forecasting, safety stock, reorder points, inventory-status classification, and automated restock recommendations within one operational web platform. The system translates forecasting results into transparent decision information for a local textile company, although the findings remain specific to the one-year dataset and organizational setting examined.
Copyright (c) 2026 Diana Nur Yasmin, Yudie Irawan, Anteng Widodo https://creativecommons.org/licenses/by/4.0
Integrating Digital SCOR and Quality Management in the Textile Industry
The growing complexity of textile supply chains has increased the need for digital capabilities that enhance operational coordination, process integration, and quality management. The integration of digital supply chain standards with quality management remains important for improving supply chain outcomes in the textile industry. This study examines the relationship between the SCOR Digital Standard (SCOR DS) and Supply Chain Performance (SCP), with Quality Management (QM) serving as a mediating mechanism. A quantitative explanatory approach was employed using data from 320 personnel involved in supply chain, production, quality, and operational activities in the textile industry. Data were collected through structured Likert-scale questionnaires and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). SCOR DS has a significant positive effect on QM (β = 0.454, p < 0.001) and SCP (β = 0.142, p = 0.009). QM also has a stronger positive effect on SCP (β = 0.484, p < 0.001). Furthermore, QM significantly mediates the relationship between SCOR DS and SCP (β = 0.220, p = 0.007). Digital supply chain capabilities based on SCOR DS can strengthen supply chain performance, particularly when supported by effective quality management. The findings provide an integrated perspective for aligning digital SCOR practices with quality management to improve textile supply chain performance.
Copyright (c) 2026 Evan Nugraha, Rini Mulyani Sari, Rida Norina https://creativecommons.org/licenses/by/4.0
The Effects of Social Media Call-Out Culture and Digital CSR Communication on Green Brand Equity and The Role of Perceived Digital Accountability as An Intervening Variable (A Study of Eiger Indonesia Consumers)
This empirical study examines how a Culture of Criticism on social media and Digital CSR Communications shape Eco-Friendly Brand Equity, highlighting the mediating mechanism of Perceived Digital Accountability among Eiger Indonesia consumers. Amid growing consumer skepticism toward corporate greenwashing practices, outdoor gear brands face dual pressure from public criticism online and their own proactive sustainability messaging. Using a quantitative cross-sectional design, empirical data were collected via an online survey targeting 143 active followers of the @eigeradventure Instagram account aged 18 to 45, selected through purposive sampling. Statistical analysis was conducted using Multiple Linear Regression along with the Sobel Test and the SPSS PROCESS Macro to test both direct pathways and indirect structural relationships. The structural framework indicates that the Culture of Accountability on social media and Digital CSR Communication significantly drive Perceptions of Digital Accountability, which in turn serve as a crucial determinant of Eco-Friendly Brand Equity. Furthermore, Perceived Digital Accountability serves as an essential psychological bridge that transforms external public scrutiny and corporate sustainability signals into enhanced brand trust, an eco-friendly image, and customer satisfaction. Based on Signaling Theory, this study contributes to contemporary brand management literature by emphasizing digital accountability as a vital strategic pillar and providing practical guidance for outdoor brand managers in navigating digital public scrutiny.
Copyright (c) 2026 Aqsha Noorieta, Wala Erpurini https://creativecommons.org/licenses/by/4.0
A Web-Based Gold Price Prediction Model Using Geopolitical Sentiment from Social Media and Gated Recurrent Unit (GRU)
Gold is widely recognized as a safe-haven asset whose price is sensitive to economic and geopolitical uncertainty. This study develops a web-based international gold price prediction system using the Gated Recurrent Unit (GRU) algorithm and evaluates the contribution of geopolitical sentiment from the X social media platform. The study uses historical XAUUSD data and English-language posts related to the Iran–United States–Israel conflict. Text data were processed through cleaning, case folding, tokenization, stopword removal, lemmatization, TF-IDF transformation, and sentiment analysis using VADER. The resulting daily sentiment scores were integrated with historical gold price features and used as an additional input to the GRU model. Two experimental scenarios were evaluated: GRU without sentiment and GRU with sentiment. The results show that the GRU model without sentiment achieved an MAE of 55.07, RMSE of 69.81, MAPE of 1.17%, and R² of 0.9629, while the model with sentiment achieved an MAE of 80.87, RMSE of 92.93, MAPE of 1.72%, and R² of 0.9342. These findings indicate that incorporating daily aggregated social media sentiment did not improve prediction performance for the dataset used. The developed Flask-based web application provides prediction, sentiment analysis, visualization, and model evaluation features, demonstrating the practical implementation of the proposed approach.
Copyright (c) 2026 Narendra Saputra, Anteng Widodo, Zainur Romadhon https://creativecommons.org/licenses/by/4.0
How Social Media Marketing and Online Reviews Influence the Likelihood of Customers Buying Again: The Role of Brand Trust Among Tokopedia Users in Bandung City
The rapid growth of the e-commerce sector in Indonesia has intensified competition among online shopping platforms, making customer loyalty and repurchase intention increasingly important for businesses. The decline in Tokopedia’s Top Brand Index indicates challenges in maintaining consumer loyalty and encouraging repeat purchases. This study aims to examine the effect of Social Media Marketing (SMM) and Electronic Word of Mouth (E-WOM) on Repurchase Intention through Brand Trust as a mediating variable among Tokopedia users in Bandung City. This study adopts the Stimulus–Organism–Response (SOR) framework, in which SMM and E-WOM represent external stimuli, Brand Trust represents the consumer’s internal psychological state, and Repurchase Intention represents the behavioral response. A quantitative approach was employed through a survey of 165 Tokopedia users in Bandung City selected using purposive sampling. The data were analyzed using multiple linear regression and the Sobel test with IBM SPSS version 26. The results indicate that both Social Media Marketing and Electronic Word of Mouth have a positive and significant effect on Brand Trust. Furthermore, Brand Trust has a positive and significant effect on Repurchase Intention. The mediation results also demonstrate that Brand Trust mediates the relationship between Social Media Marketing and Electronic Word of Mouth and Repurchase Intention. These findings indicate that effective digital marketing activities and consumer-generated information can strengthen brand trust, which subsequently encourages consumers to repurchase. This study contributes to the application of the SOR framework in the Indonesian e-commerce context and provides practical implications for Tokopedia in developing effective digital marketing strategies and strengthening consumer trust to encourage repeat purchases.
Copyright (c) 2026 Zulfikar Nurharis, Wala Erpurini https://creativecommons.org/licenses/by/4.0
Skintific Purchase Decisions Among TikTok Users in Purwokerto: The Role of Influencer Marketing, e-WOM, Brand Image, and Product Quality
This study aims to examine the influence of consumer purchasing decisions of Skintific skincare products in Purwokerto with the variables of influencer marketing, electronic word of mouth, brand image, and product quality. Quantitative data collection using Google Forms with a Likert Scale of 1-5. The research population is residents of Purwokerto who have purchased Skintific skincare products and are actively using TikTok. Sampling used a non-probability method with a purposive sampling technique. The Lemeshow method was used to determine the minimum number of samples and and the final sample consisted of 130 respondents. This study uses the Construct Validity and Reliability Test, Discriminant Validity of Fornell-Larcker and HTMT criteria, Inner VIF, Model Fit, R-Square and Hypothesis Test. The data were analyzed using the SmartPLS 3. The results of this study showed that all variables were positively related to purchase decisions, influencer marketing (β=.334), electronic word of mouth (β=.276), brand image (β=.357), and product quality (β=.306), all p<.001; R²=.643. In this study, all variables can influence purchasing decisions with the findings of brand image as the variable that has the highest influence. The findings indicate the importance of brand image consistency in Skintific communication on TikTok. This study contributes to the digital marketing literature by providing empirical evidence on the effects of influencer marketing, e-WOM, brand image, and product quality on purchase decisions. However, this study is limited to TikTok users in Purwokerto.
Copyright (c) 2026 M Rizki Bahtiar, Totok Haryanto, Erny Rachmawati, Hengky Widhiandono https://creativecommons.org/licenses/by/4.0
Financial Literacy, Investment Motivation, Information Technology, And Minimum Capital Affecting Generation Z Investment Interest in Purworejo Regency
The purpose of this study is to ascertain how financial literacy, investment motivation, information technology, and minimum capital affect Generation Z's inclination to invest in Purworejo Regency. Understanding the elements that influence Generation Z's intention to invest has become more important as their involvement in investment activities has grown. Information technology, minimum capital, financial literacy, and investing motivation are all thought to be significant factors that could affect investors' investment choices. This study used a structured questionnaire delivered using Google Forms as part of a quantitative research methodology. Purposive sampling was used to get data from 102 valid responses. Multiple linear regression was used to examine the collected data with the aid of SPSS software. The findings show that Generation Z's intention to invest is positively and significantly impacted by financial literacy, investment motivation, and minimal capital. In the meantime, investment intention is not significantly impacted by information technology. These results suggest that promoting investment intention among Generation Z requires enhancing financial awareness, boosting investment motivation, and expanding access to reasonably priced first investment money. Additionally, policymakers, financial institutions, and educational institutions can use the study's practical implications to develop initiatives that encourage youth investment engagement.
Copyright (c) 2026 Reyna Putri Gustyarni, Intan Puspitasari, Ishak https://creativecommons.org/licenses/by/4.0
How Modified BCG Matrix-Based Product Portfolio Optimization Changes Consumer Purchase Behavior: Evidence from Vending Machine Transactions
Product portfolio optimization is essential in automated retail because vending machines operate under severe storage constraints, requiring every Stock Keeping Unit (SKU) to contribute effectively to overall sales performance. However, conventional portfolio management approaches, including the Boston Consulting Group (BCG) Matrix, rely on market-level indicators that are difficult to apply in vending machine environments where external market share data are unavailable. This study proposes a Modified BCG Matrix by replacing Relative Market Share with Relative Sales Performance (RSP) and Market Growth Rate with Sales Growth Trend (SGT) to enable SKU-level portfolio optimization using internal transaction data. A quantitative longitudinal design with an Interrupted Time Series (ITS) approach was employed using 167,018 valid transactions collected from 11 smart vending machines operating in Cikarang, Indonesia, between September 2025 and June 2026. The Modified BCG Matrix guided operational decisions, including facing allocation, replenishment priority, product rotation, replacement, and product delisting. The implementation reduced the active product portfolio from 253 to 146 SKUs (42.3%), increased average daily transaction volume by 28.53%, increased average daily sales revenue by 22.19%, and produced statistically significant immediate intervention effects based on segmented regression analysis. These findings demonstrate that data-driven product portfolio optimization not only improves operational efficiency and sales performance but also reshapes consumer purchase behavior. This study extends the application of the traditional BCG Matrix from the Strategic Business Unit (SBU) level to the SKU level and provides an evidence-based decision-support framework for automated retail portfolio management.
Copyright (c) 2026 Chowal Jundy Kumoro, Lambok Rommy Sulaeman, Gredinov Sumanta Malsad, Mochamad Arya Maulana https://creativecommons.org/licenses/by/4.0
Development of Intelligent Decision Support System Based on Quadrant Analysis, Time Series Trend Analysis, and Automatic Planogram Generation for Vending Machine Product Optimization
Product management in a vending machine business requires fast and data-driven decision-making to increase sales effectiveness and profitability. However, decision-making related to price adjustments, product bundling, product replacements, and product arrangement on vending racks is still mostly done manually based on the manager's experience, so it has the potential to produce less than optimal decisions. This research aims to develop an Intelligent Decision Support System that is able to produce business strategy recommendations through the integration of Quadrant Analysis, Time Series Trend Analysis, and Automatic Planogram Generation. The research data was obtained from the results of exporting the vending machine transaction database imported into the application in CSV or Excel format, so that the system does not depend on direct integration with the Application Programming Interface (API). Quadrant Analysis is used to group products based on sales performance and profit contribution, while Time Series Trend Analysis is used to evaluate historical sales trends as a support for decision validation, rather than as a sales prediction method. The results of the second analysis were processed using a rule-based decision engine mechanism to produce recommendations in the form of price adjustments, product bundling, maintaining or replacing products, and compiling an automatic planogram based on product performance priorities. The resulting planogram can still be adjusted manually by the user so that it still provides flexibility in operational decision-making. In addition, the system presents profit analysis based on product, machine, and location as the basis for business evaluation. The resulting artifacts are in the form of a decision support system application that not only presents data visualization, but also automatically generates strategic recommendations to help managers improve the effectiveness of product management in the vending machine business.
Copyright (c) 2026 Rizaldi Putra, Syaban Maulana, Tessalonika Audry Polnaya, Muhammad Zaky Fahriansyah https://creativecommons.org/licenses/by/4.0
The Role of Customer Satisfaction in Mediating the Effects of Product Quality and Perceived Price Fairness on Switching Intention: A Study of iPhone Users in Denpasar
The premium smartphone market has become increasingly competitive, encouraging consumers to evaluate alternative brands based on the value they receive from product performance and pricing. Although the iPhone is widely recognised for its premium positioning, users may still develop intentions to switch when they perceive that the product quality or price no longer provides satisfactory value. This study examines the direct effects of product quality and perceived price fairness on switching intention, while also investigating the mediating role of customer satisfaction among iPhone users in Denpasar. A quantitative approach was adopted by collecting data from 144 respondents selected through purposive sampling. The proposed research model was analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The empirical findings indicate that both product quality and perceived price fairness significantly decrease switching intention while simultaneously exerting positive effects on customer satisfaction. In addition, customer satisfaction partially mediates the relationships between product quality and switching intention and between perceived price fairness and switching intention. These findings suggest that consumers are less likely to consider alternative smartphone brands when they perceive superior product quality and fair pricing, as these perceptions strengthen overall satisfaction. From a managerial perspective, the results highlight the importance of continuously enhancing product quality and implementing pricing strategies that consumers perceive as equitable in order to reinforce customer satisfaction and minimise switching intention.
Copyright (c) 2026 Ni Wayan Lia Kusumaningrum, Gede Bayu Rahanatha https://creativecommons.org/licenses/by/4.0
Human Resource Management Strategy in Improving Employee Performance at PT Kino Indonesia Tbk
Employee performance remains a central determinant of organizational competitiveness within the fast-moving consumer goods (FMCG) industry, particularly for companies such as PT Kino Indonesia Tbk operating amid intensifying market competition and accelerating human resource digitalization. This article aims to describe and analyze, through the lens of the Ability-Motivation-Opportunity (AMO) framework, the human resource management strategies disclosed by PT Kino Indonesia Tbk and to examine how these strategies collectively relate to employee performance improvement. This study employs a qualitative descriptive research design through library research, drawing secondary data from the company's 2022 and 2023 Annual Reports and 2024 Sustainability Report, analyzed using a structured thematic analysis procedure. The findings indicate that PT Kino Indonesia Tbk implements three interrelated strategies corresponding respectively to the ability, opportunity, and motivation dimensions: tiered competency-based development, evidenced by an increase in training hours per employee from 4.57 in 2022 to 9.18 in 2023; a digital learning platform enabling self-directed employee development; and welfare-oriented sustainability practices under the Thriving People pillar, reflected in full health-insurance coverage and complete maternity-leave reinstatement, alongside an 11 percent turnover rate in 2024. These findings demonstrate that the three strategies function as a mutually reinforcing system rather than isolated initiatives, contributing theoretically to sustainable human resource management literature by illustrating the applicability of the AMO framework to publicly disclosed corporate HR strategy, while offering practical implications for other Indonesian FMCG firms pursuing integrated HR strategy design.
Copyright (c) 2026 Riezky Army Riesha https://creativecommons.org/licenses/by/4.0
The Impact of Store Image, Customer Trust, and Perceived Service Quality on Repurchase Intention: Customer Satisfaction as a Mediator among Alfamart Consumers in Bandung
The surge in the modern retail sector has amplified competition among minimarket franchises, forcing retailers to identify the key drivers of customer retention. This research investigates how Store Image, Customer Trust, and Perceived Service Quality Influence Repurchase Intention, positioning Customer Satisfaction as a mediator among Alfamart minimarket patrons in Bandung, Indonesia. Utilizing a quantitative explanatory approach, data were gathered through structured questionnaires from 110 purposively sampled respondents with prior shopping experience at Alfamart. Multiple linear regression and the Sobel test via SPSS version 26 were applied to evaluate direct and indirect hypotheses. The conceptual framework posits that Store Image, Customer Trust, and Perceived Service Quality positively impact Customer Satisfaction, which in turn fosters Repurchase Intention. Additionally, Customer Satisfaction is anticipated to bridge the gap between these three antecedents and the intent to repurchase. Theoretically, this study enriches retail marketing literature by offering fresh empirical insights into repurchase behavior within modern retail. Practically, the insights can guide Alfamart’s management and similar retail firms in crafting strategic initiatives to bolster satisfaction, loyalty, and sustainable repurchase rates.
Copyright (c) 2026 Harly Rangga Roland Sehastian, Abdul Ahmad Hafidh Nurmansyah https://creativecommons.org/licenses/by/4.0
The Effect of Product Quality and Brand Image on Repurchase Intention of Honda Beat Motorcycles in Bandung City
Due to intensifying competition within Indonesia's automatic motorcycle sector, manufacturers are increasingly compelled to elevate product quality and solidify brand image to foster customer retention and drive repurchase intention. This study investigates the partial and simultaneous effects of product quality and brand image on the repurchase intention of Honda Beat owners in Bandung City. Employing a quantitative survey design, primary data were gathered from 120 purposively selected Honda Beat users. The dataset was subsequently evaluated using descriptive statistics, multiple linear regression, and hypothesis testing via IBM SPSS Statistics. The empirical findings reveal that both product quality and brand image exert a positive and statistically significant impact on repurchase intention individually. Concurrently, both factors significantly drive consumers' intention to repurchase, demonstrating that superior product performance, reliability, durability, and a favorable brand perception strongly incentivize repeat purchases. Consequently, preserving high manufacturing standards while enhancing brand equity remains vital for cultivating customer loyalty and maintaining market competitiveness. Ultimately, this research adds to the marketing literature on automotive consumer behavior in urban Indonesia and offers strategic insights for manufacturers seeking to optimize customer retention.
Copyright (c) 2026 Vincentius Celvin Kardiman, Wala Erpurini https://creativecommons.org/licenses/by/4.0
The Effect of Price Perception and Product Quality on Repurchase Intention: The Mediating Role of Customer Satisfaction among Oriflame Sun Care Consumers in Bandung City
The increasing competition in Indonesia's skincare industry has heightened the need to understand the factors influencing consumers repurchase intention. This study examines the effects of price perception and product quality on repurchase intention, with customer satisfaction as a mediating variable among Oriflame Sun Care consumers in Bandung City. A quantitative approach was employed using convenience sampling, involving 127 consumers who had previously purchased and used Oriflame Sun Care products. Data were analyzed using multiple regression and the Sobel test. The results show that price perception and product quality have positive and significant effects on customer satisfaction. Price perception, product quality, and customer satisfaction also have positive and significant effects on repurchase intention. Furthermore, customer satisfaction significantly mediates the effects of both price perception and product quality on repurchase intention. These findings indicate that strengthening perceived price fairness, maintaining product quality, and improving customer satisfaction are important strategies for increasing repurchase intention among Oriflame Sun Care consumers.
Copyright (c) 2026 Adinda Fachrani Saputra, Leni Evangalista Marliani https://creativecommons.org/licenses/by/4.0
The Effect of Physical Work Environment and Work Motivation on The Performance of State Civil Apparatus Employees in The Field of Public Health and Health Resource Services Cimahi City Government Health Office
One of the key metrics used to assess how well public sector entities are serving the population is the State Civil Apparatus's performance. This study aims to investigate how State Civil Apparatus in the Public Health Sector and the Health Resources Services Division of the Cimahi City Government Health Office perform in relation to their physical work environment and motivation. This study employs an associative strategy in conjunction with a quantitative approach. There were 40 participants in the study, with two direct supervisors serving as performance variable assessors and 38 State Civil Apparatus respondents serving as independent variable respondents The sampling procedure employs the census method since every member of the population is used as a research participant. Using the aid of the SPSS software version 25, data were gathered via the distribution of questionnaires and examined using statistical descriptive analysis, multiple regression analysis, and determination coefficients. The research instrument is validated using validity, reliability, and classical assumption tests prior to testing of hypotheses. The study's outcomes show that both the physical work environment and work motivation possess a simultaneous influence on State Civil Apparatus performance, and that State Civil Apparatus performance is positively impacted by the physical work environment. Additionally, most crucial element in raising State Civil Apparatus performance is work motivation. The study's conclusions show that enhancing the physical work environment quality and motivation of employees may contribute to the enhancement of the State's Civil Equipment performance within the execution of public services.
Copyright (c) 2026 Achmad Yudha Pratama, Dian Lestari https://creativecommons.org/licenses/by/4.0
The Psychology of Generation Z Investors: Mental Accounting, Loss Aversion, and Gender Dynamics in Greater Bandung
The growth of young investors supported by digital technology has not always been followed by the quality of completely rational investment decisions. This study aims to analyze the influence of mental accounting and loss aversion on Generation Z's investment decisions in the Greater Bandung area and test gender as a moderation variable. The research uses a quantitative approach with a cross-sectional survey design. Data was obtained through questionnaires from 115 Generation Z respondents who are domiciled in Greater Bandung and have investment experience. Samples were selected based on research criteria, while analysis was conducted using descriptive statistics, multiple linear regression, and Moderated Regression Analysis with IBM SPSS Statistics 25. The results show that mental accounting has a negative and significant effect on investment decisions. Loss aversion is negative but not significant, while the interactions of mental accounting with gender and loss aversion with gender are also not significant. The model explains 52.1% of the variance in investment decisions (Adjusted R² = 0.521). Theoretically, the findings indicate that cognitive and emotional biases do not exert equal explanatory power in Generation Z investment decisions and that gender does not necessarily condition these relationships. Practically, the results support portfolio-level evaluation tools and behavioral-finance education that help young investors distinguish useful fund discipline from rigid mental accounting.
Copyright (c) 2026 Ifan Fauji, Frido Saritua Simatupang https://creativecommons.org/licenses/by/4.0
The Influence of Financial Literacy and Digital Wallet Usage on Financial Behavior Among Students: An Empirical Study of Students in South Jakarta
This study evaluates the influence of financial literacy and the use of e-wallets on the financial behavior of students in South Jakarta, focusing on both individual effects and the interaction between these factors. A quantitative approach was employed within an explanatory-causal framework, with primary data collected through a 1-4 Likert scale questionnaire distributed to 400 students residing or studying in the area, selected via purposive sampling. The analysis included instrument quality assessment, descriptive statistics, classical assumption testing, multiple linear regression, as well as t-tests and F-tests. Findings indicate that financial literacy does not exert a significant influence on students' financial behavior, with a significance value of 0.178, exceeding the 0.05 threshold. In contrast, e-wallet usage demonstrates a notable positive impact, evidenced by a significance value of 0.000, which is below 0.05, along with a positive regression coefficient. When assessed together, both factors significantly affect financial behavior, as shown by an F value of 902.144 and a significance level of 0.000. The Adjusted R Square value of 0.819 suggests that 81.9% of the variance in students' financial behavior can be attributed to financial literacy and e-wallet usage, while the remaining 18.1% is influenced by other variables not examined in this study. These results emphasize the greater role of e-wallet usage in shaping financial practices among students compared to financial literacy. Therefore, it is recommended that digital financial literacy initiatives be enhanced, focusing on the development of record-keeping skills, expenditure management, and responsible use of digital transaction tools.
Copyright (c) 2026 Revaldo, Mukti Soma https://creativecommons.org/licenses/by/4.0
Structural Change Detection and Forecasting of Indonesia's Tourism-Related Output Using PELT and SARIMA Intervention Models
Quarterly tourism-related output is seasonal and highly vulnerable to structural disruptions, so models fitted to stable historical patterns may fail after shocks. This study detects changepoints and compares forecasting models for Indonesia's real GDP in Accommodation and Food Service Activities, used as a proxy for tourism-related economic output. The dataset comprised 50 quarterly observations at constant 2010 prices from 2013Q1 to 2025Q2. PELT was applied to detrended, seasonally adjusted log-training residuals. Ordinary SARIMA, SARIMA models with pulse and step interventions, six exponential-smoothing specifications, and a seasonal-naive benchmark were screened using training AICc, 16 rolling one-step validation origins, and an untouched ten-quarter fixed test. PELT identified 2017Q2, 2020Q2, and 2022Q1 as changepoints, with 2020Q2 remaining the most robust under stronger penalties. SES achieved the smallest rolling-validation RMSE (6,283.9), while the pulse-plus-temporary-step SARIMA intervention was best within its family (RMSE 6,917.4). On the fixed 2023Q1-2025Q2 test, SARIMA (0,1,1) × (0,0,0)₄ performed best overall, with MAE of Rp5,301.9 billion, RMSE of Rp6,131.6 billion, sMAPE of 5.23%, and MASE of 1.016. For the selected baseline SARIMA, residual autocorrelation and ARCH effects were not significant; the intervention model, however, retained significant residual autocorrelation. Residuals were non-normal across the retained models, and the baseline SARIMA underpredicted the later recovery. PELT provided structural diagnosis, but explicit intervention effects did not guarantee superior holdout forecasts. Parsimonious SARIMA provides the most defensible baseline, supplemented by changepoint monitoring and scenario-based intervention analysis.
Copyright (c) 2026 Haves Qausar, Zata Hasyyati https://creativecommons.org/licenses/by/4.0
Decision Support System for Selecting the Best Smartphone Using the Multi Attribute Utility Theory (MAUT) Method at Sinar Mas Selluler Kudus
The increasing variety of smartphone products with different specifications and prices makes the selection process more difficult for customers and often results in subjective recommendations from sales personnel. This study aims to develop a web-based Decision Support System (DSS) for smartphone selection at Sinar Mas Selluler Kudus using the Multi Attribute Utility Theory (MAUT) method. The system evaluates smartphone alternatives based on five criteria: Random Access Memory (RAM), Internal Storage, Screen Size, Battery Capacity, and Price. The research employed the System Development Life Cycle (SDLC) approach, including planning, analysis, design, implementation, and testing. The MAUT method was applied through criteria weighting, utility normalization, preference value calculation, and ranking to generate objective recommendations. The developed system was functionally validated using Black Box Testing to ensure that all system features operated according to the specified functional requirements. The developed system successfully automated the evaluation process, reduced subjective decision-making, and improved the efficiency of smartphone selection. The calculation results showed that Huawei (A3) achieved the highest preference value of 0.7215, indicating that it is the most suitable smartphone alternative according to the predefined criteria and weights. The implementation results demonstrate that the proposed system can assist sales personnel in providing objective recommendations while helping customers compare smartphone alternatives more efficiently based on their preferences and budget constraints. Therefore, the proposed system provides accurate, transparent, and consistent recommendations to support customers and sales personnel in making better purchasing decisions.
Copyright (c) 2026 Arina Fawaida, Noor Latifah, Yudie Irawan https://creativecommons.org/licenses/by/4.0
Under-Five Children's Nutritional Status Prediction Using Naïve Bayes and Decision Tree Based on Anthropometric Data and Mother–Child Class Participation
Nutritional status is an important indicator of the health and development of children under five, making early identification essential for supporting appropriate nutritional interventions. This study aimed to develop and compare the performance of the Naïve Bayes and Decision Tree algorithms in classifying the nutritional status of children under five based on anthropometric measurements and participation in the mother and Children Under Five Class program in Mlonggo District, Indonesia. A quantitative approach was applied using the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework. The initial dataset contained 4,588 records, of which 4,563 valid records remained after the preprocessing stage. Model performance was evaluated using accuracy, precision, recall, F1-score, confusion matrix, ROC curve, and McNemar’s test. The results showed that the Decision Tree algorithm achieved a higher cross-validation accuracy of 90.90% compared with 87.59% for Naïve Bayes. The testing results also demonstrated that Decision Tree consistently outperformed Naïve Bayes across the evaluation metrics. Therefore, Decision Tree was selected as the most suitable model for nutritional status classification. The model was subsequently implemented in a web-based application supporting individual and batch prediction, along with the presentation of prediction results and recommended health interventions. The system can support healthcare workers in conducting nutritional status assessments more efficiently and objectively.
Copyright (c) 2026 Tsirwatun Nisail Khasanah, Fajar Nugraha, Yudie Irawan https://creativecommons.org/licenses/by/4.0
Enhancing Employee Performance in The Public Sector: The Role of Human Resource Competence and Organizational Communication with Evidence from Selayar Islands Regency
This study aims to examine the influence of technical guidance, human resource (HR) competence, and organizational communication on employee performance at the Secretariat of the Regional House of Representatives (DPRD) of the Selayar Islands Regency using a quantitative survey approach with 80 respondents; data were collected through questionnaires and analyzed using multiple linear regression with prior validity, reliability, and classical assumption tests to ensure model accuracy. The findings reveal that HR competence and organizational communication have a positive and significant effect on employee performance, while technical guidance does not show a significant influence; moreover, organizational communication is identified as the most dominant variable. The model demonstrates strong explanatory power with an R² value of 0.871, indicating that 87.1% of performance variation is explained by the independent variables. These results emphasize the critical role of effective communication and competent human resources in improving organizational performance, while highlighting the need to redesign training programs to better align with job-specific demands in the public sector.
Copyright (c) 2026 Muh. Alim, Muhammad Rusydi, Muchriady Muchran https://creativecommons.org/licenses/by/4.0
Influence of Environmental Concern and Green Packaging Perception on Consumers' Willingness to Pay For FMCG: Green Skepticism as A Mediator
As sustainability concerns grow, FMCG firms have increasingly turned to eco-friendly packaging as part of their green strategy. Yet a gap persists between consumers' pro-environmental attitudes and their actual purchase behavior, since favorable attitudes toward the environment do not always translate into a premium price consumers are willing to pay. Building on this gap, this study investigates how environmental concern and green packaging perception shape FMCG consumers' willingness to pay, with green skepticism examined as a potential mediating pathway. A total of 176 FMCG consumers in Indonesia were recruited through a purposive-sampling procedure to serve as the study's respondents. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0. The results show that EC and GP directly and positively predict WTP, whereas the indirect pathways through GS were not statistically supported. Notably, GP was found to reduce GS the reverse of what was hypothesized and GS itself showed no significant bearing on WTP. These findings indicate that in the FMCG context, consumers translate environmental concern and green packaging perception directly into willingness to pay, without a meaningful skeptical evaluation process. This study contributes theoretically by identifying the boundary conditions of green skepticism as a mediating mechanism in low-involvement product categories, and offers practical implications for FMCG companies in designing sustainability communication that is directly value-oriented for consumers.
Copyright (c) 2026 Alfigo Adisari, Raden Johnny Hadi Raharjo https://creativecommons.org/licenses/by/4.0
Customer Review Sentiment Classification of Belikopi Products Using the Support Vector Machine (SVM) Method
The rapid development of information technology and the widespread use of social media have significantly changed the way customers express their opinions and experiences regarding products and services. Platforms such as Instagram, TikTok, and Google Maps have become important sources of customer feedback that can be analyzed to understand public perception and customer satisfaction. Sentiment analysis is one of the text mining techniques that can automatically classify opinions into positive, neutral, and negative sentiments, enabling businesses to make informed decisions based on customer feedback. This study aims to analyze customer sentiment toward Belikopi products using the Support Vector Machine (SVM) classification algorithm. A total of 4,636 customer reviews and comments were collected from Instagram, TikTok, and Google Maps and manually labeled into three sentiment categories: positive, neutral, and negative. Before the classification process, the dataset underwent several preprocessing stages, including case folding, cleaning, tokenizing, stopword removal, and stemming to improve the quality of textual data. Furthermore, the Term Frequency–Inverse Document Frequency (TF-IDF) method was employed to convert text into numerical feature vectors suitable for machine learning classification. The dataset was divided into 80% training data and 20% testing data using a stratified sampling approach to maintain the distribution of sentiment classes. The experimental results showed that the SVM model achieved an accuracy of 93.34%, demonstrating its capability to classify customer sentiment with high performance. The findings indicate that the proposed approach is effective in identifying customer perceptions of Belikopi products and can provide valuable insights for evaluating customer satisfaction, improving product quality, and supporting strategic business decision-making.
Copyright (c) 2026 Avin Nuzula Fitranti, R. Rhoedy Setiawan, Yudie Irawan https://creativecommons.org/licenses/by/4.0
Analysis of Uncertainty Factors of Rice Availability in Karawang Regency Using a Dynamic System Approach
Karawang Regency serves as a crucial national granary, playing a vital role in supporting food security. This study analyzes how climate change, shifting agricultural land areas, productivity, and population growth impact rice availability. Additionally, it models simulations to maintain stable rice supplies using a system dynamics approach. The model was developed using Causal Loop Diagrams (CLD) and Stock Flow Diagrams (SFD), and subsequently validated through Mean Absolute Percentage Error (MAPE). The validation results showed MAPE values of 5.6% for rice production and 3.2% for rice consumption, indicating that the model is valid. Simulation results revealed that although rice production is projected to remain higher than consumption, rice availability is expected to decline until 2046. Scenario analysis demonstrated that increasing productivity has the greatest influence on improving rice availability. First scenario consisting of a productivity level of 8 tons/ha, an annual change in agricultural land area of 65 ha, a population growth rate of 0.5%, and a maximum temperature increase of 0.35°C is projected to produce approximately 539,959 tons of rice availability by 2046. The proposed model can serve as a decision support system for local governments in maintaining food security through simulation-based policy planning by incorporating the effects of flooding, paddy grain prices, rice prices, and rice distribution and supply chain dynamics.
Copyright (c) 2026 Anditania Sari Dwi Putri, Annisa Indah Pratiwi, Annisa Nurizzati https://creativecommons.org/licenses/by/4.0
Multi-Platform Sentiment Analysis of Diabetes Mellitus on X and TikTok Using K-Nearest Neighbor, Chi-Square Selection, and Oversampling
Diabetes mellitus is a chronic health condition that is widely discussed by the public on social media, generating a large volume of opinions that are difficult to interpret manually. This study analyzes public sentiment toward Diabetes mellitus using data collected from X (Twitter) and TikTok. Text data were preprocessed (cleaning, slang normalization, stopword removal, and stemming) and duplicate entries were removed. Sentiment labels were generated automatically through a rule-based lexicon across four categories (positive, negative, neutral, and irrelevant/discarded), and the reliability of this automatic labeling was verified through manual validation of a stratified sample of 200 data points, measured using Cohen's Kappa. Positive and negative data were then weighted using TF-IDF, reduced using Chi-Square feature selection, balanced using SMOTE, and classified using K-Nearest Neighbor (KNN). Model performance was evaluated using accuracy, precision, recall, and F1-score, and compared across four scenarios: baseline KNN, KNN with Chi-Square, KNN with SMOTE, and the combined KNN+Chi-Square+SMOTE model. The manual validation of 198 valid samples produced an agreement accuracy of 59.60% and a Cohen's Kappa of 0.459 (moderate agreement), indicating that the main source of disagreement lies at the boundary between the neutral and sentiment-bearing classes, while direct positive-negative misclassification was rare (4.5%). The combined model achieved an accuracy of 82.86%, with a macro-averaged precision of 82.95%, recall of 83.56%, and F1-score of 82.79%. Interestingly, Chi-Square feature selection alone yielded the highest accuracy among the four scenarios (85.10%), suggesting that feature selection contributed more to performance gains than class balancing in this dataset. These findings suggest that combining feature selection and oversampling techniques improves the reliability of multi-platform sentiment classification for health-related topics and can inform more effective public health communication strategies regarding diabetes.
Copyright (c) 2026 Asti Nisa, Noor Latifah, R. Rhoedy Setiawan https://creativecommons.org/licenses/by/4.0
The Effects of Price Perception and Product Quality on Repurchase Intention: The Mediating Role of Customer Satisfaction Among Consumers of Make Over Lipstick in Cimahi City
This study aims to analyze the influence of price perception and product quality on repurchase intention, with consumer satisfaction as a mediating variable among Make Over lipstick consumers in Cimahi City. A quantitative approach was employed, utilizing an explanatory research design and survey method. The sample consisted of 134 female consumers who had purchased and used Make Over lipstick, selected through convenience sampling. Data were collected using a five-point Likert scale questionnaire and analyzed with descriptive analysis, multiple linear regression, path analysis, and the Sobel test, assisted by SPSS version 25. The results indicate that price perception does not have a significant effect on consumer satisfaction, whereas product quality has a positive and significant effect on consumer satisfaction. Perceived price, product quality, and consumer satisfaction each have a positive and significant effect on repurchase intention, with perceived price exerting the most dominant direct influence. Mediation analysis indicates that consumer satisfaction does not mediate the effect of perceived price on repurchase intention, but does mediate the effect of product quality on repurchase intention. These findings suggest that appropriate price management and product quality improvement are necessary to enhance consumer satisfaction and repurchase intention for Make Over lipstick.
Copyright (c) 2026 Wan Maharani Alista Sari, Leni Evangalista Marliani https://creativecommons.org/licenses/by/4.0
The Effect of Perceived Enjoyment and Social Interaction on Continuance Intention Through User Satisfaction Among Valorant Players in Bandung City
This study aims to analyze the effect of perceived enjoyment and social interaction on continuance intention through user satisfaction among Valorant players in the city of Bandung. This research is motivated by the decline in Valorant's global monthly active player count, from approximately 24–25 million in mid-2024 to 17–20 million by the end of 2025, as well as the fluctuating pattern of information searches about Valorant in Indonesia, which indicates an issue with players' continuance intention. This study uses a quantitative approach with a survey method. The research sample consisted of 116 respondents selected using a purposive sampling technique, with the criteria of being at least 17 years old, having played Valorant at least once in the last three months, and residing in the city of Bandung. Data were analyzed using multiple linear regression and the Sobel test with the assistance of SPSS version 25. The results show that perceived enjoyment and social interaction have a positive and significant effect on user satisfaction, and user satisfaction has a positive and significant effect on continuance intention. Directly, only social interaction has a significant effect on continuance intention, while perceived enjoyment has no significant direct effect and is thus fully mediated by user satisfaction, whereas the effect of social interaction is partially mediated. These findings indicate that enjoyment in playing only drives continuance intention after being processed through satisfaction, whereas social interaction drives that intention both directly and through user satisfaction. This study reinforces the integration of the Expectation Confirmation Model, the concept of a hedonic information system, and self-determination theory in the study of post-adoption user behavior in online games. The findings can serve as input for Riot Games and other stakeholders in the competitive gaming industry in designing player retention strategies that emphasize playing enjoyment, the quality of social interaction, and user satisfaction.
Copyright (c) 2026 Afif Nasywa Ramadhan, Faizal Fardhani Sigarlaki https://creativecommons.org/licenses/by/4.0
A Multi-Criteria Fuzzy AHP Approach to Determine PKH Recipients in Sumber Harapan Village
The development of information technology encourages the use of decision support systems to increase objectivity and efficiency in various fields, including the determination of social assistance recipients. In addition, through the main discussion carried out in this study aims to be able to analyze the process of determining the recipients of the Family Hope Program (PKH) in Sumber Harapan Village based on predetermined social and economic criteria and applying the Fuzzy Analytical Hierarchy Process (Fuzzy AHP) method to determine the importance weight of each criterion so that the assessment process becomes more objective, systematic, and transparent. And in addition, for the Research Method section used in this study is a qualitative approach through direct observation, interviews with village officials and related parties, and documentation studies of prospective PKH recipient data. The results of the study indicate that the Fuzzy AHP method is effective in determining the priority of aid recipients based on seven assessment criteria. Of the 15 alternatives analyzed, Lina Marlina (Alternative 8) obtained the highest priority value of 0.0920, followed by Siti Aminah (Alternative 2) with a value of 0.0895 and Nabila Sari (Alternative 12) of 0.0876, while Dedi Kurniawan (Alternative 5) obtained the lowest value of 0.0349. The developed web-based decision support system is able to automate the data management process, Fuzzy AHP calculations and present selection results quickly and accurately, thus helping village governments produce more targeted, transparent and accountable decisions in the distribution of PKH social assistance.
Copyright (c) 2026 Ade Amanda Yunita, William Ramdhan, Abdul Karim Syahputra https://creativecommons.org/licenses/by/4.0
Green Experience and Digital Engagement as Drivers of Generation Z Consumer Loyalty in Coffee Shops: A Mediation Model of Perceived Value and Brand Attachment
The increasing adoption of sustainable practices and digital technologies has reshaped consumer behavior, particularly among Generation Z coffee shop customers. This study examines the effects of green experience and digital engagement on Generation Z consumer loyalty through the mediating roles of perceived value and brand attachment. A quantitative survey was conducted among 300 Generation Z coffee shop customers in Pontianak, Indonesia. Data were collected using a structured questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that green experience significantly enhances perceived value (β = 0.728, p < 0.001), while digital engagement positively influences brand attachment (β = 0.799, p < 0.001). Perceived value emerged as the strongest predictor of consumer loyalty (β = 1.491, p < 0.001), followed by brand attachment (β = 0.089, p < 0.001). Furthermore, perceived value and brand attachment significantly mediate the relationships between green experience, digital engagement, and consumer loyalty. These findings demonstrate that Generation Z consumer loyalty is primarily developed through cognitive evaluations and emotional attachment. The study provides theoretical insights into sustainable consumer behavior and offers practical guidance for coffee shop managers in developing sustainability-oriented and digitally engaging strategies to strengthen long-term consumer loyalty.
Copyright (c) 2026 Mahardika Agung Madepo, Lina Budiarti, Romi Ferdian, Lidya Verawati https://creativecommons.org/licenses/by/4.0
Integration Model of Green Property and Digital Marketing in Business Development Strategies for Land Plotting in Bali Province
This research seeks to analyze the synergy between Green Property principles and Digital Marketing strategies in the development of land plotting in Bali. As climate change poses significant challenges and public awareness of environmental issues grows, property developers must embrace environmentally responsible practices. Employing a quantitative methodology, data was gathered from property stakeholders throughout various regions in Bali via surveys. The findings reveal that adopting eco-friendly technologies, such as renewable energy and sustainable building materials, significantly enhances the appeal of land plotting products to consumers. Furthermore, effective Digital Marketing strategies, including the use of social media and captivating visual content, are vital for establishing brand identity and improving product visibility in a competitive landscape. Although developers face obstacles related to digital skills and marketing comprehension, this study uncovers opportunities for a cohesive integration of both approaches. Recommendations emphasize the necessity for developers to invest in digital skills training and foster collaborations to create more impactful marketing strategies. By embracing Green Property principles alongside Digital Marketing, developers can solidify their market position while actively contributing to environmental sustainability in Bali.
Copyright (c) 2026 Theodorus Hadrianus Gabriel Asy, Yulianto Umar Rofi’i https://creativecommons.org/licenses/by/4.0