Analisis Faktor Yang Mempengaruhi Penumpang Angkutan Umum Beralih Ke Transportasi Online Go-Jek Menggunakan Metode K-Means Clustering
DOI:
https://doi.org/10.35870/jtik.v6i1.381Keywords:
Online Transportation Go-Jek, Clusters, Data Mining, K-MeansAbstract
The objectives of this research are; 1) Can find the results of the analysis of switching factors, namely the age data, and 2) Can find the results of the analysis of switching factors, namely the data on the travel time of public transportation, 3) Can find the results of the analysis of switching factors, namely the data on the travel time of Go-jek 4) Can find the results of the analysis of switching factors, namely the tariff data, and 5) Can find the results of the analysis of switching factors, namely the data that is easy to obtain. This study was designed to determine the results of the analysis of factors that influence the shifting of public transportation to Go-jek online transportation using the K-means clustering algorithm. The data collection technique in this study was by means of a questionnaire through the Go-jek community in Indonesia and secondary data taken from the internet media. Based on the results of the analysis that has been carried out on the analysis of factors that influence public transport passengers to switch to Go-jek online transportation using the K-means clustering algorithm, it is hoped that further researchers will test with other clustering algorithms, and the rapidminer software used as research material can be developed further. become more other features.Downloads
References
Rendy, Y., 2018. Analisis Faktor-Faktor Yang Mempengaruhi Permintaan terhadap Ojek Online (Studi Kasus Pada Go-Jek di Kota Malang). Jurnal Ilmiah Mahasiswa FEB, 7(1).
Lestari, A.D., 2018. Analisis Multivariat Clustering K-Means Pada Kabupaten/Kota Di Provinsi Jawa Tengah Berdasarkan Indeks Pembangunan Manusia Tahun 2017 Dengan Bantuan Software SPSS (Doctoral dissertation, Universitas Negeri Semarang).
Sundari, S., Damanik, I.S., Windarto, A.P., Tambunan, H.S., Jalaluddin, J. and Wanto, A., 2019, September. Analisis K-Medoids Clustering Dalam Pengelompokkan Data Imunisasi Campak Balita Di Indonesia. In Prosiding Seminar Nasional Riset Information Science (SENARIS) (Vol. 1, pp. 687-696).
Ningrat, D.R., Di Asih, I.M. and Wuryandari, T., 2016. Analisis Cluster Dengan Algoritma K-Means Dan Fuzzy C-Means Clustering Untuk Pengelompokan Data Obligasi Korporasi. Jurnal Gaussian, 5(4), pp.641-650.
Ramdani, A.L. and Firmansyah, H.B., 2018. Clustering Application for UKT Determination Using Pillar K-Means Clustering Algorithm and Flask Web Framework. Indonesian Journal of Artificial Intelligence and Data Mining, 1(2), pp.53-59.
Haris, A. and Hendrian, E., 2019. Sistem Monitoring dan Klaster Ketersediaan Energi Menggunakan Metode K-Means pada Pembangkit Listrik Tenaga Surya. CESS (Journal of Computer Engineering, System and Science), 4(2), pp.266-271.
Mulaki, S.F., Setiyawati, N. and Wijaya, A.F., 2018. Analisis Data Mahasiswa Menggunakan Algoritma K-Means Clustering sebagai Dasar Pelaksana Promosi. JBASE-Journal of Business and Audit Information Systems, 1(2).
Bootupacademyai, 2021. Lengkap, Data Mining Adalah? Pengertian Hingga Belajar Clustering, bootup.ai, 2019. https://bootup.ai/blog/data-mining-adalah/ (accessed Jun. 04, 2021).
Devipursitasari, 2021. Eksplorasi Data Mining Software (Rapid Miner), iMe (iLearning Media), 2013. https://ilearning.me/2013/10/08/eksplorasi-data-mining-software-rapid-miner/ (accessed Jun. 04, 2021).
Fadhilah, A.M., Wahyuddin, M.I. and Hidayatullah, D., 2020. Analisis Faktor yang Mempengaruhi Perokok Beralih ke Produk Alternatif Tembakau (VAPE) menggunakan Metode K-Means Clustering. Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi), 5(2), pp.219-225.
Atmaja, E.H.S., 2019. Implementation of k-Medoids Clustering Algorithm to Cluster Crime Patterns in Yogyakarta. International Journal of Applied Sciences and Smart Technologies, 1(1), pp.33-44.
M, B, Tomy J., A., U, & Jacob, p., 2011. K- Means Clustering Student Data to Characterize Performance Patterns. International Journal of Advanced Computer Science and Applications, 1(3), 138–140
Durairaj, M. and Vijitha, C., 2014. Educational data mining for prediction of student performance using clustering algorithms. International Journal of Computer Science and Information Technologies, 5(4), pp.5987-5991.
Downloads
Published
Issue
Section
License
Copyright (c) 2022 Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi)

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors who publish with this journal agree to the following terms:
1. Copyright Retention and Open Access License
Authors retain copyright of their work and grant the journal non-exclusive right of first publication under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
This license allows unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
2. Rights Granted Under CC BY 4.0
Under this license, readers are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, including commercial use
- No additional restrictions — the licensor cannot revoke these freedoms as long as license terms are followed
3. Attribution Requirements
All uses must include:
- Proper citation of the original work
- Link to the Creative Commons license
- Indication if changes were made to the original work
- No suggestion that the licensor endorses the user or their use
4. Additional Distribution Rights
Authors may:
- Deposit the published version in institutional repositories
- Share through academic social networks
- Include in books, monographs, or other publications
- Post on personal or institutional websites
Requirement: All additional distributions must maintain the CC BY 4.0 license and proper attribution.
5. Self-Archiving and Pre-Print Sharing
Authors are encouraged to:
- Share pre-prints and post-prints online
- Deposit in subject-specific repositories (e.g., arXiv, bioRxiv)
- Engage in scholarly communication throughout the publication process
6. Open Access Commitment
This journal provides immediate open access to all content, supporting the global exchange of knowledge without financial, legal, or technical barriers.
