Analisis Sentimen Review Film Indonesia Berdasarkan Rentang Usia dengan Simple Moving Average untuk Optimasi Sistem Rekomendasi
DOI:
https://doi.org/10.35870/jtik.v10i1.5219Keywords:
Sentiment Analysis, Film Recommendations, Age Range, Indonesian Film Industry, Simple Moving Average (SMA)Abstract
The rapid growth of the Indonesian film industry has increased the number of audience reviews across various digital platforms. However, existing film recommendation systems remain general and do not consider demographic factors, particularly the age range of viewers. This study aims to analyze the sentiment of Indonesian film reviews based on audience age categories in order to optimize film recommendation systems. Primary data were collected through questionnaires distributed to respondents aged 13–30 years, supported by additional review data from social media and online platforms. The method applied is sentiment analysis combined with Simple Moving Average (SMA). The integration of age-based sentiment analysis with SMA has been shown to improve the accuracy and relevance of film recommendation systems. This study provides implications for streaming platform developers and film producers to consider age segmentation in distribution, promotion strategies, and quality improvement within the Indonesian film industry.
Downloads
References
Afisyah, C., & Sukmawati, A. I. (2023). Persepsi Mahasiswa Batak ISI Yogyakarta terhadap Komunikasi Budaya dan Simbol Lapo pada Film “Ngeri-Ngeri Sedap”. Jurnal Mahasiswa Komunikasi Cantrik, 3(2). https://doi.org/10.20885/cantrik.vol3.iss2.art3.
Amelia, D., & Sikumbang, A. T. (2024). Representasi Pesan Edukasi dalam Film “Di Bawah Umur”(Analisis Semiotika John Fiske Tentang Perilaku Remaja Gen-Z). Jurnal Indonesia: Manajemen Informatika dan Komunikasi, 5(2), 2001-2010. https://doi.org/10.35870/jimik.v5i2.836.
Azima, B. M., & Syahbani, D. B. (2024). Analisis Isi Kuantitatif Diskriminasi Berbasis Umur Terhadap Gangguan Kesehatan Mental Dalam Representasi Film ‘Kembang Api’. Jurnal Intelek Dan Cendikiawan Nusantara, 1(3), 3367-3379.
HASNA, S. K. (2021). Analisis Sentimen Data Ulasan Menggunakan Algoritma Support Vector Machine (Studi Kasus: Aplikasi Iflix).
Indah Purnamasari, N., & Nuris Azizah, A. (2023). Inovasi Penggunaan Media Pembelajaran: Film Animasi Diva sebagai Stimulan Pengembangan Kemampuan Menghafal Huruf Hijaiyah pada Anak. JURNAL WALADI: Wawasan Belajar Anak Usia Dini, 1 (2), 223–252.
Iqbal, M., & Rikarno, R. (2022). Adat Budaya Minangkabau Melihat Karya Film Dua Garis Biru Produksi Starvision Plus. Besaung: Jurnal Seni Desain dan Budaya, 7(1). https://doi.org/10.36982/jsdb.v7i1.2579.
Nurtikasari, Y., Alam, S., & Hermanto, T. I. (2022). Analisis Sentimen Opini Masyarakat Terhadap Film Pada Platform Twitter Menggunakan Algoritma Naive Bayes. INSOLOGI: Jurnal Sains dan Teknologi, 1(4), 411-423. https://doi.org/10.55123/insologi.v1i4.770.
PD, R. R. N. A., & Kusuma, S. (2023). Analisis Resepsi Kekerasan Seksual pada Perempuan dalam Film Penyalin Cahaya. Jurnal InterAct, 12(2), 97-106. https://doi.org/10.25170/interact.v12i2.4896.
Rifki, M. H., Utami, Y. R. W., & Harsadi, P. (2024). Text Mining Untuk Analisis Sentimen Review Film Menggunakan Algoritma Naïve Bayes. JuSiTik: Jurnal Sistem dan Teknologi Informasi Komunikasi, 7(2), 77-86. https://doi.org/10.32524/jusitik.v7i2.1168.
Sagita, D. I., Arthansa, R. M., & Sari, A. P. (2024). Komparasi Analisis Sentimen Ulasan Film Avengers: EndGame Di IMDB Menggunakan Metode Naive Bayes Dan SVM. Storage: Jurnal Ilmiah Teknik Dan Ilmu Komputer, 3(3), 156-166. https://doi.org/10.55123/storage.v3i3.4026.
Sinulingga, J. E. B., & Sitorus, H. C. K. (2024). Analisis Sentimen Opini Masyarakat terhadap Film Horor Indonesia Menggunakan Metode SVM dan TF-IDF. Jurnal Manajemen Informatika (JAMIKA), 14(1), 42-53. https://doi.org/10.34010/jamika.v14i1.11946.
Sriyatin, S., Arkam, R., & Lestari, E. (2023). Pemanfaatan Film Nussa Rara untuk Pengembangan Nilai Karakter Disiplin Anak Usia Dini. MENTARI: Jurnal Pendidikan Anak Usia Dini, 3(1).
Subagyo, I., Yulianto, L. D., Permadi, W., Dewantara, A. W., & Hartanto, A. D. (2019). Sentiment Analisis Review Film Di IMDB Menggunakan Algoritma SVM. e-Jurnal JUSITI (Jurnal Sistem Informasi dan Teknologi Informasi), 8(1), 47-56. https://doi.org/10.36774/jusiti.v8i1.600.
Vania, E., Nuraini, S., & Kartika, D. S. Y. (2022, September). Penggunaan Algoritma K-Means Clustering Untuk Menentukan Rekomendasi Film Indonesia. In Prosiding Seminar Nasional Teknologi dan Sistem Informasi (Vol. 2, No. 1, pp. 207-214). https://doi.org/10.33005/sitasi.v2i1.299.
Verakandhi, D. (2024). Perubahan preferensi menonton film pada era media sosial: Dampak short video dan implikasinya pada perilaku menonton film. Rekam: Jurnal Fotografi, Televisi, Animasi, 20(1), 37-45. https://doi.org/10.24821/rekam.v20i1.11286.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Sri Lestari, Wealty Sweet Charollyn Pasaribu

This work is licensed under a Creative Commons Attribution 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.
