Fenomena Perubahan Pola Konsumsi Rumah Tangga di Era Digital: Pengembangan Aplikasi Mobile Berbasis Machine learning untuk Manajemen Anggaran dan Preferensi Belanja
DOI:
https://doi.org/10.31004/joecy.v5i2.3720Abstract
Tujuan penelitian ini adalah menganalisis transformasi pola konsumsi rumah tangga di era digital serta mengeksplorasi potensi pengembangan aplikasi mobile berbasis machine learning untuk manajemen anggaran dan preferensi belanja. Penelitian ini dilatarbelakangi oleh pesatnya adopsi platform digital, khususnya e-commerce dan teknologi keuangan, yang telah mengubah perilaku konsumen serta struktur keuangan rumah tangga. Meskipun digitalisasi menawarkan efisiensi dan kenyamanan, fenomena ini juga menimbulkan tantangan berupa konsumsi impulsif, ketidakstabilan keuangan, dan kesenjangan digital.
Bahan dan metode. Penelitian ini menggunakan pendekatan kualitatif dengan desain studi literatur. Publikasi akademik, laporan institusional, serta studi empiris yang relevan dari tahun 2015 hingga 2025 dikumpulkan secara sistematis dan dianalisis dengan metode analisis tematik. Tema utama yang dikaji meliputi faktor pendorong transformasi konsumsi digital, variasi sosial-ekonomi dalam perilaku rumah tangga, peran aplikasi mobile dalam manajemen keuangan, serta integrasi machine learning dalam keuangan konsumen. Analisis komparatif juga digunakan untuk mengidentifikasi persamaan dan perbedaan antar penelitian terdahulu, dengan menjaga validitas dan reliabilitas melalui triangulasi sumber.
Hasil. Temuan menunjukkan bahwa konsumsi digital didorong oleh kemajuan teknologi, perubahan gaya hidup, dan faktor sosial-ekonomi. Aplikasi mobile terbukti meningkatkan kesadaran finansial, disiplin anggaran, serta literasi keuangan rumah tangga. Namun, aplikasi yang ada masih kurang adaptif dan personal, sehingga retensi pengguna rendah. Integrasi machine learning memberikan peluang untuk analisis prediktif pengeluaran, rekomendasi personal, serta fitur pengendalian keuangan yang mampu mengurangi perilaku impulsif.
Kesimpulan. Konsumsi digital rumah tangga menghadirkan peluang sekaligus risiko. Aplikasi berbasis machine learning berpotensi menjadi bukan hanya alat penganggaran, tetapi juga intervensi keuangan yang inklusif, edukatif, dan berkelanjutan. Keberhasilan adopsinya bergantung pada transparansi, keamanan data, dan inklusivitas, sehingga relevan untuk berbagai tipe rumah tangga di Indonesia maupun secara global.
Keywords: Konsumsi Digital, Keuangan Rumah Tangga, Aplikasi Mobile, Machine learning, Literasi Keuangan
References
Chen, L., Xu, L., & Arpan, L. M. (2021). Machine learning–based mobile applications for personal finance: Adoption, impacts, and policy implications. Telematics and Informatics, 57, 101516. https://doi.org/10.1016/j.tele.2020.101516
Nugraha, A., & Widodo, S. (2022). Digital consumption patterns of Indonesian households after COVID-19 pandemic. Journal of Asian Business and Economic Studies, 29(3), 201–215. https://doi.org/10.1108/JABES-07-2021-0105
Rahmawati, E., & Fitriani, N. (2022). Personalized shopping experience and impulsive buying behavior in online retail. Journal of Retailing and Consumer Services, 68, 103042. https://doi.org/10.1016/j.jretconser.2022.103042
Santoso, H., Nugroho, L., & Wulandari, A. (2019). Household income and digital consumption: Evidence from Indonesia. International Journal of Emerging Markets, 14(6), 1092–1109. https://doi.org/10.1108/IJOEM-08-2018-0426
Widyanto, A., & Setyowati, R. (2021). E-commerce adoption and the shifting household consumption in Indonesia. Journal of Economic Structures, 10(1), 25. https://doi.org/10.1186/s40008-021-00259-5
Bank Indonesia. (2021). The impact of e-commerce on household consumption and Indonesia’s economic growth. Bulletin of Monetary Economics and Banking, 24(4), 415–436. https://doi.org/10.21098/bemp.v24i4.1810
Dhandra, T. K. (2020). Does self-esteem matter? A framework depicting role of self-esteem between dispositional traits and compulsive buying. Journal of Retailing and Consumer Services, 55, 102135. https://doi.org/10.1016/j.jretconser.2020.102135
Hidayat, T., & Ananda, R. (2020). Digital literacy and household financial management in the era of online consumption. Journal of Indonesian Economy and Business, 35(2), 95–112. https://doi.org/10.22146/jieb.52415
Saputra, R., Nugroho, A., & Putri, D. (2022). Adoption of digital financial applications and its impact on household budgeting behavior in Indonesia. Journal of Economics and Development, 24(2), 182–197. https://doi.org/10.1108/JED-01-2021-0003
Zhang, Y., Chen, J., & Lee, J. (2020). Applying machine learning to predict consumer behavior in digital finance. Decision Support Systems, 130, 113231. https://doi.org/10.1016/j.dss.2019.113231
Azzahra, N. F., & Wibowo, T. (2023). Household debt and digital lending behavior in Indonesia. Journal of Behavioral and Experimental Finance, 37, 100806. https://doi.org/10.1016/j.jbef.2022.100806
Demirgüç-Kunt, A., Klapper, L., Singer, D., Ansar, S., & Hess, J. (2018). The Global Findex Database 2017: Measuring financial inclusion and the fintech revolution. World Bank. https://doi.org/10.1596/978-1-4648-1259-0
Kusnandar, A., & Fanggidae, R. E. (2020). Digital lifestyle and consumption patterns of Indonesian millennials. Indonesian Journal of Business and Entrepreneurship, 6(1), 23–34. https://doi.org/10.17358/ijbe.6.1.23
Li, Y., Wu, J., & Mai, F. (2021). The effect of data security and privacy concerns on consumers’ adoption of fintech apps. Information & Management, 58(7), 103495. https://doi.org/10.1016/j.im.2021.103495
Braun, V., & Clarke, V. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health, 11(4), 589–597. https://doi.org/10.1080/2159676X.2019.1628806
Noble, H., & Smith, J. (2015). Issues of validity and reliability in qualitative research. Evidence-Based Nursing, 18(2), 34–35. https://doi.org/10.1136/eb-2015-102054
Petticrew, M., & Roberts, H. (2016). Systematic reviews in the social sciences: A practical guide. John Wiley & Sons. https://doi.org/10.1002/9780470754887
Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039
Belanche, D., Casaló, L. V., & Flavián, C. (2019). Artificial Intelligence in FinTech: Understanding robo-advisors adoption among customers. Industrial Management & Data Systems, 119(7), 1411–1430. https://doi.org/10.1108/IMDS-08-2018-0368
Omar, N. A., Leach, D., & March, J. (2021). Digital impulse buying: Examining the role of promotions, payment convenience and consumer traits. Journal of Retailing and Consumer Services, 61, 102567. https://doi.org/10.1016/j.jretconser.2021.102567
Priporas, C. V., Stylos, N., & Fotiadis, A. K. (2017). Generation Z consumers’ expectations of interactions in smart retailing: A future agenda. Computers in Human Behavior, 77, 374–381. https://doi.org/10.1016/j.chb.2017.01.058
Sheth, J. (2020). Impact of COVID-19 on consumer behavior: Will the old habits return or die? Journal of Business Research, 117, 280–283. https://doi.org/10.1016/j.jbusres.2020.05.059
Fernandes, D., Ferreira, F. A. F., & Jalali, M. S. (2022). Enhancing household financial literacy through mobile applications: Evidence from emerging markets. International Journal of Consumer Studies, 46(4), 1380–1394. https://doi.org/10.1111/ijcs.12753
Putri, A., & Hartono, B. (2020). Adoption and retention of mobile financial applications in Indonesia. Journal of Indonesian Economy and Business, 35(3), 201–218. https://doi.org/10.22146/jieb.58041
Reddy, P., Sharma, A., & Singh, R. (2021). Mobile personal finance apps: The role of visual data analytics in consumer budgeting. Journal of Retailing and Consumer Services, 62, 102651. https://doi.org/10.1016/j.jretconser.2021.102651
Xu, H., Teo, H. H., Tan, B. C. Y., & Agarwal, R. (2021). The role of mobile applications in promoting sustainable consumer finance. Information Systems Research, 32(1), 15–34. https://doi.org/10.1287/isre.2020.0987
Yu, H. (2020). Mobile financial management applications and consumer budgeting behavior: An empirical study. Journal of Behavioral and Experimental Economics, 87, 101564. https://doi.org/10.1016/j.socec.2020.101564
Dwivedi, Y. K., Hughes, L., Kar, A. K., Baabdullah, A. M., Grover, P., Abbas, R., & Raghavan, V. (2021). Climate of consumer behavior research in the digital age: A bibliometric analysis. International Journal of Information Management, 59, 102336. https://doi.org/10.1016/j.ijinfomgt.2021.102336
Ghosh, S. (2022). Digital lending and household debt: Evidence from Southeast Asia. Emerging Markets Review, 53, 100876. https://doi.org/10.1016/j.ememar.2022.100876
Kapoor, K., Dwivedi, Y. K., Piercy, N. F., & Rana, N. P. (2021). Digital adoption in emerging markets: Demographic determinants and policy implications. Journal of Business Research, 124, 620–633. https://doi.org/10.1016/j.jbusres.2020.11.014
Omar, N. A., Ramayah, T., & Thurasamy, R. (2022). The role of trust and privacy concerns in mobile financial applications adoption. Technological Forecasting and Social Change, 180, 121688. https://doi.org/10.1016/j.techfore.2022.121688
UNCTAD. (2021). Digital economy report 2021: Cross-border data flows and development. United Nations. https://doi.org/10.18356/9789210059148
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