Analisis Customer Behavior BPJS Ketenagakerjaan: Menentukan Strategi Pelayanan melalui Big Data Analytics
DOI:
https://doi.org/10.61626/jamsostek.v3i1.108Keywords:
Big Data Analytics, BPJS Ketenagakerjaan, Customer Behavior, Aplikasi Jamsostek Mobile (JMO), Strategi PelayananAbstract
Menghadapi era Volatility, Uncertainty, Complexity, and Ambiguity (VUCA), data menjadi semakin kompleks, sulit diolah, dipahami dan diinterpretasikan. Data historis layanan, seperti pola kunjungan, kelompok usia, dan kebutuhan pelanggan dapat dianalisis untuk memahami customer behavior. Penelitian ini bertujuan memberikan gambaran mengenai pemanfaatan big data analytics untuk merumuskan strategi pelayanan berbasis customer behavior. Penelitian dilakukan di Kantor Cabang BPJS Ketenagakerjaan Madiun dengan menerapkan metode deskriptif melalui big data analytics, yang meliputi tahap data preparation, data visualization, dan data analysis. Hasil studi menunjukkan bahwa penerapan big data analytics dapat memberikan wawasan yang bernilai tentang customer behavior peserta BPJS Ketenagakerjaan, sehingga dapat dijadikan acuan dalam menentukan strategi pelayanan yang lebih efektif dan efisien. Berdasarkan hasil analisis data, disimpulkan bahwa penambahan personel layanan diperlukan setiap awal bulan untuk mengantisipasi lonjakan kunjungan peserta. Informasi terkait perubahan skema layanan juga perlu disosialisasikan setidaknya dua bulan sebelum diberlakukan, untuk memberi waktu kepada peserta memahaminya. Strategi Direct Information Services disarankan bagi peserta yang berusia lebih dari 42 tahun, karena jumlah kunjungan atas permintaan informasinya yang tinggi. Selain itu, direkomendasikan melakukan pemutakhiran aplikasi Jamsostek Mobile (JMO) menjadi lebih user-friendly bagi Generasi Z dan Milenial. Pemantauan JMO secara rutin juga perlu dilakukan untuk memastikan keandalan performanya.
Downloads
References
Adaga, Ejuma Martha, Gold Nmesoma Okorie, Zainab Efe Egieya, Uneku Ikwue, Chioma Ann Udeh, Donald Obinna DaraOjimba, dan Osato Itohan Oriekhoe. 2023. “The Role of Big Data in Business: A Critical Review”. Computer Science & IT Research Journal 4 (3). https://doi.org/10.51594/csitrj.v4i3.686.
Arumugam, M. dan C. Jayanthi. 2022. “Consumer Behaviour Analysis in Social Network Using Big Data”. International Journal of Health Sciences 6(S2), 8699-8706. https://doi.org/10.53730/ijhs.v6nS2.7246.
Broman, Karl W. dan Kara H. Woo. 2018. “Data Organization in Spreadsheets”. The American Statistician 72 (1). https://doi.org/10.1080/00031305.2017.1375989.
C., Devi Akalya, Ghanasiyaa S., Harshini K., Shanmathy S., Poojashree K. E., dan Kruthikkha P. C. 2022. “Consumer Behaviour Analysis”. International Journal of Research and Applied Technology (INJURATECH) 2 (1). https://doi.org/10.34010/injuratech.v2i1.6536.
Caihua, Zhang dan Tongxin Tan. 2020. “The Impact of Big Data Analysis on Consumer Behavior”. J. Phys.: Conf. Ser. https://iopscience.iop.org/article/10.1088/1742- 6596/1544/1/012165.
Davenport, Thomas H. 2014. “How strategists use “big data” to support internal business decisions, discovery and production”. Strategy & Leadership 42 (4). https://doi.org/10.1108/SL-05-2014-0034.
Davis, Leann dan Geethu Wilson. 2020. A Study on Consumer Behavior Using Big Data Analytics. https://ijcrt.org/papers/IJCRT22A6732.pdf.
Dolot, Anna. 2018. “The characteristics of Generation Z”. e-mentor 2 (74). https://www.doi.org/10.15219/em74.1351.
Earley, Christine E. 2015. “Data analytics in auditing: Opportunities and challenges”. Business Horizons, 58(5), 493–500. https://doi.org/10.1016/j.bushor.2015.05.002.
Fauziyah, Nur Rosyda. 2022. VUCA: Volatility, Uncertainty, Complexity, Ambiguity Dalam Dunia Bisnis. Diakses pada 28 Maret 2024, https://www.gramedia.com/best- seller/vuca/.
Florencondia, Noel T., Ladignon Christopher M., Muldong Roviel M.C. 2024. “Enhancing Performance Metrics: A Google Looker Studio Approach to Key Performance Indicator (KPI) Management System for Homecorp Offshore Drafting Team”. Engineering and Technology Journal, 9(5), 4076–4088. https://doi.org/10.47191/etj/v9i05.25.
Gómez-Díaz, Javier Andrés. 2016. “Reviewing a Consumer Decision Making Model in Online Purchasing: An ex-post-fact Study with a Colombian Sample”. Avances en Psicología Latinoamericana, 34(2), 273-292. http://dx.doi.org/10.12804/apl34.2.2016.05.
Hermawan, Ade. 2024. “Mengintip Celah antara Potensi dan Tantangan Big Data pada Layanan Jaminan Sosial Ketenagakerjaan Indonesia”. Jurnal Jamsostek 2(2):185–200. https://doi.org/10.61626/jamsostek.v2i2.59.
Khade, Anindita A. 2016. “Performing Customer Behavior Analysis Using Big Data Analytics”. Procedia Computer Science 79: 986-992. https://doi.org/10.1016/j.procs.2016.03.125.
Kotler, P., Kevin Keller, Mairead Brady, Malcolm Goodman, dan Torben Hansen. 2019. Marketing Management. Singapore: Pearson Education.
Lang, Lumi. 2022. “Service Strategy Analysis of Big Data Management in Small and Medium- sized Enterprises”. Frontiers in Business, Economics and Management, 6(2), 224-228. https://doi.org/10.54097/fbem.v6i2.3033.
Li, Wei. 2021. “Analysis on Application of Big Data Technology in Audit Practice”. Advances in Intelligent Systems and Computing, 1303, 1042–1048. Diakses pada 25 Agustus 2023. https://doi.org/10.1007/978-981-33-4572-0_149.
Li, Yifei. 2023. “Big Data Analysis in Consumer Behavior: Evidence from Social Media and MobilePayment”. Advances in Economics, Management and Political Sciences, 64:269-275. https://doi.org/10.54254/2754-1169/64/20231548.
Ma, Alfred C. 2020. “Making Data Reports Useful: From Descriptive to Predictive”. Cureus 12 (10). https://pubmed.ncbi.nlm.nih.gov/33194487/.
Megatef, Sima Ghaleb., Raed Ahmad Momami, dan Ghaiath Altrjman. 2019. “The Evaluation of Complaint Handling Processes in Five Star Hotels and its Reflection on Customers' Satisfaction”. African Journal of Hospitality Tourism and Leisure 8 (2). https://www.researchgate.net/publication/331684847_The_Evaluation_of_Complai nt_Handling_Process_in_Five_Star_Hotels_and_its_Reflection_on_Customers'_Sati sfaction.
Mothersbaugh, David. 2019. Consumer Behavior: Building Marketing Strategy. New York: McGraw-Hill Higher Education.
Osmundson, Brooke. 2022. “An In-Depth Guide to Get Started with Looker Studio (The New Google Data Studio)”. Search Engine Journal – Marketing Analytics. Diakses pada 5 November 2023. https://www.searchenginejournal.com/google-looker-studio- beginner-guide/471369/.
Peraturan Presiden (PERPRES) Nomor 25. 2020. Tata Kelola Badan Penyelenggara Jaminan Sosial.
Rayhan, Rajan, Abu Rayhan, dan Robert Kinzler. 2023. “Exploring the Power of Data Manipulation and Analysis: A Comprehensive Study of NumPy, SciPy, and Pandas”. https://doi.org/10.13140/RG.2.2.22390.16968.
Safitri, Riesty Amaylia. 2022. “Kesiapan Generasi Milenial Sebagai Role Model di Era New Normal”. Social, Humanities, and Educational Studies (SHES): Conference Series 5 (1). https://doi.org/10.20961/shes.v5i1.57798.
Sahoo, Kabita., Abhaya Kumar Samal, Jitendra Pramanik, dan Subhendu Kumar Pani. 2019. “Exploratory Data Analysis using Python”. International Journal of Innovative Technology and Exploring Engineering 8(12): 4727-4735. https://www.researchgate.net/publication/341121348_Exploratory_Data_Analysis_ using_Python.
Santoso, Rachmad., Hisbulloh Ahlis Munawi, dan Ary Permatedeny Nevita. 2020. “Analisa Perilaku Konsumen: Strategi Memenangkan Persaingan Bisnis di Era Ekonomi Digital”. Jurnal Teknologi Terapan G-Tech 4(1):286-293. https://media.neliti.com/media/publications/406800-analisa-perilaku-konsumen-strategi- memen-93a3dbdc.pdf.
Schiffman, Leon G., dan Joe Wisenblit. 2018. Consumer Behavior (What's New in Marketing). New Jersey: Pearson.
Sharma, Sharad dan Archita Kandel. 2023. Data Visualization and Its Impact in Decision Making in Business. https://doi.org/10.13140/RG.2.2.21906.12483.
Slabá, Marie. 2019. “The Impact of Age on The Customers Buying Behaviour and Attitude to Price”. Littera Scripta 12 (2). https://doi.org/10.36708/Littera_Scripta2019/2/11.
Solomon, Michael Robert, Stephen Dann, Susan Dann, dan Rebekah Russel-Bennett. 2019. “Consumer Behavior: Buying, Having, and Being”. https://www.researchgate.net/publication/27476273.
Srivastava, Deepmala. 2023. “An Introduction to Data Visualization Tools and Techniques in Various Domains”. International Journal of Computer Trends and Technology 71 (4). https://doi.org/10.14445/22312803/IJCTT-V71I4P116.
Statista. 2023. Volume of data/information created, captured, copied, and consumed worldwide from 2010 to 2020, with forecasts from 2021 to 2025. Diakses pada 12 Mei 2023, https://www.statista.com/statistics/871513/worldwide-data-created/
The Economist. 2017. The World's Most Valuable Resource is No Longer Oil, but Data. Diakses pada 20 Juli 2023. https://www.economist.com/leaders/2017/05/06/the-worlds-most- valuable-resource-is-no-longer-oil-but-data.
Vasilopoulou, C., Leonidas Theodorakopoulos, dan Ioanna Giotopoulos, K. 2023. “Big Data and Consumer Behavior: The Power and Pitfalls of Analytics in the Digital Age”. Technium Social Sciences Journal. https://www.semanticscholar.org/paper/Big-Data-and-Consumer-Behavior%3A-The- Power-and-of-in-Vasilopoulou Theodorakopoulos/2a7b1abde61d6733e1e17a33cdd4fd585fb6579f.
Wardhana, Aditya, Syahputra Syahputra, dan Kristina Sisilia. 2019. Riset Pemasaran. Bandung: Anugrah Adi Cipta.
World Economic Forum. 2023. Future of Job Survey 2023. Diakses pada 7 September 2023. https://www3.weforum.org/docs/WEF_Future_of_Jobs_2023.pdf.
Yau, Peter ChunYu, Dennis Wong, Woo Hok Luen, dan Joseph Leung. 2020. Understanding Consumer Behavior by Big Data Visualization in the Smart Space Laboratory. In Proceedings of the 5th International Conference on Big Data and Computing (ICBDC '20). Association for Computing Machinery, New York, NY, USA, 13–17. https://doi.org/10.1145/3404687.3404705.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Jurnal Jamsostek
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
