STRATEGI PERENCANAAN PENDIDIKAN BERBASIS DATA UNTUK MENINGKATKAN MUTU SEKOLAH DI ERA SOCIETY 5.0
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Abstract
This study discusses the effectiveness, challenges, and technological developments in data-based education planning in the context of the digital era. The background of this study stems from the educational needs in the Society 5.0 era, which demands 21st-century competencies and the use of data to support evidence-based decision-making. The research uses a literature study approach by reviewing articles from reputable national and international journals in the 2015–2025 period. The analysis was conducted using a thematic approach that grouped the findings into three main dimensions, namely planning effectiveness, implementation challenges, and the development of Educational Data Mining (EDM) and Learning Analytics (LA). The results of the study show that data-based planning effectively improves objectivity, equity of services, and transparency in education governance. However, its implementation faces obstacles in the form of unintegrated data quality, low data literacy among educators, infrastructure limitations, and cultural and ethical issues related to privacy. Meanwhile, the development of EDM and LA opens up opportunities for planning transformation with predictive and prescriptive approaches that support personalised learning and adaptive resource management. This study emphasises the importance of integrating technological innovation, data governance policies, and human resource capacity building to strengthen the implementation of data-based educational planning in Indonesia.
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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
References
Anastassia Amellia Kharis, S., & Haqqi Anna Zili, A. (2022). Learning Analytics dan Educational Data Mining pada Data Pendidikan. Jurnal Riset Pembelajaran Matematika Sekolah, 6, 12–20.
Dwijaksana, N. A., & Muhammad, A. H. (2025). Pemanfaatan Teknologi Learning Analytics Dalam Mendeteksi Pola Belajar Untuk Meningkatkan Kualitas Pembelajaran di Smk Negeri 1 Kabupaten Sorong. Jurnal Pendidikan Universitas Garut, 122–128. https://doi.org/https://doi.org/10.52434/jpu.v19i1.42480
Gengeç Benli, Ş., İçer, S., Demirci, E., Karaman, Z. F., Ak, Z., Acer, İ., … Sertkaya, B. (2024). Data-driven exploratory method investigation on the effect of dyslexia education at brain connectivity in Turkish children: a preliminary study. Brain Structure and Function, 229(7), 1697–1712. https://doi.org/10.1007/s00429-024-02820-5
Hadijaya, Y., Azizi, A. R., Monalisa, F. N., & Fadla, S. L. (2022). Perencanaan Pendidikan dalam Meningkatkan Efektivitas dan Mutu Pendidikan di MTs Negeri Binjai. IKAMAS: Jurnal Manajemen Pendidikan Islam, 02(02), 130–140. Retrieved from https://ikamas.org/jurnal/index.php/ikamas/article/view/46
Hanžel, V., Bertalanič, B., & Fortuna, C. (2025). Towards data-driven electricity management: multi-region uniform data and knowledge graph. Scientific Data , 12(1), 1–21. https://doi.org/10.1038/s41597-024-04310-z
Kalita, E., Oyelere, S. S., Gaftandzhieva, S., Rajesh, K. N. V. P. S., Jagatheesaperumal, S. K., Mohamed, A., … Ali, T. (2025). Educational data mining: a 10-year review. Discover Computing, 28(1). https://doi.org/10.1007/s10791-025-09589-z
Lampropoulos, G., & Evangelidis, G. (2025). Learning Analytics and Educational Data Mining in Augmented Reality, Virtual Reality, and the Metaverse: A Systematic Literature Review, Content Analysis, and Bibliometric Analysis. Applied Sciences (Switzerland), 15(2). https://doi.org/10.3390/app15020971
Moh. Arifudin, F. Z. (2021). Planning (Perencanaan) dalam Manajemen Pendidikan Islam. MA’ALIM: Jurnal Pendidikan Islam, 1(1), 28–45.
Mulyadi, M. (2024). DATA-DRIVEN EDUCATION MANAGEMENT: MORE INFORMED DECISION-MAKING. International Journal of Society Reviews (INJOSER), 4(02), 7823–7830.
Mustafa, I. A., Syamsuddin, Ayusaputri, K. G., Warman, & Hidayanto, D. N. (2025). APPLICATION OF DATA-DRIVEN DECISION MAKING IN EDUCATION MANAGEMENT IN EAST KUTAI REGENCY. As - S A B I Q U N Jurnal Pendidikan Islam Anak Usia Dini, 7(Dddm), 308–321.
Ogata, H., Liang, C., Toyokawa, Y., Hsu, C. Y., Nakamura, K., Yamauchi, T., … Majumdar, R. (2024). Co-designing Data-Driven Educational Technology and Practice: Reflections from the Japanese Context. Technology, Knowledge and Learning, 29(4), 1711–1732. https://doi.org/10.1007/s10758-024-09759-w
Ramaditya, M., Syamsari, S., Hadirawati, H., & Hanifah, A. (2023). The Effect of Digital Learning, Innovative Behavior and Knowledge Management on Private Higher Education Performance. AL-ISHLAH: Jurnal Pendidikan, 15(4), 6342–6360. https://doi.org/10.35445/alishlah.v15i4.3773
Robert Hegestedt, Jalal Nouri, R., & Rundquist, U. F. (2023). Data-Driven School Improvement and Data-Literacy in K-12: Findings from a Swedish National Program. International Journal of Emerging Technologies in Learning (IJET), 18(24), 133–148. https://doi.org/doi.org/10.3991/ijet.v18i15.37241
Rohmah, I. I., Rofiq, A., & Ihwan, M. B. (2025). Data Driven Educational Planning Strategy: Examining Challenges and Opportunities in the Digital Era. Electronic Journal of Education, Social Economics and Technology, 6(1), 327–336. https://doi.org/10.33122/ejeset.v6i1.438
Romero, C., & Ventura, S. (2020). Educational data mining and learning analytics: An updated survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 10(3). https://doi.org/10.1002/widm.1355
Sajja, R., Sermet, Y., Cwiertny, D., & Demir, I. (2023). Integrating AI and Learning Analytics for Data-Driven Pedagogical Decisions and Personalized Interventions in Education. Technology, Knowledge and Learning. https://doi.org/10.1007/s10758-025-09897-9
Singh, D., & Kaur, J. (2024). Data-Driven Decision Making in Education: Role of Big Data technologies. Singh, Kaur. Wisdom Leaf Press, 65–71. https://doi.org/10.55938/wlp.v1i5.183
Siregar, K. E. (2024). Increasing Digital Literacy In Education : Analysis Of Challenges And Opportunities Through Literature Study. International Journal of Multilingual Education and Applied Linguistics, 1(2), 10–25. Retrieved from https://international.aspirasi.or.id/index.php/IJMEAL/article/view/18
Sun, A. X., & Mizumoto, A. (2025). Exploring the barriers to data-driven learning in the classroom: a systematic qualitative synthesis. Applied Corpus Linguistics, 5(2), 100126. https://doi.org/10.1016/j.acorp.2025.100126
Tian, D., Jia, X., Ma, R., Liu, S., Liu, W., & Hu, C. (2021). BinDeep: A deep learning approach to binary code similarity detection. Expert Systems with Applications, 168, 114348. https://doi.org/10.1016/j.eswa.2020.114348
Uddin, S., Ong, S., & Lu, H. (2022). Machine learning in project analytics: a data-driven framework and case study. Scientific Reports, 12(1), 1–13. https://doi.org/10.1038/s41598-022-19728-x
Main Article Content
Abstract
This study discusses the effectiveness, challenges, and technological developments in data-based education planning in the context of the digital era. The background of this study stems from the educational needs in the Society 5.0 era, which demands 21st-century competencies and the use of data to support evidence-based decision-making. The research uses a literature study approach by reviewing articles from reputable national and international journals in the 2015–2025 period. The analysis was conducted using a thematic approach that grouped the findings into three main dimensions, namely planning effectiveness, implementation challenges, and the development of Educational Data Mining (EDM) and Learning Analytics (LA). The results of the study show that data-based planning effectively improves objectivity, equity of services, and transparency in education governance. However, its implementation faces obstacles in the form of unintegrated data quality, low data literacy among educators, infrastructure limitations, and cultural and ethical issues related to privacy. Meanwhile, the development of EDM and LA opens up opportunities for planning transformation with predictive and prescriptive approaches that support personalised learning and adaptive resource management. This study emphasises the importance of integrating technological innovation, data governance policies, and human resource capacity building to strengthen the implementation of data-based educational planning in Indonesia.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
References
Anastassia Amellia Kharis, S., & Haqqi Anna Zili, A. (2022). Learning Analytics dan Educational Data Mining pada Data Pendidikan. Jurnal Riset Pembelajaran Matematika Sekolah, 6, 12–20.
Dwijaksana, N. A., & Muhammad, A. H. (2025). Pemanfaatan Teknologi Learning Analytics Dalam Mendeteksi Pola Belajar Untuk Meningkatkan Kualitas Pembelajaran di Smk Negeri 1 Kabupaten Sorong. Jurnal Pendidikan Universitas Garut, 122–128. https://doi.org/https://doi.org/10.52434/jpu.v19i1.42480
Gengeç Benli, Ş., İçer, S., Demirci, E., Karaman, Z. F., Ak, Z., Acer, İ., … Sertkaya, B. (2024). Data-driven exploratory method investigation on the effect of dyslexia education at brain connectivity in Turkish children: a preliminary study. Brain Structure and Function, 229(7), 1697–1712. https://doi.org/10.1007/s00429-024-02820-5
Hadijaya, Y., Azizi, A. R., Monalisa, F. N., & Fadla, S. L. (2022). Perencanaan Pendidikan dalam Meningkatkan Efektivitas dan Mutu Pendidikan di MTs Negeri Binjai. IKAMAS: Jurnal Manajemen Pendidikan Islam, 02(02), 130–140. Retrieved from https://ikamas.org/jurnal/index.php/ikamas/article/view/46
Hanžel, V., Bertalanič, B., & Fortuna, C. (2025). Towards data-driven electricity management: multi-region uniform data and knowledge graph. Scientific Data , 12(1), 1–21. https://doi.org/10.1038/s41597-024-04310-z
Kalita, E., Oyelere, S. S., Gaftandzhieva, S., Rajesh, K. N. V. P. S., Jagatheesaperumal, S. K., Mohamed, A., … Ali, T. (2025). Educational data mining: a 10-year review. Discover Computing, 28(1). https://doi.org/10.1007/s10791-025-09589-z
Lampropoulos, G., & Evangelidis, G. (2025). Learning Analytics and Educational Data Mining in Augmented Reality, Virtual Reality, and the Metaverse: A Systematic Literature Review, Content Analysis, and Bibliometric Analysis. Applied Sciences (Switzerland), 15(2). https://doi.org/10.3390/app15020971
Moh. Arifudin, F. Z. (2021). Planning (Perencanaan) dalam Manajemen Pendidikan Islam. MA’ALIM: Jurnal Pendidikan Islam, 1(1), 28–45.
Mulyadi, M. (2024). DATA-DRIVEN EDUCATION MANAGEMENT: MORE INFORMED DECISION-MAKING. International Journal of Society Reviews (INJOSER), 4(02), 7823–7830.
Mustafa, I. A., Syamsuddin, Ayusaputri, K. G., Warman, & Hidayanto, D. N. (2025). APPLICATION OF DATA-DRIVEN DECISION MAKING IN EDUCATION MANAGEMENT IN EAST KUTAI REGENCY. As - S A B I Q U N Jurnal Pendidikan Islam Anak Usia Dini, 7(Dddm), 308–321.
Ogata, H., Liang, C., Toyokawa, Y., Hsu, C. Y., Nakamura, K., Yamauchi, T., … Majumdar, R. (2024). Co-designing Data-Driven Educational Technology and Practice: Reflections from the Japanese Context. Technology, Knowledge and Learning, 29(4), 1711–1732. https://doi.org/10.1007/s10758-024-09759-w
Ramaditya, M., Syamsari, S., Hadirawati, H., & Hanifah, A. (2023). The Effect of Digital Learning, Innovative Behavior and Knowledge Management on Private Higher Education Performance. AL-ISHLAH: Jurnal Pendidikan, 15(4), 6342–6360. https://doi.org/10.35445/alishlah.v15i4.3773
Robert Hegestedt, Jalal Nouri, R., & Rundquist, U. F. (2023). Data-Driven School Improvement and Data-Literacy in K-12: Findings from a Swedish National Program. International Journal of Emerging Technologies in Learning (IJET), 18(24), 133–148. https://doi.org/doi.org/10.3991/ijet.v18i15.37241
Rohmah, I. I., Rofiq, A., & Ihwan, M. B. (2025). Data Driven Educational Planning Strategy: Examining Challenges and Opportunities in the Digital Era. Electronic Journal of Education, Social Economics and Technology, 6(1), 327–336. https://doi.org/10.33122/ejeset.v6i1.438
Romero, C., & Ventura, S. (2020). Educational data mining and learning analytics: An updated survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 10(3). https://doi.org/10.1002/widm.1355
Sajja, R., Sermet, Y., Cwiertny, D., & Demir, I. (2023). Integrating AI and Learning Analytics for Data-Driven Pedagogical Decisions and Personalized Interventions in Education. Technology, Knowledge and Learning. https://doi.org/10.1007/s10758-025-09897-9
Singh, D., & Kaur, J. (2024). Data-Driven Decision Making in Education: Role of Big Data technologies. Singh, Kaur. Wisdom Leaf Press, 65–71. https://doi.org/10.55938/wlp.v1i5.183
Siregar, K. E. (2024). Increasing Digital Literacy In Education : Analysis Of Challenges And Opportunities Through Literature Study. International Journal of Multilingual Education and Applied Linguistics, 1(2), 10–25. Retrieved from https://international.aspirasi.or.id/index.php/IJMEAL/article/view/18
Sun, A. X., & Mizumoto, A. (2025). Exploring the barriers to data-driven learning in the classroom: a systematic qualitative synthesis. Applied Corpus Linguistics, 5(2), 100126. https://doi.org/10.1016/j.acorp.2025.100126
Tian, D., Jia, X., Ma, R., Liu, S., Liu, W., & Hu, C. (2021). BinDeep: A deep learning approach to binary code similarity detection. Expert Systems with Applications, 168, 114348. https://doi.org/10.1016/j.eswa.2020.114348
Uddin, S., Ong, S., & Lu, H. (2022). Machine learning in project analytics: a data-driven framework and case study. Scientific Reports, 12(1), 1–13. https://doi.org/10.1038/s41598-022-19728-x