PENERAPAN ALGORITMA APRIORI UNTUK MENGIDENTIFIKASI LOKASI STRATEGIS PROMOSI SEKOLAH SWASTA

Authors

DOI:

https://doi.org/10.31949/j-ensitec.v11i02.13377

Abstract

Schools must carry out effective promotions and target the right markets to attract prospective students efficiently. This study applies data mining using Association Rule and Apriori algorithms to uncover patterns for identifying promising promotional areas. It consists of four stages: data collection, preprocessing, implementation and testing, and evaluation, aiming to determine strategic locations for school promotion. The Apriori algorithm analyzed student data and produced 16 association rules, all with 100% confidence. Findings show that Kaliwates District appeared eight times, Sumbersari four times, and Tempurejo and Patrang twice each, indicating most students come from Kaliwates. The ‘Public Elementary School’ itemset appeared 12 times, revealing that most students enrolled from public rather than private schools. The study concludes that educational data plays a crucial role in shaping promotion strategies, especially through association analysis. Rules with the ‘District’ itemset in the antecedent are particularly useful as a promotional reference. These insights help decision-makers identify high-potential regions and school origins, supporting more targeted and effective promotional efforts.

Keywords:

apriori algorithm, association rule mining, data mining, private school, promotion strategy

Downloads

Download data is not yet available.

References

[1] Agal, S., Sharma, P., Mohan, C. R., Madan, P., V, M., & Arri, H. S. (2023). Using Machine Learning Algorithms to Suggest a Method for Predictive Analysis in Data Mining. 2023 IEEE International Conference on ICT in Business Industry & Government (ICTBIG) (pp. 1-5). IEEE.

[2] Greaves, E., Wilson, D., & Nairn, A. (2023). Marketing and School Choice: A Systematic Literature Review. Review of Educational Research, 825-861.

[3] Hikmawati, E., Maulidevi, N. U., & Surendro, K. (2022). Rule-Ranking Method Based on Item Utility in Adaptive Rule Model. PeerJ Computer Science 8.

[4] Hodijah, A., & Setijohatmo, U. T. (2021). Analysis Of Frequent Itemset Generation Based On Trie Data Structure In Apriori Algorithm. TELKOMNIKA, 19(5), 1553-1564.

[5] Laili, U. H. (2022). Implementasi Data Mining Naïve Bayes Dan Svm (Support Vector Machine) Dalam Pengumpulan Berita Kriminal Di Indonesia Pada Masa Pandemi COVID-19 Studi Kasus : Situs Berita Detik.com. J-ENSISTEC (Journal of Engineering and Sustainable Technology) Vol. 09 No. 01.

[6] Lim, W. M., Jee, T. W., & De Run, E. C. (2018). Strategic brand management for higher education institutions with graduate degree programs: empirical insights from the higher education marketing mix. Journal of Strategic Marketing, 28(3), 225–245.

[7] Maruseac, M., & Ghinita, G. (2020). Precision-Enhanced Differentially-Private Mining of High-Confidence Association Rules. IEEE Transactions on Dependable and Secure Computing Volume: 17, Issue: 6.

[8] Norjanah, S., Windiarti, I. S., & Qamaruzzaman, M. H. (2022). Sistem Informasi Pendaftaran Siswa Baru di SD Islam Hasanka Palangkaraya Berbasis Web. J-ENSISTEC (Journal of Engineering and Sustainable Technology) Vol. 09 No. 01.

[9] Supriyati, E., Iqbal, M., & Khotimah, T. (2019). Using Similarity Degrees To Improve Fuzzy Mining Association Rule Based Model For Analyzing IT Entrepreneurial Tendency. IIUM Engineering Journal, 20(2), 78–89.

[10] Veer, A., Gurav, M., Dange, S., Chandgude, S., & Wangikar, V. (2022). Apriori Algorithm with Dynamic Parameter Selection and Pruning of Misleading Rules. Lecture Notes in Networks and Systems, vol 286, 619–627.

[11] Zakur, Y. A., Mirashrafi, S. B., & Flaih, L. R. (2023). A Comparative Study on Association Rule Mining Algorithms on the Hospital Infection Control Dataset. Baghdad Science Journal 20(5).

Downloads

Abstract Views : 7
Downloads Count: 3

Published

2025-06-20

How to Cite

Sulistyo, H. W., Hardian Oktavianto, & Irawan, D. (2025). PENERAPAN ALGORITMA APRIORI UNTUK MENGIDENTIFIKASI LOKASI STRATEGIS PROMOSI SEKOLAH SWASTA. J-ENSITEC, 11(02), 102016–102022. https://doi.org/10.31949/j-ensitec.v11i02.13377

Issue

Vol. 11 No. 02 (2025): June 2025

Section

Articles

License

Copyright (c) 2025 Henny Wahyu Sulistyo, Hardian Oktavianto, Dudi Irawan

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

An author who publishes in the J-ENSITEC (Journal of Engineering and Sustainable Technology)  agrees to the following terms:

  1. Author retains the copyright and grants the journal the right of first publication of the work simultaneously licensed under the Creative Commons Attribution-ShareAlike 4.0 License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal
  2. The author is able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book) with the acknowledgment of its initial publication in this journal.
  3. The author is  permitted and encouraged to post his/her  work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of the published work

Most read articles by the same author(s)