IMPLEMENTASI ALGORITMA APRIORI UNTUK ANALISIS PERSEDIAAN MATERIAL DI WAREHOUSE PT. TELKOM AKSES MAKASSAR
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Abstract
This research aims to implement Apriori algorithm for data mining in material inventory management at PT. Telkom Akses Makassar. Apriori algorithm identifies frequent itemsets and generates association rules from transaction data to optimize warehouse stock management. The methodology includes data collection through observation, interviews, and historical transaction datasets. Data processing uses Apriori to calculate support, confidence, and lift metrics. The results indicate that frequent item combinations can improve planning accuracy and reduce stockouts. A web-based application, Material Analyzer, was developed for analysis and visualization, featuring dashboard, analysis, history, and visualization modules. This study contributes practically by supporting logistics decision-making and theoretically by expanding data mining applications in inventory systems.
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How to Cite
Dzul Jalali Wal Ikram, Ahmad Rifai Sadrin, Dikwan Moeis, & Rosnani. (2025). IMPLEMENTASI ALGORITMA APRIORI UNTUK ANALISIS PERSEDIAAN MATERIAL DI WAREHOUSE PT. TELKOM AKSES MAKASSAR. Jurnal Informatika Progres, 17(1), 52-62. Retrieved from https://jurnal.stmikprofesional.ac.id/index.php/Progress/article/view/426
References
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[9] Ulvah. (2018). Implementasi algoritma Apriori aturan keterkaitan data untuk analisa keranjang belanja sistem persediaan obat pada Apotek Perdos Farma Makassar. Jurnal Instek (Informatika Sains dan Teknologi).
[10] Wahono, S., & Ali, H. (2021). Peranan data warehouse, software, dan brainware terhadap pengambilan keputusan (literature review executive support system for business). Jurnal Ekonomi, Manajemen dan Sistem Informasi, 3(2), 225–239. https://doi.org/10.31933/jemsi.v3i2.781
[11] Sianturi, F. A. (2018). Penerapan algoritma Apriori untuk penentuan tingkat pesanan. Jurnal Mantik Penusa, 2(1), 50–57. Retrieved from http://bowmasbow.blogspot.com/
[12] Dongga, J., Sarungallo, A., Koru, N., & Lante, G. (2023). Implementasi data mining menggunakan algoritma Apriori dalam menentukan persediaan barang (studi kasus: Toko Swapen Jaya Manokwari). G-Tech: Jurnal Teknologi Terapan, 7(1), 119–126. https://doi.org/10.33379/gtech.v7i1.1938
[13] Wahyuni, S. (2018). Implementasi data mining dalam memprediksi stok barang menggunakan algoritma Apriori. Jurnal Teknik dan Informatika.
[14] Oladele, T. O., Ogundokun, R. O., Adegun, A. A., Adeniyi, E. A., & Ajanaku, A. T. (2021). Development of an inventory management system using association rule. Indonesian Journal of Electrical Engineering and Computer Science, 21(3), 1868–1876. https://doi.org/10.11591/ijeecs.v21.i3.pp1868-1876
[15] Firmansyah, A., & Merlina, N. (2020). Prediksi pola penjualan tiket kapal PT. Pelni cabang Makassar menggunakan metode algoritma Apriori. JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer), 5(2), 183–190. https://doi.org/10.33480/jitk.v5i2.1123
[2] Avizenna, M. H. (2022). Applying the Apriori algorithm to analyze and optimize medical device inventory management. Journal of Applied Data Science, 3(4), 143–151. https://doi.org/10.47738/jads.v3i4.33
[3] Jessfry, V., & Siddik, M. (2024). Penerapan data mining menggunakan algoritma Apriori dalam membangun sistem persediaan barang. Journal of Information System & Informatics Engineering, 8(1), 187–199.
[4] Syahara, Z., Adiha, R. N., & Windarto, A. P. (2021). Implementasi data mining algoritma Apriori pada sistem persediaan bahan bangunan di Karang Sari. Brahmana: Jurnal Penerapan Kecerdasan Buatan, 2(2), 107–115. https://doi.org/10.30645/brahmana.v2i2.72
[5] Uddin Adnan, M. I., Raz, R., Ahmed, T., & Islam, A. H. M. S. (2020). Application and analysis of retail inventory using data mining techniques. Global Journal of Computer Science and Technology, 20(2), 27–33. https://doi.org/10.34257/gjcstgvol20is2pg27
[6] Riadi, I., Herman, H., Fitriah, F., Suprihatin, S., Muis, A., & Yunus, M. (2023). Implementation of association rule using Apriori algorithm and frequent pattern growth for inventory control. Jurnal Infotel, 15(4), 369–378. https://doi.org/10.20895/infotel.v15i4.980
[7] Fakultas Teknik, Universitas Muhammadiyah Magelang. (2021). Prediksi kebutuhan material pembangunan jaringan Telkom menggunakan algoritma Apriori. [Prosiding/Artikel].
[8] Kurnawan, I., Marisa, F., & Purnomo, P. (2018). Implementasi data mining dengan algoritma Apriori untuk memprediksi tingkat kelulusan mahasiswa. Jurnal Teknologi dan Manajemen Informatika, 4(1). https://doi.org/10.26905/jtmi.v4i1.1894
[9] Ulvah. (2018). Implementasi algoritma Apriori aturan keterkaitan data untuk analisa keranjang belanja sistem persediaan obat pada Apotek Perdos Farma Makassar. Jurnal Instek (Informatika Sains dan Teknologi).
[10] Wahono, S., & Ali, H. (2021). Peranan data warehouse, software, dan brainware terhadap pengambilan keputusan (literature review executive support system for business). Jurnal Ekonomi, Manajemen dan Sistem Informasi, 3(2), 225–239. https://doi.org/10.31933/jemsi.v3i2.781
[11] Sianturi, F. A. (2018). Penerapan algoritma Apriori untuk penentuan tingkat pesanan. Jurnal Mantik Penusa, 2(1), 50–57. Retrieved from http://bowmasbow.blogspot.com/
[12] Dongga, J., Sarungallo, A., Koru, N., & Lante, G. (2023). Implementasi data mining menggunakan algoritma Apriori dalam menentukan persediaan barang (studi kasus: Toko Swapen Jaya Manokwari). G-Tech: Jurnal Teknologi Terapan, 7(1), 119–126. https://doi.org/10.33379/gtech.v7i1.1938
[13] Wahyuni, S. (2018). Implementasi data mining dalam memprediksi stok barang menggunakan algoritma Apriori. Jurnal Teknik dan Informatika.
[14] Oladele, T. O., Ogundokun, R. O., Adegun, A. A., Adeniyi, E. A., & Ajanaku, A. T. (2021). Development of an inventory management system using association rule. Indonesian Journal of Electrical Engineering and Computer Science, 21(3), 1868–1876. https://doi.org/10.11591/ijeecs.v21.i3.pp1868-1876
[15] Firmansyah, A., & Merlina, N. (2020). Prediksi pola penjualan tiket kapal PT. Pelni cabang Makassar menggunakan metode algoritma Apriori. JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer), 5(2), 183–190. https://doi.org/10.33480/jitk.v5i2.1123