Implementasi Data Mining untuk Menentukan Pola Pembelian Obat Menggunakan Metode Apriori
DOI:
https://doi.org/10.47065/bulletincsr.v6i4.1133Keywords:
Data Mining; Apriori; Association Rule; Purchasing Pattern; PharmacyAbstract
The development of information technology has increased the amount of drug sales transaction data in the pharmacy sector. However, transaction data are generally used only as administrative archives and have not been optimally utilized to produce strategic information. This study aims to implement data mining using the Apriori method to determine drug purchasing patterns based on pharmaceutical transaction data. This research employed a quantitative approach using the Pharmacy Transactional Dataset obtained from the Kaggle platform. The research stages were conducted using the Cross Industry Standard Process for Data Mining (CRISP-DM), including business understanding, data understanding, data preparation, modeling, evaluation, and deployment. The analysis process was carried out using the Python programming language with the assistance of the pandas and mlxtend libraries. The results showed that the purchasing relationship between Paracetamol and Vitamin C had the highest association value with a support value of 32% and a confidence value of 78%. These results indicate that the Apriori algorithm is capable of identifying relationships among drug products based on pharmaceutical transaction data. The resulting information can be utilized to support promotional strategies, drug inventory management, and business decision-making in the pharmaceutical sector.
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References
K. R. Alla and G. Thangarasu, “Supply Chain Management of Drug Products in Blockchain Using Reinforcement Learning,” International Journal of Technology, vol. 14, no. 6, p. 1256, Oct. 2023, doi: 10.14716/ijtech.v14i6.6626.
A. Budi Trisnawan, “Pemanfaatan Big Data dalam Sistem Informasi untuk Pengambilan Keputusan Strategis,” Journal of Information System and Education Development, vol. 3, no. 3, pp. 39–43, Sep. 2025, doi: 10.62386/jised.v3i3.163.
A. A. Fahmi, H. Tsaniya Ilyas, M. Faila Sufa, and D. Safitri Ramadhani, “Strategi Peningkatan Layanan Apotek Berdasarkan Servqual dan Importance Performance Analysis,” Journal of Manufacturing in Industrial Engineering & Technology, vol. 4, no. 1, pp. 30–41, Jun. 2025, doi: 10.30651/mine-tech.v4i1.26546.
S. Angriawan, “Pengaruh Pengelolaan Obat dan Harga Obat terhadap Keputusan Pembelian melalui Kualitas Pelayanan pada Apotek Restu Bunda,” Assets Journal: Management, Administration, Economics, and Accounting, vol. 2, no. 2, pp. 37–44, Dec. 2024, doi: 10.59923/assets.v2i2.248.
R. Ricardo, Y. Reswan, D. Abdullah, and M. Muntahanah, “Analysis of Consumer Purchase Patterns Using Apriori Algorithm at Ryo Jaya Buah Store,” Jurnal Komputer, Informasi dan Teknologi, vol. 4, no. 1, p. 7, Jul. 2024, doi: 10.53697/jkomitek.v4i1.1762.
Moh. L. Prayugo, D. A. Wibowo, Moch. S. Hidajat, E. Mintorini, and R. R. Ali, “Data Mining Application Analyzing Customer Purchase Patterns Using The Apriori Algorithm,” Journal of Applied Intelligent System, vol. 9, no. 1, pp. 122–135, Apr. 2025, doi: 10.62411/jais.v9i1.10308.
E. Rahma Hidayani and Melri Deswina, “Penerapan Algoritma Apriori dalam Pengembangan Sistem Rekomendasi Produk untuk Meningkatkan Penjualan Impulsif melalui Analisis Pola Pembelian,” Merkurius?: Jurnal Riset Sistem Informasi dan Teknik Informatika, vol. 3, no. 4, pp. 336–349, Jul. 2025, doi: 10.61132/merkurius.v3i4.1006.
A. A. Firdaus, N. Iksan, D. N. Sadiah, L. Sagita, and D. Setiawan, “Penerapan Algoritma Apriori untuk Prediksi Kebutuhan Suku Cadang Mobil,” Jurnal Sistem dan Teknologi Informasi (Justin), vol. 9, no. 1, p. 13, Jan. 2021, doi: 10.26418/justin.v9i1.41151.
Fransiska Diana Hermanto and A. Bellanov, “Penerapan Algoritma Apriori Dalam Analisis Pola Pembelian Pelanggan Pada Usaha Kafe,” Industrial & System Engineering Journals (ISEJOU), vol. 4, no. 1, pp. 373–385, Dec. 2025, doi: 10.37477/isejou.v4i1.888.
S. Raka Pramuja Ananda, L. Prayoga Yudhi Putra, A. Ramadhan Oktaviano, T. Sulanjari, A. Nur Farida, and A. Arum Sari, “Analisis Pola Pembelian Pelanggan Menggunakan Algoritma Apriori Pada Transaksi Belanja Supermarket,” Prosiding Seminar Nasional Teknologi Informasi dan Bisnis, pp. 407–413, Jul. 2025, doi: 10.47701/p8h17364.
Y. Yulindawati, A. Yusnita, R. Mayasari, and M. E. Melano, “Analisis Pola Penjualan Obat di Apotek Menggunakan Algoritma Apriori Untuk Optimalisasi Stok dan Penjualan,” TIN: Terapan Informatika Nusantara, vol. 5, no. 2, pp. 100–107, Jul. 2024, doi: 10.47065/tin.v5i2.5407.
E. Fadilah, Ahmad Faqih, and Sandy Eka Permana, “Using the Apriori Algorithm to Identify Purchase Patterns for Enhancing Sales in Personal Shopper Services,” Journal of Artificial Intelligence and Engineering Applications (JAIEA), vol. 4, no. 2, pp. 745–751, Feb. 2025, doi: 10.59934/jaiea.v4i2.741.
K. Kharomiyah, N. Rahaningsih, and R. D. Dana, “Analisis Keterkaitan Penjualan Obat melalui Penerapan Algoritma FP-Growth guna Optimalisasi Strategi Pemasaran,” Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer), vol. 23, no. 1, p. 57, Feb. 2024, doi: 10.53513/jis.v23i1.9495.
N. A. Foci and A. S. Indrapriyatna, “Optimising Inventory Control in Pharmaceutical Distribution: A Case Study on PT. XYZ,” Performa: Media Ilmiah Teknik Industri, vol. 24, no. 2, pp. 147–155, Sep. 2025, doi: 10.20961/performa.v24i2.2737.
M. Melviani, O. Priadi, and S. Muttaharah, “Analisis Strategi Manajemen Pemasaran Apotex ‘X’ Di Banjarmasin,” Health Research Journal of Indonesia, vol. 2, no. 2, pp. 150–154, Dec. 2023, doi: 10.63004/hrji.v2i2.309.
S. Butsianto, Candra Naya, and Anggi Muhammad Rifa’i, “Implementasi Algoritma Apriori dalam Menemukan Pola Asosiasi pada Data Penjualan Produk Retail,” Bulletin of Computer Science Research, vol. 5, no. 5, pp. 938–947, Aug. 2025, doi: 10.47065/bulletincsr.v5i5.731.
A. Rondy, J. Kusanti, and A. Rianto, “Implementasi Data Mining dalam Menganalisis Pola Pembelian Produk Toko Oleh-Oleh Umrah dan Haji,” Jurnal Syntax Admiration, vol. 5, no. 12, pp. 5536–5549, Dec. 2024, doi: 10.46799/jsa.v5i12.1894.
F. S. Saad, N. Azizah, and Z. Yani, “Penerapan Algoritma Apriori untuk Menentukan Pola Permintaan Bahan Makanan Berdasarkan Data Transaksi,” Jurnal Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence), vol. 5, no. 2, pp. 388–397, Aug. 2023, doi: 10.55382/jurnalpustakaai.v5i2.1181.
Nur Aini and Zaehol Fatah, “Implementasi Algoritma Apriori untuk Analisis Pola Pembelian Konsumen pada Dataset Market Basket Analysis,” Jurnal Mahasiswa Teknik Informatika, vol. 4, no. 2, pp. 168–176, Oct. 2025, doi: 10.35473/jamastika.v4i2.4521.
M. Syahrir, R. Rismayanti, and M. A. Wicaksono, “Penentuan Pola Pembelian Obat Menggunakan Algoritma Apriori,” Jurnal SAINTEKOM, vol. 11, no. 2, p. 142, Sep. 2021, doi: 10.33020/saintekom.v11i2.249.
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