Implementasi Algoritma Apriori Menggunakan Cross-Industry Standar Process for Data-Mining Untuk Menentukan Pola Pembelian Obat


  • Maya Istifarsari Universitas Binaniaga Indonesia, Bogor, Indonesia
  • Leny Tritanto Ningrum * Mail Universitas Binaniaga Indonesia, Bogor, Indonesia
  • Lis Utari Universitas Binaniaga Indonesia, Bogor, Indonesia
  • (*) Corresponding Author
Keywords: Apriori; Lift Ratio; Medicine; Pharmacy; Purchasing

Abstract

In the health sector, the availability of adequate medicines in pharmacies is very important in ensuring patients receive optimal care. The availability of drugs that is not well maintained can hamper the treatment process and have a negative impact on health services as a whole. The problem discussed in this research is the accumulation of drug stock caused by drug purchases that are not balanced with sales, causing losses to the pharmacy. Based on these problems, it can be stated that currently the pharmacy is not appropriate and effective in determining drug purchasing patterns. For this reason, it is necessary to determine drug purchasing patterns at pharmacies using the Apriori algorithm. This research aims to determine drug itemsets based on association rules so that these itemsets can be prioritized for stock in each purchase. This can also be displayed by an application prototype so that it is easier to get a combination of itemsets in determining drug purchases to help anticipate drug supply needs to be more efficient. . The final result of this research is a combination of itemsets in the form of drug items that meet the requirements for a minimum support value of 25% and a minimum confidence value of 60%, namely Methylprednisolone 4mg Novel and Paracetamol Mef with a support value of 41.57% and a confidence value of 62.50%. FG Troches and Paracetamol Mef with a support value of 25% and a confidence value of 100%, as well as Metformin 500MG Hj and Sanmol Tab with a support value of 25% and a confidence value of 60%. The final result of the association rules was an evaluation test to measure the strength of the relationship between items using the lift ratio and produced a value above 1%, namely an average test value of 2.4%, so it can be stated that the a priori results are said to be valid or strong.

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References

A. Ishaq, L. A. Utami, and S. Mariana, “Analisa Pola Penjualan Obat Menggunakan Algoritma Apriori Pada Apotek Zam-Zam Bogor,” vol. 08, no. 1, pp. 13–23, 2019.

S. Lestari and S. Saepudin, “Analisis Sentimen Vaksin Sinovac Pada Twitter Menggunakan Algoritma Naive Bayes,” SISMATIK (Seminar Nas. Sist. Inf. dan Manaj. Inform., pp. 163–170, 2021.

R. Dahlia, L. A. Fitriana, and S. Seimahuira, “Analisis Pola Pembelian Obat Demam Dengan Teknik Data Mining Menggunakan Algoritma Apriori ( Studi Kasus : Apotek Ambawang Farma ),” vol. 15, no. 1, pp. 172–184, 2024.

A. M. Sormin, “ALGORITMA APRIORI ( STUDI KASUS : PUSKESMAS UMBAN SARI ),” vol. 2, no. 1, pp. 149–163, 2023.

W. Delrinata and F. B. Siahaan, “Implementasi Algoritma Apriori Untuk Menentukan Stok Obat,” vol. 09, pp. 222–228, 2020.

U. Ependi and A. Putra, “Solusi Prediksi Persediaan Barang dengan Menggunakan Algoritma Apriori ( Studi Kasus : Regional Part Depo Auto 2000 Palembang ),” vol. 5, no. 2, pp. 139–145, 2019.

P. Haryandi et al., “Penerapan Algoritma Apriori untuk Mencari Pola Penjualan Produk Herbal ( Studi Kasus : Toko Hanawan Gemilang ),” vol. 4221, pp. 218–225, 2021.

L. I. Prahartiwi and W. Dari, “Algoritma Apriori untuk Pencarian Frequent itemset dalam Association Rule Mining,” vol. 7, no. September, pp. 143–152, 2019.

D. Pratiwi and J. S. Wibowo, “Implementasi Algoritme Apriori Pada Sistem Persediaan Obat Apotik Puskesmas,” Jutisi J. Ilm. Tek. Inform. dan Sist. Inf., vol. 12, pp. 214–219, 2023.

S. Awaliyah, R. Sutomo, and F. Handayanna, “Analisis Pola Pembelian Obat di Apotek Sekar Adi Menggunakan Metode Algoritma Apriori Depok,” vol. 4, pp. 112–127, 2020.

M. S. Sandy, H. Setiawan, U. Indahyanti, F. Sains, and D. Teknologi, “Analisis Data Mining Produk Retail Menggunakan Metode Asosiasi Dengan Menerapkan Algoritma Apriori,” vol. 4, no. 2, pp. 384–391, 2023.

K. P. Sinaga and M. S. Yang, “Unsupervised K-means clustering algorithm,” IEEE Access, vol. 8, pp. 80716–80727, 2020, doi: 10.1109/ACCESS.2020.2988796.

R. Chapman, P., Clinton, J., Kerber., CRISP-DM 1.0 Step-by-step data mining guide, vol. 1. USA: SPSS, 2000.

L. T. Ningrum, I. Irmayansyah, and L. Utari, “Penerapan Metode K-Means dan Euclidean Distance Untuk Seleksi Metode Judul Tugas Akhir,” Acad. J. Comput. Sci. Res., vol. 6, no. 1, p. 13, 2024, doi: 10.38101/ajcsr.v6i1.10766.

D. Anggraini, U. P. Sanjaya, and I. A. Sa’ida, “Analisis Penerapan Metode Association Rule Mining Untuk Transaksi Penjualan di Toko Bangunan Dengan Algoritma Apriori,” SINTECH (Science Inf. Technol. J., vol. 5, no. 2, pp. 124–138, 2022, doi: 10.31598/sintechjournal.v5i2.1193.

I. Qoniah and A. T. Priandika, “Analisis Market Basket Untuk Menentukan Asossiasi Rule Dengan Algoritma Apriori (Studi Kasus: Tb.Menara),” J. Teknol. dan Sist. Inf., vol. 1, no. 2, pp. 26–33, 2020, doi: 10.33365/jtsi.v1i2.368.

U. Baetulloh, A. I. Gufroni, and R. -, “Penerapan Metode Association Rule Mining Pada Data Transaksi Penjualan Produk Kartu Perdana Kuota Internet Menggunakan Algoritma Apriori,” Simetris J. Tek. Mesin, Elektro dan Ilmu Komput., vol. 10, no. 1, pp. 173–188, 2019, doi: 10.24176/simet.v10i1.2890.

D. Sitanggang, Algoritma Apriori, 1st ed. Medan: Unpri Press Universitas Prima Indonesia, 2023.

S. Ningsih, “Algoritma Apriori Pada Sistem Persediaan Dan Penjualan Tanaman Anggrek Secara Online,” J. Sist. Inf. Bisnis, vol. 3, no. 2, pp. 63–70, 2022.

C. I. Wiryawan, Y. R. W. Utami, and D. Nugroho, “Algoritma Apriori Untuk Penentuan Assosiasi Penjualan Barang,” J. Teknol. Inf. dan Komun., vol. 9, no. 1, p. 7, 2021, doi: 10.30646/tikomsin.v9i1.538.

M. Syahrir, R. Rismayanti, and M. A. Wicaksono, “Penentuan Pola Pembelian Obat Menggunakan Algoritma Apriori,” J. SAINTEKOM, vol. 11, no. 2, p. 142, 2021, doi: 10.33020/saintekom.v11i2.249.

V. C. Nisa and F. N. Khasanah, “Algoritma Apriori Dalam Identifikasi Pola Pembelian Konsumen Pada Produk Minuman,” vol. 8, no. 2, pp. 156–164, 2023.

Melinska Ayu Febrianti, “ANALISIS POLA PEMBELIAN PELANGGAN BERDASARKAN TRANSAKSI PENJUALAN PADA RITEL DENGAN METODE MULTILEVEL ASSOCIATION RULES,” UNIVERSITAS ISLAM YOGYAKARTA, 2022.


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Article History
Submitted: 2024-06-03
Published: 2024-07-24
Abstract View: 507 times
PDF Download: 375 times
How to Cite
Istifarsari, M., Ningrum, L., & Utari, L. (2024). Implementasi Algoritma Apriori Menggunakan Cross-Industry Standar Process for Data-Mining Untuk Menentukan Pola Pembelian Obat. Journal of Information System Research (JOSH), 5(4), 1063-1075. https://doi.org/10.47065/josh.v5i4.5263
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