Data Mining Menggunakan Metode Asosiasi Apriori untuk Merekomendasi Pola Obat Pada Puskesmas
-
Dewinta Marthadinata Sinaga
*
STIKOM Tunas Bangsa, Pematangsiantar,
Indonesia
- Agus Perdana Windarto STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
- Heru Satria Tambunan STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
- Irfan Sudahri Damanik STIKOM Tunas Bangsa, Pematangsiantar, Indonesia (*) Corresponding Author
Abstract
Drugs are one of the most important components in terms of health, both to cure and reduce pain due to illness suffered by everyone, besides that the use of drugs also gives us information about what diseases everyone suffers so that the information is very helpful for health workers. For this reason, drugs need to be managed properly, effectively and efficiently. This study aims to analyze the a priori algorithm on drug output data at the Parsoburan Health Center Pematangsiantar to find out what types of drugs are most needed by patients at the same time. The data used is in the form of drug output data in April 2021. Based on the a priori algorithm calculations, 70 association rules were formed with a number minimum of support 90% and a minimum confidence of 90%. It is hoped that the results of the research can help the Parsoburan Health Center Pematangsiantar optimize quality health services for planning future drug needs and produce useful information for decision making.
Downloads
References
Suhartini, L. kerta Wijaya, and N. A. Pratiwi, “Penerapan Algoritma K-Means Untuk Pendataan Obat Berdasarkan Laporan Bulanan Pada Dinas Kesehatan Kabupaten Lombok Timur,” Infotek J. Inform. dan Teknol., vol. 3, no. 2, pp. 147–156, 2020.
Taslim and Fajrizal, “Penerapan algorithma k-mean untuk clustering data obat pada puskesmas rumbai,” J. Teknol. Inf. dan Komun., vol. 7, no. 2, pp. 108–114, 2016, doi: 10.31849/digitalzone.v7i2.602.
C. D. Pratiwi, A. A. Rumayar, and C. K. F. Mandagi, “Hubungan Kualitas Jasa Pelayanan Kesehatan Dengan Kepuasan Pasien Di Puskesmas Mopuya Kecamatan Dumoga Utara Kabupaten Bolaang Mongondow,” KESMAS, vol. 7, no. 5, 2018.
K. Fatmawati and A. P. Windarto, “Data Mining: Penerapan Rapidminer Dengan K-Means Cluster Pada Daerah Terjangkit Demam Berdarah Dengue (Dbd) Berdasarkan Provinsi,” CESS (Journal Comput. Eng. Syst. Sci., vol. 3, no. 2, pp. 173–178, 2018, doi: 10.24114/cess.v3i2.9661.
L. Henando, “Algoritma Apriori Dan Fp-Growth Untuk Analisa Perbandingan Data Penjualan Leptop Berdasarkan Merk Yang Diminati Konsumen (Studi Kasus : Indocomputer Payakumbuh),” J-Click (Jurnal Sist. Inf. Dan Manaj. Inform., vol. 6, no. 1, pp. 1–17, 2019.
R. Rismanto, L. Darmawan, and A. Prasetyo, “Penerapan Algoritma Apriori Dalam Menentukan Pola Pembelian Konsumen Di Kafe Hidden Toast And Float,” Teknol. Inform. dan Terap., vol. 04, no. 02, pp. 97–102, 2017.
Gustientiedina, M. H. Adiya, and Y. Desnelita, “Penerapan Algoritma K-Means Untuk Clustering Data Obat-Obatan Pada RSUD Pekanbaru,” J. Nas. Teknol. dan Sist. Inf., vol. 5, no. 1, pp. 17–24, 2019, doi: 10.25077/teknosi.v5i1.2019.17-24.
H. D. Wijaya and S. Dwiasnati, “Implementasi Data Mining dengan Algoritma Naïve Bayes pada Penjualan Obat,” J. Inform., vol. 7, no. 1, pp. 1–7, 2020, doi: 10.31311/ji.v7i1.6203.
Y. A. M, W. Choiriah, and Akmal, “Penerapan Data Mining Menggunakan Metode Assiciation Rule Dengan Algoritma Apriori Untuk Analisa Pola Penjualan Barang,” JURTEKSI (Jurnal Teknol. dan Sist. Informasi), vol. 5, no. 2, pp. 193–198, 2019, doi: 10.33330/jurteksi.v5i2.362.
E. Budiyati, Hurniningsih, and M. D. Lusita, “Implementasi Metode Algoritma Apriori Untuk Penempatan Buku Pada Rak Perpustakaan Stmik Jakarta Sti&K,” J. Inf. Syst. Informatics Comput., vol. 4, no. 1, pp. 30–39, 2020.
A. Rahmadsyah, Hartono, and R. Rosnelly, “Analisa Association Rule Pada Algoritma Apriori Untuk Minat Pembelian Alat Kesehatan,” J. Media Inform. Budidarma, vol. 5, no. 1, pp. 280–286, 2021, doi: 10.30865/mib.v5i1.2658.
F. A. K. Wardani and T. Kristiana, “Implementasi Data Mining Penjualan Produk Kosmetik Pada PT. Natural Nusantara Menggunakan Algoritma Apriori,” Paradig. - J. Komput. dan Inform., vol. 22, no. 1, pp. 85–90, 2020, doi: 10.31294/p.v21i2.
N. Rahmawati, Y. Novianto, and Jasmir, “Klasifikasi Kondisi Gizi Balita Menggunakan Metode Naive Bayes ( Studi Kasus Posyandu Melati IV),” J. Ilm. Mhs. Tek. Inform., vol. 2, no. 3, pp. 257–268, 2020.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Data Mining Menggunakan Metode Asosiasi Apriori untuk Merekomendasi Pola Obat Pada Puskesmas
Pages: 143-149
Copyright (c) 2022 Dewinta Marthadinata Sinaga, Agus Perdana Windarto, Heru Satria Tambunan, Irfan Sudahri Damanik
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are 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 an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their 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 published work (Refer to The Effect of Open Access).
