Implementasi Algoritma Apriori untuk Mengidentifikasi Pola Asosiasi Peresepan Obat dan Penyakit di Klinik Pratama Az-Zainiyah

The Az-Zainiyah Primary Clinic under the auspices of the Nurul Jadid Islamic Boarding School provides health services to students and the surrounding community. Daily drug prescribing activities generate historical data that has not been optimally utilized. This study aims to identify patterns of association between drug prescribing and common diseases by applying the Apriori algorithm as a data mining method. The data used came from 3,661 student prescription transactions during February 2023. The results of the analysis revealed a combination of drugs that were often prescribed together, including Scopma Plus and Coro-sorb, with a support value of 0.062, confidence of 0.625, and lift of 4.068. This combination was strongly correlated with complaints of diarrhea and abdominal pain, which were also common findings during field observations. These findings have practical implications in the formulation of drug stock policies, increasing service efficiency, and data-based clinical decision making in the clinic environment.

Authors

Publication Details

Journal
TRILOGI Jurnal Ilmu Teknologi Kesehatan dan Humaniora
Published
2025-06-22
DOI
https://doi.org/10.33650/trilogi.v6i2.11573
Primary Topic
Management and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Implementasi Algoritma Apriori untuk Mengidentifikasi Pola Asosiasi Peresepan Obat dan Penyakit di Klinik Pratama Az-Zainiyah

C. Novia, Nurul Imaniyah, Sudriyanto Sudriyanto
TRILOGI Jurnal Ilmu Teknologi Kesehatan dan Humaniora
Management and Optimization Techniques
article

Implementasi Algoritma Apriori untuk Mengidentifikasi Pola Asosiasi Peresepan Obat dan Penyakit di Klinik Pratama Az-Zainiyah

C. Novia, Nurul Imaniyah, Sudriyanto Sudriyanto
article en

Abstract

The Az-Zainiyah Primary Clinic under the auspices of the Nurul Jadid Islamic Boarding School provides health services to students and the surrounding community. Daily drug prescribing activities generate historical data that has not been optimally utilized. This study aims to identify patterns of association between drug prescribing and common diseases by applying the Apriori algorithm as a data mining method. The data used came from 3,661 student prescription transactions during February 2023. The results of the analysis revealed a combination of drugs that were often prescribed together, including Scopma Plus and Coro-sorb, with a support value of 0.062, confidence of 0.625, and lift of 4.068. This combination was strongly correlated with complaints of diarrhea and abdominal pain, which were also common findings during field observations. These findings have practical implications in the formulation of drug stock policies, increasing service efficiency, and data-based clinical decision making in the clinic environment.

TRILOGI Jurnal Ilmu Teknologi Kesehatan dan HumanioraVol. 6(2)
Openalex Percentile: Top 64%
Management and Optimization Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Implementasi Algoritma Apriori untuk Mengidentifikasi Pola Asosiasi Peresepan Obat dan Penyakit di Klinik Pratama Az-Zainiyah — C. Novia, Nurul Imaniyah, et al. · TRILOGI Jurnal Ilmu Teknologi Kesehatan dan Humaniora (2025) | TGRS Research Map | TGRS