ANALISIS POLA PENYAKIT DENGAN METODE ASSOCIATION RULE (STUDI KASUS : RSUD LABUANG BAJI)

RSUD Labuang Baji has a lot of medical record data, but this medical record data has not been used optimally and has not been processed to produce useful information for Laburan Baji Hospital. In this study the data used were outpatient medical record data in 2019, by analyzing three attributes, namely disease diagnosis (ICD), gender, and age group. The method for conducting data analysis is the association rule method using the Apriori algorithm and Tools R. The results of this study are disease patterns using a minimum support value of 0.01 and a minimum confidence value of 0.6, and the disease pattern formed is an associative rule with a combination of 2k-itemset and 3k item set of 25 associative rules where the rules for this disease pattern have a lift ratio value of > 1, so this disease pattern can be used as a recommendation to improve hospital services.

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Publication Details

Journal
Journal of Informatics and Computer Engineering Research
Published
2024-12-29
DOI
https://doi.org/10.31963/jicer.v1i2.5177
Primary Topic
Management and Optimization Techniques
Type
article
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article

ANALISIS POLA PENYAKIT DENGAN METODE ASSOCIATION RULE (STUDI KASUS : RSUD LABUANG BAJI)

Zawiyah Saharuna, Iin Karmila Yusri, Yupita Febriani Mintu
Journal of Informatics and Computer Engineering Research
Management and Optimization Techniques
article

ANALISIS POLA PENYAKIT DENGAN METODE ASSOCIATION RULE (STUDI KASUS : RSUD LABUANG BAJI)

Zawiyah Saharuna, Iin Karmila Yusri, Yupita Febriani Mintu
article en

Abstract

RSUD Labuang Baji has a lot of medical record data, but this medical record data has not been used optimally and has not been processed to produce useful information for Laburan Baji Hospital. In this study the data used were outpatient medical record data in 2019, by analyzing three attributes, namely disease diagnosis (ICD), gender, and age group. The method for conducting data analysis is the association rule method using the Apriori algorithm and Tools R. The results of this study are disease patterns using a minimum support value of 0.01 and a minimum confidence value of 0.6, and the disease pattern formed is an associative rule with a combination of 2k-itemset and 3k item set of 25 associative rules where the rules for this disease pattern have a lift ratio value of > 1, so this disease pattern can be used as a recommendation to improve hospital services.

Journal of Informatics and Computer Engineering ResearchVol. 1(2)
KK Women's and Children's Hospital (SG), Politeknik Negeri Ujung Pandang
Openalex Percentile: Top 51%
Management and Optimization Techniques
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