Analisis Sentimen Aplikasi Mobile JKN di Google Play Store Menggunakan Algoritma Naive Bayes
-
Luthfi Eka Naufal
*
Univeritas Pelita Bangsa, Bekasi,
Indonesia
- Nurhadi Surojudin Univeritas Pelita Bangsa, Bekasi, Indonesia
- Irfan Afriantoro Univeritas Pelita Bangsa, Bekasi, Indonesia (*) Corresponding Author
Abstract
Health is a human right that must be fulfilled by the state, one of which is through the National Health Insurance-Kartu Indonesia Sehat (JKN-KIS) program managed by BPJS Kesehatan. To support the service, BPJS Kesehatan launched the Mobile JKN application in 2017. However, in its implementation, this application still faces various technical issues that affect user satisfaction and experience. This study aims to analyze user sentiment towards the Mobile JKN application by applying the Naive Bayes classification method. The data used comes from 10,000 user reviews on the Google Play Store in the period April to June 2024. The analysis results show that most reviews are positive (64%), followed by negative reviews (32.61%), and neutral (3.39%). The Naive Bayes model used showed excellent performance with an accuracy of 91.3%, an Area Under Curve (AUC) value of 0.985, and balanced precision and recall. However, the classification of neutral reviews is still not optimal due to their ambiguous nature. This research provides useful input for BPJS Kesehatan to improve the quality of JKN Mobile application services and increase user satisfaction.
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