ANALISIS SENTIMEN TERHADAP PENGGUNAAN APLIKASI MOBILE JKN DENGAN PENDEKATAN RANDOM FOREST CLASSIFIER
DOI:
https://doi.org/10.31849/gf3ekc32Keywords:
Sentimen Analisis, BPJS Kesehatan, Mobile JKN, TF-IDF, Random Forest ClassifierAbstract
Health is a fundamental need for all people. In an effort to ensure equitable access to health insurance services in Indonesia, the government has assigned BPJS Kesehatan as the national health insurance provider. As part of its digital innovation, BPJS Kesehatan introduced the Mobile JKN application to make it easier for the public to access healthcare services online. However, the implementation of this application still raises various complaints, such as login difficulties, update disruptions, and limited features, as reflected in predominantly negative user reviews. To objectively assess public perception, this study conducted sentiment analysis on 5,000 user reviews of Mobile JKN obtained from the Google Play Store. The analysis process included cleaning, tokenizing, stopword removal, stemming, labeling, and word weighting using TF-IDF. Classification was performed using the Random Forest Classifier algorithm. The results showed that out of 976 test data, 883 were correctly predicted and 93 were misclassified, with an accuracy of 90.47%, precision of 90.15%, recall of 90.47%, and an F1-score of 89.90%. These findings demonstrate that Random Forest is effective in identifying both positive and negative sentiments and can serve as a basis for the future development of the Mobile JKN application
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