TY - JOUR
T1 - Factor analysis influencing Mobile JKN user experience using sentiment analysis
AU - Qahar, Muhammad Yazid Al
AU - Ruldeviyani, Yova
AU - Mukharomah, Ulfah Nur
AU - Fidyawan, Miftahul Agtamas
AU - Putra, Ramadhoni
N1 - Publisher Copyright:
© 2024, Institute of Advanced Engineering and Science. All rights reserved.
PY - 2024/6
Y1 - 2024/6
N2 - Social security administration for health or Badan Penyelenggara Jaminan Sosial Kesehatan (BPJS Kesehatan), as a public legal entity, has a critical role in the health of the Indonesian population. BPJS Kesehatan introduced the Mobile national health insurance or jaminan kesehatan nasional (JKN) application to enhance its services, enabling Indonesians to access it directly. Nevertheless, the rating of the Mobile JKN application on the Google Play Store has shown a gradual decline over time. Therefore, this study was conducted to analyze the factors influencing the user experience of the Mobile JKN application, utilizing the review data obtained from the Google Play Store. Sentiment analysis using the Naïve Bayes (NB) classification model and support vector machine (SVM) combined with synthetic minority oversampling technique (SMOTE) and slang word replacement. The results obtained an accuracy value of 93.33%, precision of 93.76%, recall of 93.33%, and F1-score of 93.43%. A further analysis was conducted using online service quality factors to obtain the main factors influencing the experience of Mobile JKN application users. The evaluation findings revealed that factors of security, ease of use, and timeliness are three fundamental aspects that should be given immediate attention by BPJS Kesehatan while improving the Mobile JKN application in the future.
AB - Social security administration for health or Badan Penyelenggara Jaminan Sosial Kesehatan (BPJS Kesehatan), as a public legal entity, has a critical role in the health of the Indonesian population. BPJS Kesehatan introduced the Mobile national health insurance or jaminan kesehatan nasional (JKN) application to enhance its services, enabling Indonesians to access it directly. Nevertheless, the rating of the Mobile JKN application on the Google Play Store has shown a gradual decline over time. Therefore, this study was conducted to analyze the factors influencing the user experience of the Mobile JKN application, utilizing the review data obtained from the Google Play Store. Sentiment analysis using the Naïve Bayes (NB) classification model and support vector machine (SVM) combined with synthetic minority oversampling technique (SMOTE) and slang word replacement. The results obtained an accuracy value of 93.33%, precision of 93.76%, recall of 93.33%, and F1-score of 93.43%. A further analysis was conducted using online service quality factors to obtain the main factors influencing the experience of Mobile JKN application users. The evaluation findings revealed that factors of security, ease of use, and timeliness are three fundamental aspects that should be given immediate attention by BPJS Kesehatan while improving the Mobile JKN application in the future.
KW - Mobile JKN
KW - Naïve Bayes
KW - Online service quality factor
KW - Sentiment analysis
KW - SMOTE
KW - Support vector machine
UR - http://www.scopus.com/inward/record.url?scp=85193693061&partnerID=8YFLogxK
U2 - 10.11591/ijai.v13.i2.pp1782-1793
DO - 10.11591/ijai.v13.i2.pp1782-1793
M3 - Article
AN - SCOPUS:85193693061
SN - 2089-4872
VL - 13
SP - 1782
EP - 1793
JO - IAES International Journal of Artificial Intelligence
JF - IAES International Journal of Artificial Intelligence
IS - 2
ER -