Sentiment Analysis of MyPertamina on Google Play Store Using Naïve Bayes for Sustainable Policies - Kustyana, Engkus; Eko Prasetyo; Shofa Nurfauziah; Wibi Alya Azahra; Zahra Nanda (Jurnal Dialektika: Jurnal Ilmu Sosial, 2024)
The MyPertamina application is a digital service developed by Pertamina to make it easier for people to carry out vehicle fuel transactions. However, the implementation of this application has generated various responses from users, both in the form of reviews and star ratings on the Google Play Store. User reactions to this application show a variety of opinions, including criticism and appreciation. This research aims to analyze user sentiment towards the MyPertamina application, which is classified into two main categories, namely positive and negative sentiment. The research dataset was obtained through a process of scraping user reviews on the Google Play Store in the period 1 October to 1 December 2024. The data used includes 4812 reviews with label division: ratings 4 and 5 are considered positive sentiment, while ratings 1, 2, and 3 are considered positive sentiment. sentiment.negative Analysis was carried out using the Python programming language via the Google Colab platform. The dataset is divided into 80% training data and 20% test data to build a sentiment classification model. The research results show that the Naive Bayes Classifier algorithm is used to carry out classification with an accuracy level of 78%, precision 75%, recall 99%, and f1-score 86%. This analysis shows that most sentiment towards the app is negative, reflecting user complaints regarding various technical issues with the app. It is hoped that this research can become a basis for improving the MyPertamina application system and provide insight for further research in sentiment classification.