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All Journal EDUMATIC: Jurnal Pendidikan Informatika Communications in Humanities and Social Sciences
Intan Novita Dewi, Intan Novita
Program Studi Teknik Industri Fakultas Teknik UNDIP
Religion Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences

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Analisis Sentimen Ulasan Aplikasi PosPay untuk Meningkatkan Kepuasan Pengguna dengan Metode K-Nearest Neighbor (KNN) Mustaqim, Kiki; Amaresti, Fatia Amalia; Dewi, Intan Novita
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.24779

Abstract

PT Pos Indonesia has launched a digital pospay service. Users who have a positive experience are more likely to return to application. User perceptions analysis can be known from the Review sentiments. Review sentiments that are classified as positive and negative are really needed by developers to improve services (user satisfaction). The research aims to increase user satisfaction of the PosPay application based on the application's review data. The source of data is a review of the pospay application at Google play store. The method used quantitative study method that is K-Nearest Neighbor (K-NN) that classify objects based on learning data that are closest to the object. Research variable is the word from user commentary that associated with the pospay application services. Application review data in scrapping, preprocessing, splits data (train data and test data). Supervised learning (TF-IDF and K-NN) prepared with python programming provides data visualizing. The research results show that the sentiment of Pospay application users tends to be positive. K-NN classification model produces 91% accuracy, 90% precision and recall by 99%. The key word of positive sentiment is: easy, helpful, transaction. Keyword negative sentiment: balance, pay, login.
Assessment of mobile payment service based on user review in Indonesia Dewi, Intan Novita; Nurcahyo, Rahmat; Farizal
Communications in Humanities and Social Sciences Vol. 4 No. 2 (2024): CHSS
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia (KIPMI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/chss.4.2.2024.81

Abstract

This study evaluates user satisfaction with mobile payment services, focusing on sentiment of user reviews from Twitter. Four key dimensions—reliability, economic benefits, assurance, and responsiveness—were analyzed for two applications, DANA and LinkAja. This study used Support Vector Machine algorithm with an accuracy measurement using the Confusion Matrix reaching 83.83% for DANA and 82,58% for LinkAja. The ROC curve showed the best AUC result of 0.909 for DANA and 0.900 for LinkAja (Excellent Classification). Sentiment analysis revealed that both applications faced predominantly negative sentiment, except for the economic benefit dimension of LinkAja, which showed a higher proportion of positive sentiment. Major issues identified include slow problem resolution, unresponsive customer service, and occasional application errors. These challenges highlight user dissatisfaction and the need for improved customer service and system reliability. The findings underscore the importance of addressing user complaints promptly to enhance satisfaction and foster loyalty.
Co-Authors Farizal Maresti, Fatia Amalia Mustaqim, Kiki Rahmat Nurcahyo