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All Journal Jurnal Ilmiah KOMPUTASI EDUMATIC: Jurnal Pendidikan Informatika Jurnal Ilmiah Sains dan Teknologi Jurnal Media Informatika MASALIQ: Jurnal Pendidikan dan Sains Data Sciences Indonesia (DSI) Mutiara: Jurnal Penelitian dan Karya Ilmiah Competitive Jurnal Pengabdian Masyarakat Indonesia (JPMI)
Maresti, Fatia Amalia
Universitas Logistik Dan Bisnis Internasional
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Physics Social Sciences Transportation Other

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Journal : EDUMATIC: Jurnal Pendidikan Informatika

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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.
Co-Authors Aleffa Rahman, Mylo Anisah, Sabrina Nur Azzahra, Siti Salwa Ginasta, Nava Gia Hargiyanto, Radio Ananto Intan Novita Dewi, Intan Novita Kiki Mustaqim Laode Muhammad Aznur Syahfajar Lustin, Maria B. B. C. Lustin, Maria Bernadina Cintany Muhammad Vito Aristawidya Mustaqim , Kiki Mustaqim, Kiki Mustika Anugraheni, Gabriella Ningsih, Salsa Paringga Pangestu Pakpahan, Thiodas H. Pakpahan, Thiodas Heni Rahayu, Woro I. Rahayu, Woro Isti Riza, Noviana Ulfiani Ramadhani, Firna Wardana, Aulia