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All Journal Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi)
Gunadarma, I Ketut Agus Leo
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Computer Science & IT

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Performance Analysis of the K-Nearest Neighbors (K-NN) for Sentiment Analysis of Online Loan Application X Gunadarma, I Ketut Agus Leo; Arya Sasmita, Gusti Made; Prayana Trisna, I Nyoman
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 12 No 3 (2024): Vol. 12, No. 3, December 2024
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2024.v12.i03.p07

Abstract

The digital economy in Indonesia is growing rapidly, including in online lending services. Application X is one of the popular online lending applications, offering users convenience in applying for loans online. This research employs sentiment analysis on user reviews of Application X to understand their preferences and needs. The K-Nearest Neighbours (K-NN) method is applied as the primary algorithm for sentiment classification. Data collected through user review scraping undergoes a series of preprocessing stages, such as tokenization, stop word removal, and stemming, aimed at improving data quality. The K-NN model is tested in various scenarios to achieve the best results. The best scenario reveals that the highest accuracy is achieved by the K-NN model when the stop word removal process is not applied during the data preprocessing stage where the accuracy without using the stop word process was 92.9%, compared to 89.9% when using stop words.
Co-Authors Gusti Made Arya Sasmita Prayana Trisna, I Nyoman