Agents: Journal of Artificial Intelligence and Data Science
Vol 4 No 1 (2024): Vol 4 No 1 (2024): September - Februari

Tinjauan Sentimen Terhadap Ulasan Aplikasi Peminjaman Online dengan Metode Support Vector Machine (SVM)

ST. Aminah Dinayati Ghani (Universitas Dipa Makassar)
Nur Salman Nur Salman (Universitas Dipa Makassar)
Farhan Wahyuta Kusuma Farhan Wahyuta Kusuma (Universitas Dipa Makassar)



Article Info

Publish Date
28 Feb 2024

Abstract

Online loans, abbreviated as "Pinjol," refer to the practice of lending money online through applications or websites without involving traditional financial institutions such as banks or other traditional creditors. Examples of applications in this field include AkuLaku and Kredivo. These apps operate in the e-commerce and credit provision sectors in Southeast Asia, including Indonesia. Despite their operational strengths, these applications have both advantages and disadvantages, leading to positive and negative reviews on platforms like the Play Store. The research aims to identify positive and negative reviews within these online loan applications that can influence users' decisions when choosing a particular app. SVM classification technique is employed to analyze positive and negative sentiments from these reviews. The accuracy results obtained after sentiment analysis for Kredivo are 81%, while for AkuLaku, it is 75%. A higher accuracy value indicates a better ability of the model to predict sentiments correctly. Visualization of impactful words based on word frequency is presented in the form of a Word Cloud. Therefore, based on the sentiment analysis conducted using the SVM model, the author suggests choosing the Kredivo app when selecting an online loan application, as the analysis indicates that Kredivo has better quality compared to AkuLaku.

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Journal Info

Abbrev

agents

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

Description

The AGENTS published the original manuscripts from researchers, practitioners, and students in the various topics of Artificial Intelligence and Data Science including but not limited to fuzzy logic, genetic algorithm, evolutionary computation, neural network, hybrid systems, adaptation and learning ...