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All Journal Journal of Artificial Intelligence and Engineering Applications (JAIEA) AMMA : Jurnal Pengabdian Masyarakat
Agung Triyono
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Humanities Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing

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Implementation of the Naive Bayes Method in Sentiment Analysis of Spotify Application Reviews Agung Triyono; Ahmad Faqih; Fathurrohman
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 2 (2025): February 2025
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i2.824

Abstract

This study focuses on sentiment analysis of Spotify application reviews on Google Play Store using the Naive Bayes algorithm. As a leading music streaming platform, Spotify receives diverse user feedback that reflects their experiences, complaints, and satisfaction. Sentiment analysis aids in understanding user opinions, enhancing services, and innovating features. The research involves collecting user reviews via web scraping, followed by preprocessing steps such as text cleaning, tokenization, normalization, stopword removal, and stemming. The Term Frequency-Inverse Document Frequency (TF-IDF) method is employed to assign weights to words, highlighting their significance in reviews. The Naive Bayes algorithm categorizes sentiments into positive, negative, and neutral classes. Performance evaluation uses a confusion matrix to measure accuracy, precision, recall, and F1-score. Results indicate that Naive Bayes effectively classifies large volumes of unstructured data with high accuracy and efficiency. This study contributes practically by offering actionable insights to improve Spotify's services and theoretically by advancing sentiment analysis methodologies using machine learning. The findings highlight the algorithm's potential to understand user needs and address issues, reinforcing its value in text analytics for mobile applications.
Penyusunan Laporan Keuangan Sederhana Berbasis Excel untuk Usaha Mikro Umi Hayati; Willy Prihartono; Agung Saeful; Agung Triyono
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 04 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Micro businesses are the backbone of the Indonesian economy, but there are still many micro businesses that do not have the ability to keep good and systematic financial records. The main problem faced is the lack of understanding of the importance of financial statements as well as limitations in the use of complex accounting technology. This service activity aims to increase the capacity of micro business actors in preparing simple financial reports by utilizing Microsoft Excel. The program is conducted through face-to-face training, hands-on practice, and intensive mentoring. The training materials include basic introduction to accounting, making profit and loss statements, cash flow statements, and using Excel templates that have been prepared by the team. The methods used included group discussions, case studies, simulations, and evaluation of results. The results of the activities showed that the partners experienced a significant improvement in their understanding and financial recording skills. Some partners have implemented daily transaction recording and are able to prepare financial reports independently. In addition, awareness of the importance of financial management for business sustainability also increased. Future recommendations include the need for further training, development of digital-based financial recording applications, and collaboration with financial institutions to access funding. This activity proves that with the right approach, micro-entrepreneurs can be encouraged to be more professional in managing their finances, thus increasing their competitiveness and business sustainability amidst dynamic economic challenges.
Co-Authors Agung Saeful Ahmad Faqih Fathurrohman, Fathurrohman Umi Hayati Willy Prihartono