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All Journal Jurnal Sistem Komputer dan Informatika (JSON) Bulletin of Computer Science Research
Deva Nita Mulya
Politeknik Bhakti Semesta, Salatiga
Computer Science & IT Control & Systems Engineering

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Analisis Sentimen Customer Feedback Tokopedia Menggunakan Algoritma Naïve Bayes Aldian Umbu Tamu Ama; Deva Nita Mulya; Yashinta Putri D Astuti; Ignatius Bias Galih Prasadhya
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 1 (2022): September 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4783

Abstract

Products and customers have a close relationship, therefore UMKM need to build good relationships with customers. The most common way that companies or UMKM do is to look at the reviews given, this is called customer feedback. The results of customer feedback to companies or UMKM can improve service and product quality. The problem that arises is how to process the many reviews given, especially reviews from marketplaces like Tokopedia. Therefore, a method is needed to see user reviews of the products being sold, whether positive or negative. The method that will be used is sentiment analysis. Sentiment analysis is the process of understanding and extracting and automatically processing text data and can produce sentiments that are displayed in a sentence. The steps taken were taking House of Smith customer review data at Tokopedia, manual labeling to get positive and negative data reviews, data preprocessing, TF-IDF weighting and classification using the Naïve Bayes algorithm. The results of sentiment testing using the Naïve Bayes algorithm with TF-IDF weighting quality accuracy of 83% with visualization of the distribution of words that appear the most are the words 'good', 'comfortable' and 'use' for positive reviews. The most frequent negative reviews were 'material' and 'thin' which indicated that some buyers felt that the product had a thin material.
Analisis Sentimen Customer Feedback Tokopedia Menggunakan Algoritma Naïve Bayes Aldian Umbu Tamu Ama; Deva Nita Mulya; Yashinta Putri D Astuti; Ignatius Bias Galih Prasadhya
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 4 No. 1 (2022): September 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4783

Abstract

Products and customers have a close relationship, therefore UMKM need to build good relationships with customers. The most common way that companies or UMKM do is to look at the reviews given, this is called customer feedback. The results of customer feedback to companies or UMKM can improve service and product quality. The problem that arises is how to process the many reviews given, especially reviews from marketplaces like Tokopedia. Therefore, a method is needed to see user reviews of the products being sold, whether positive or negative. The method that will be used is sentiment analysis. Sentiment analysis is the process of understanding and extracting and automatically processing text data and can produce sentiments that are displayed in a sentence. The steps taken were taking House of Smith customer review data at Tokopedia, manual labeling to get positive and negative data reviews, data preprocessing, TF-IDF weighting and classification using the Naïve Bayes algorithm. The results of sentiment testing using the Naïve Bayes algorithm with TF-IDF weighting quality accuracy of 83% with visualization of the distribution of words that appear the most are the words 'good', 'comfortable' and 'use' for positive reviews. The most frequent negative reviews were 'material' and 'thin' which indicated that some buyers felt that the product had a thin material.
Perancangan UI/UX Aplikasi Kasir Inklusif untuk Penyandang Disabilitas di Coffee Shop Aldian Umbu Tamu Ama; Ricky Arnold Nggili; Deva Nita Mulya; Yashinta Putri Dwi Astuti
Bulletin of Computer Science Research Vol. 5 No. 2 (2025): February 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i2.470

Abstract

Kopi Hening is a coffee business in Salatiga City managed by individuals who are deaf or hard of hearing. Facing challenges in customer communication and manual bookkeeping processes, this study aims to design a prototype UI/UX for an inclusive cashier application to enhance operational efficiency and bookkeeping accuracy. Using the Design Science Research Methodology (DSRM) approach, the study involved direct observation of cashier activities, interviews with supervisors, and design evaluation through simulations using the Cognitive Walkthrough method. The Cognitive Walkthrough evaluation, which measured user success rates in completing specific tasks, showed good performance with transaction scenarios achieving 83-86% success rates (cash payment 83%, transfer 83%, QRIS 86%) and financial bookkeeping scenarios reaching 73%. Expert evaluations confirmed that the design adheres to inclusive UI/UX principles, though further adjustments, such as optimizing text size and element spacing, are recommended for better accessibility. This study serves as an initial step toward supporting digital inclusion and provides a foundation for the future development of inclusive cashier applications.
Co-Authors Aldian Umbu Tamu Ama Ignatius Bias Galih Prasadhya Ricky Arnold Nggili Yashinta Putri D Astuti Yashinta Putri Dwi Astuti