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All Journal Jurnal PkM MIFTEK Journal of Intelligent Systems Technology and Informatics
Haq, Faizal
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Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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Perbaikan Sistem Kerja Pada Industri Sepatu di CV. Civani Wanaraja-Garut Fatimah, Dini Destiani Siti; Abdalah, Salman Nurdin; Haq, Faizal; Hidayatulloh, Endang Prayoga; Aprila, Dzikri; Rahman, Taupik; Nurzaman, Muhammad Zein; Amelia, Nadya; Oktapiani, Vini; Nurhaqiqi, Lisda; Aditia, Aditia; Alfarez, Rendi; Yusuf, Muhammad; Aldika, Alwin; Andriani, Ai Dini; Rahmadiani, Dina; Fahrezi, Filah; Mujahidin, Mujahidin; Ramadania, Sania Putri; Hanifah, Dinda; Efendi, Kurniawan; Kurniawan, Dede Rizki
Jurnal PkM MIFTEK Vol 4 No 1 (2023): Jurnal PkM MIFTEK
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/miftek/v.4-1.1324

Abstract

Standardization of work systems is necessary both for companies and for workers, standardization makes it easier for companies to make company plans and targets. For workers, standardization is a guide in making it easier for workers to do their work. This study aims to integrate the results of research conducted from 2022 and try it out, resulting in standardization of work systems in the shoe industry at CV. Civani which includes the specifications and physical form of the facilities used, work methods for each work station and the physical work environment that meets the job requirements. By standardizing the work system, it is hoped that workers will be more comfortable and safe in doing their jobs and help in achieving targets.
Customer Comment Clustering for Kahf Face Wash at Kahf Official Shop Using K-Means Method Arbiansyah, Gilang; Haq, Faizal
Journal of Intelligent Systems Technology and Informatics Vol 1 No 3 (2025): JISTICS, November 2025
Publisher : Aliansi Peneliti Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64878/jistics.v1i3.23

Abstract

The advancement of information technology has encouraged people to shop more confidently, including for men's skincare products. Although data indicate that men's interest in skincare remains relatively low, sales of Kahf Face Wash show high figures. In this context, consumer reviews on e-commerce platforms serve as a valuable source of information for understanding customer satisfaction and experience. This study aims to group consumer comments on Kahf Face Wash products from the Kahf Official Shop using the K-Means clustering method. A total of 4,966 consumer comments were collected automatically through web crawling techniques. These comments then underwent several text processing stages, including case folding, cleaning, tokenization, normalization, removal of stop words, and stemming. After the cleaning process, 2,431 comments remained for analysis. The textual data was transformed into numerical representations using the TF-IDF method, and the optimal number of clusters was determined using the Elbow method, which indicated the optimal value at k = 3. The clustering results categorized the comments into three groups: purchase experience (1,506 comments), product effectiveness (474 comments), and delivery and service (451 comments). Visualization was conducted using PCA and bar charts to better illustrate the distribution and proportion of comments in each cluster. Evaluation of the clustering results using inertia and the Davies–Bouldin Index revealed that the model effectively grouped the comments with a reasonably high quality. This study makes a significant contribution by helping companies analyze customer behavior through an unsupervised learning approach. This method enables companies to efficiently extract structured insights from unstructured reviews, which can be utilized to enhance service quality, marketing strategies, and future product development.
Co-Authors Abdalah, Salman Nurdin Aditia, Aditia Aldika, Alwin Alfarez, Rendi Amelia, Nadya Andriani, Ai Dini Aprila, Dzikri Arbiansyah, Gilang Dini Destiani Siti Fatimah Efendi, Kurniawan Fahrezi, Filah Hanifah, Dinda Hidayatulloh, Endang Prayoga Kurniawan, Dede Rizki Muhammad Yusuf Mujahidin Mujahidin Nurhaqiqi, Lisda Nurzaman, Muhammad Zein Oktapiani, Vini Rahmadiani, Dina Ramadania, Sania Putri Taupik Rahman