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All Journal Jurnal PkM MIFTEK Journal of Intelligent Systems Technology and Informatics
Nurapipah, Nida
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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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LITERASI DIGITAL DAN DIGITALISASI KESENIAN DI DESA MEKARMUKTI Elsen, Rickard; Ramadhan, Iwan; Hamzah, Muhamad; Kaulan, Muhammad Denanda; Nurapipah, Nida; Septiyani, Tiara; Amelia, Melina; Indallah, Aghniya Qolbin; Putri, Salsabilah Triana; Romansah, Ubad; Munawar, Deni Wildan; Mubarok, Zam Zam; Abadi, Manza Restu; Hanif, Muhammad; Jaelani, Iqbal Waliyuddin Sidiq; Assholih, Mukhtar; Apriliansah, Rudi; Nurzaman, Ikbal Saputra; Septiana, Yuga; Saputra, Raihan Rafif Syaefudin; Alamsyah, Reza Bachtiar; Rosandi, Ujang Ahmad
Jurnal PkM MIFTEK Vol 6 No 1 (2025): Jurnal PkM MIFTEK
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/miftek/v.6-1.1945

Abstract

This study explores the role of students in the Mekarmukti village community over a period of one month, specifically through real work lecture activities with digital literacy work programs, education, physical development, and collaboration with the village government and other campuses. These activities involve introducing social media to artists, teaching Bebras and Information and Communication Technology Volunteers, teaching in early childhood education (PAUD), and optimizing Micro, Small, and Medium Enterprises through the introduction of Google Maps, rebranding, and employee needs analysis. In addition, students participated in helping prepare for the 79th Anniversary of the Republic of Indonesia, teaching the Koran, cleaning the mosque environment, painting Posyandu and PAUD, and helping with the physical construction of the sports building. This study uses a qualitative method with a case study approach to analyze the impact and contribution of students in these activities.
Skin Tone Classification in Digital Images Using CNN For Make-Up and Color Recommendation Nurapipah, Nida; Yuliana, Siti Sarah
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.v1i3.29

Abstract

Human skin tone variation is an obstacle in the development of a digital beauty product recommendation system. The purpose of this study is to categorize skin tone into three groups (Black, Brown, and White). Using a Convolutional Neural Network (CNN) based on the refined EfficientNetB0 architecture on a balanced dataset of 1,500 facial images, each class consisting of 500 images. All images in the dataset have been resized to 224 × 224 pixels to match the model input and ensure data uniformity and compatibility with the EfficientNetB0 model architecture used. The dataset used was obtained from the Kaggle platform and processed through the normalization and augmentation stages. It was then evaluated through the validation process using the 5-fold cross-validation method. This model achieved a total accuracy level of 88.67%, with the white category demonstrating precision (0.93), recall (0.95), and F1-score (0.94), as well as the highest AUC of 0.99, indicating very satisfactory performance. Additionally, this system can offer personalized beauty product recommendations, including foundation shades, lipstick colors, and clothing color palettes, tailored to specific skin tones. This method enhances the user experience by providing accurate recommendations that adapt to various lighting conditions, making it suitable for use on digital beauty platforms.
Co-Authors Abadi, Manza Restu Alamsyah, Reza Bachtiar Amelia, Melina Apriliansah, Rudi Assholih, Mukhtar Elsen, Rickard Hamzah, Muhamad Indallah, Aghniya Qolbin Jaelani, Iqbal Waliyuddin Sidiq Kaulan, Muhammad Denanda Mubarok, Zam Zam Muhammad Hanif Munawar, Deni Wildan Nurzaman, Ikbal Saputra Putri, Salsabilah Triana Romansah, Ubad Rosandi, Ujang Ahmad RR. Ella Evrita Hestiandari Saputra, Raihan Rafif Syaefudin Septiana, Yuga Septiyani, Tiara Yuliana, Siti Sarah