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All Journal SKANIKA: Sistem Komputer dan Teknik Informatika SAINTEK
Helmi Ahmad Fauzi Candra
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Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Engineering Industrial & Manufacturing Engineering

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Pengembangan Sistem Rekomendasi Berpakaian Menggunakan Local Binary Pattern dan K-Nearest Neighbor di Program Studi Teknik Informatika Universitas Pelita Bangsa M. Najamuddin Dwi Miharja; Helmi Ahmad Fauzi Candra; Nanang Tedi
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 8 No 2 (2025): Jurnal SKANIKA Juli 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v8i2.3584

Abstract

The student code of ethics governs behavior, speech, actions, appearance, and dress during their academic journey. At Pelita Bangsa University, many students tend to follow evolving fashion trends, which often conflict with the faculty's dress code that emphasizes wearing formal, collared clothing. This research addresses the issue by developing an image-based detection system to identify whether students wear formal or informal attire. The study utilizes the Local Binary Pattern (LBP) method for feature extraction and the K-Nearest Neighbor (K-NN) method for classification. A total of 130 images were tested, consisting of 70 t-shirts and 60 shirts. The best accuracy was achieved using parameters R=1 and P=8 for LBP and K=1 with Euclidean distance for K-NN, resulting in an average accuracy of 95.16%. The developed system is capable of accurately classifying images of t-shirts and shirts, demonstrating high precision and efficiency in image-based classification. These findings indicate that the application of the Local Binary Pattern (LBP) and K-Nearest Neighbor (K-NN) methods is an effective combination for detecting compliance with student dress code regulations
Implementasi Metode Local Binary Pattern (LBP) Dan K-Nearest Neighbor (K-Nn) Pada Sistem Berpakaian Di Prodi Teknik Informatika Universitas Pelita Bangsa Isarianto; Helmi Ahmad Fauzi Candra
Prosiding Sains dan Teknologi Vol. 3 No. 1 (2024): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 3 - Januari 2024
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The student code of ethics is a set of rules that regulate students' attitudes, words, actions, appearance, and clothing while they are students. Pelita Bangsa University students also follow the development of fashion trends from fashion developments every year, which will have an impact on the dress code of ethics for students of the Pelita Bangsa University Faculty of Engineering. Dressing neatly and politely means wearing formal clothes when participating in campus activities. Several lecturers require wearing formal (collared) clothing when participating in learning activities. Research has been proposed to detect clothing using the Local Binary Pattern (LBP) method with the K-Nearest Neighbor (KNN) classification. 130 images were used with a composition of 70 images of t-shirts and 60 images of shirts. This system is used to detect t-shirts and shirts. A system will be designed to detect shirts that focus on Pelita Bangsa University students using the Local Binary Pattern (LBP) and K-Nearest Neighbor (KNN) methods as classifiers. It is hoped that the results of testing this research can get better accuracy than previous research. This accuracy was obtained from testing 130 images using the Lbp extraction method with values of R=1 and P=8, in addition to the KNN classification with values of K=1 and Euclidean distance parameters.
Co-Authors Isarianto M. Najamuddin Dwi Miharja Nanang Tedi