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Implementasi K-Means Clustering pada Citra Digital Tomat untuk Identifikasi Kondisi Segar dan Busuk Nasrul Mahruf Aznawi; Muhammad Irham Setiadi; Zarifah Aina; Setti Manullang; Shafira Nur Rahmadiyah
Journal of Students‘ Research in Computer Science Vol. 6 No. 1 (2025): Mei 2025
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/srtqmw49

Abstract

The manual identification of fresh and rotten tomatoes has still relied on human visual observation, which tends to be inconsistent and time-consuming. This study aimed to develop a tomato image classification system using the K-Means Clustering method based on color, shape, and texture features to automatically identify fresh and rotten conditions. The Dataset consisted of 500 tomato images for training and 60 tomato images for testing, equally representing fresh and rotten conditions. The process involved converting the images into L*a*b and grayscale formats, performing segmentation using K-Means, and extracting shape and texture features for the classification process. The testing results showed that the system successfully classified fresh and rotten tomatoes with an accuracy rate of 95%, with both precision and recall exceeding 93% for each class. These findings indicated that the K-Means method could be effectively applied in tomato image processing to support the sorting process of agricultural products. This research contributed to the development of a digital image-based classification system that could be integrated into smart agriculture systems.
SISTEM PENDUKUNG KEPUTUSAN PENENTUAN JURUSAN SISWA MENGGUNAKAN METODE FUZZY TAHANI Zarifah Aina; Sriani Sriani; Ahmad Taufik Al Afkari Siahaan
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 4 (2026): August 2026 (1)
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i4.7050

Abstract

Abstract: The process of assigning academic tracks for students at MAN 3 Medan is still carried out manually based on students’ own choices, which risks producing decisions that do not match their actual ability and interest. This study develops a web-based decision support system using the Fuzzy Tahani method to recommend the MIPA, IPS, and Islamic Religious Studies tracks for Grade X students. Four criteria are used: academic grades, interest, aptitude, and learning style, processed through fuzzification and a fuzzy query with the AND (minimum) operator. To overcome cases where the standard operator produces a zero fire strength for every track, this study proposes a two-stage evaluation consisting of a primary evaluation, a secondary MAX-fix evaluation, and a raw-score tie-break. Data were collected from 188 students through report-card grades and a 33-item questionnaire, then processed with the Laravel framework and a MySQL database. The system recommended the MIPA track for 78 students, IPS for 80 students, and Islamic Religious Studies for 30 students. Accuracy testing against actual Grade XI tracks yielded 86.70%, black-box testing showed that all features functioned correctly, and System Usability Scale (SUS) testing produced a score of 75.00, categorized as Acceptable with a Good adjective rating. Keywords: decision support system; Fuzzy Tahani; track assignment; fire strength; System Usability Scale   Abstrak: Proses penentuan jurusan siswa di MAN 3 Medan masih dilakukan secara manual berdasarkan pilihan siswa, sehingga berpotensi menghasilkan keputusan yang kurang sesuai dengan kemampuan dan minat siswa. Penelitian ini membangun sistem pendukung keputusan berbasis web menggunakan metode Fuzzy Tahani untuk merekomendasikan jurusan MIPA, IPS, dan Ilmu Keagamaan Islam bagi siswa kelas X. Empat kriteria digunakan, yaitu nilai akademik, minat, bakat, dan gaya belajar, yang diproses melalui tahap fuzzifikasi dan fuzzy query dengan operator AND (minimum). Untuk mengatasi kasus fire strength bernilai nol pada seluruh jurusan akibat operator standar, penelitian ini mengusulkan evaluasi bertingkat berupa evaluasi primer, evaluasi sekunder (MAX-fix), dan tie-break berbasis skor mentah. Data diperoleh dari 188 siswa melalui nilai rapor dan kuesioner 33 item, kemudian diproses menggunakan framework Laravel dan basis data MySQL. Sistem merekomendasikan 78 siswa ke jurusan MIPA, 80 siswa ke jurusan IPS, dan 30 siswa ke jurusan Ilmu Keagamaan Islam. Pengujian akurasi terhadap jurusan aktual kelas XI menghasilkan akurasi 86,70%, pengujian black-box menunjukkan seluruh fitur berjalan sesuai fungsinya, dan pengujian System Usability Scale (SUS) menghasilkan skor 75,00 dengan kategori Acceptable dan predikat Good. Kata kunci: sistem pendukung keputusan; fuzzy tahani; penentuan jurusan; fire strength; system usability scale