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All Journal Jurnal Sosioteknologi Jurnal Otomasi Kontrol dan Instrumentasi
Nazuwatussya’diyah, Nazuwatussya’diyah
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Chemical Engineering, Chemistry & Bioengineering Control & Systems Engineering Engineering Industrial & Manufacturing Engineering Social Sciences

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Sistem Deteksi Cacat Pada Biji Kopi Melalui Model Algoritma Roboflow- Detection Transformer (RF-DTER) Sabar, Sabar; Nazuwatussya’diyah, Nazuwatussya’diyah; Pertiwi, Kisna; Fathurahman, Muhamad
Jurnal Otomasi Kontrol dan Instrumentasi Vol 18 No 1 (2026): Jurnal Otomasi Kontrol dan Instrumentasi
Publisher : Pusat Teknologi Instrumentasi dan Otomasi (PTIO) - Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/joki.2026.18.1.3

Abstract

Coffee bean quality control is a critical stage in processing industries to meet export and consumption standards. Traditional visual manual inspection often results in inconsistency, subjectivity, and reduced production throughput. This research implements the Roboflow Detection Transformer (RF-DETR), an end-to-end transformer-based object detection architecture, to identify subtle and complex coffee bean defects. The study uses image processing and machine learning with a labeled dataset of 2,010 coffee bean images classified into five defect categories: brown, black, unripe, broken black, and partially black. The data are split into 75% training, 17% validation, and 8% testing. Performance evaluation shows RF-DETR detects and classifies all defect types effectively, achieving a mean Average Precision (mAP) of 97,6%, with 95,7% precision, 91,0% recall, and an F1 score of 93,29%. These results indicate that RF-DETR balances accurate spatial localization with reliable class prediction, minimizes false positives, and maintains strong detection sensitivity. Therefore, RF-DETR provides a solid technological basis for high-precision, real-time automated coffee bean sorting in industrial settings. For deployment, it can be integrated with production cameras and conveyor sorting actuators to deliver fast, consistent decisions. Future work may optimize augmentation, lighting calibration, and edge computing deployment to improve robustness across varied production lines in practice.
Analisis Teknokultur Pengelolaan Air Limbah Batik di Cirebon Selama dan Setelah Pandemi COVID-19 Nazuwatussya’diyah, Nazuwatussya’diyah; Ekawati, Estiyanti; Nugraha, Ashari Budi; Yulia, Elfi; Srie Rejeki, Eggie Rizki
Jurnal Sosioteknologi Vol. 25 No. 1 (2026): MARCH 2026
Publisher : Fakultas Seni Rupa dan Desain ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/sostek.itbj.2026.25.1.1

Abstract

Public perception of the need for batik has declined since the COVID-19 pandemic. It significantly reduced the quantity of batik sales and production, with many industries ceased production. Therefore, relevant strategies integrating technology and culture were needed to maintain the resilience and sustainability of batik businesses. This paper presents the techno-culture view of three aspects of the batik industry: the production process, marketing, and management of batik wastewater. To capture the current conditions, field surveys using qualitative methods in questionnaires and interviews with batik respondents were carried out twice in Trusmi, Cirebon, during and after the COVID-19 pandemic. The survey results were presented, comparing wastewater characteristics during and after the pandemic to determine whether there were significant differences in the wastewater management process between the two periods. The priority of wastewater management strategy was analyzed using the Analytical Hierarchical Process, and it was found that the main priority was the environment (0.58), followed by social (0.23), economy (0.15), and institution (0.05). In addition, the Water Quality Index in the sample has a value range of 47 (Class III/Fair) to 69 (Class IV/Poor/Marginal).
Co-Authors Ekawati, Estiyanti Fathurahman, Muhamad Kisna Pertiwi, Kisna Nugraha, Ashari Budi Sabar Sabar Srie Rejeki, Eggie Rizki Yulia, Elfi