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All Journal Information Technology Education Journal Journal of Embedded Systems, Security and Intelligent Systems
Labusab
Universitas Negeri Makassar
Computer Science & IT Education

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Journal : Journal of Embedded Systems, Security and Intelligent Systems

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PENGEMBANGAN APLIKASI LUNAK UNTUK MONITORING KULIAH DARING DALAM UPAYA PENANGGULANGAN WABAH COVID-19 Muhammad Agung; Labusab
Journal of Embedded Systems, Security and Intelligent Systems Vol 1, No 2 (2020): November 2020
Publisher : Program Studi Teknik Komputer

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Abstract

Penelitian ini dilakukan untuk mengembangkan suatu aplikasi yang dapat digunakan dalam memonitoring proses pembelajaran yang dilakukan dalam lingkup Universitas Negeri Makassar (UNM). Dalam pengembangan aplikasi ini, sistem monitoring digunakan sebagai sarana rekam jejak pembelajaran daring yang dilakukan selama masa pandemic COVID-19 dan model ISO 9126 digunakan untuk menguji kehandalan dari aplikasi. Aplikasi ini divalidasi oleh pakar dan responden. Dari hasil validasi tersebut diperoleh aplikasi MonitorDaring yang mendapat penilaian Baik (B) oleh pakar dengan persentase 81,25%, dan mendapat penilaian Baik (B) oleh responden dengan persentase 77,89%.
INTEGRATION OF OTSU THRESHOLDING AND MORPHOLOGICAL OPERATIONS FOR CAROLINA REAPER CHILI IMAGE SEGMENTATION Andi Baso Kaswar; Labusab; Ismail Aqsha
Journal of Embedded Systems, Security and Intelligent Systems Vol 5, No 3 (2024): November 2024
Publisher : Program Studi Teknik Komputer

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Abstract

Segmentation is an important step in building a fruit-quality classification system. Previous research has shown the success of the Otsu Thresholding method for fruit image segmentation, but its application to Carolina Reaper chili images in Indonesia has not been carried out specifically. This research proposes the integration of the Otsu Thresholding method with morphological operations to improve the accuracy of Carolina Reaper chili image segmentation based on the ripeness level. The process starts with RGB image acquisition using a controlled camera, followed by red channel extraction as the segmentation input. The Otsu method is used to separate the object and background based on pixel intensity, resulting in a binary image that is enhanced through morphological operations, including dilation, imfill, and bwareaopen. The results show high accuracy, with averages of 99.85% (mature), 99.38% (almost mature), and 99.67% (raw). The average computation time is less than one second which shows the potential for real-time applications. This research contributes to the efficiency of technology-based postharvest processing of Carolina chili peppers
Co-Authors Andi Baso Kaswar Andi Baso Kaswar Aqsha, Ismail Muhammad Agung