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All Journal Brilliance: Research of Artificial Intelligence Room of Civil Society Development Room of Civil Social Development
Damar Novtahaning
Universitas Jember
Arts Humanities Decision Sciences, Operations Research & Management Education Mathematics Social Sciences Other

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Implementation of YOLO in Cabbage Plant Disease Detection for Smart and Sustainable Agriculture Saputra, Muhammad Andryan Wahyu; Novtahaning, Damar; Narandha Arya Ranggianto; Dwi Wijonarko
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.5054

Abstract

Cabbage plants are a commodity needed by the community and an export commodity that must have good quality and be worth selling. There are approaches to create detection systems, namely rule-based and image-based. The use of images allows the system to be reorganized by training data, resulting in a flexible system. The image will be detected by the model and then predict the cabbage plant disease. The data used is image data, namely Alternaria Spots, Healthy, Black Root, and White Rust. Implementation This research tests the YOLO model in making a detection system with the highest precision-confidence result for all labels is 78,5%. While in confusion-matrix testing, the highest result is 0.67 in White Rust disease. This indicates that the YOLO model can identify diseases in cabbage plants based on data that has been trained with great results.
Implementation of YOLO in Cabbage Plant Disease Detection for Smart and Sustainable Agriculture Saputra, Muhammad Andryan Wahyu; Novtahaning, Damar; Narandha Arya Ranggianto; Dwi Wijonarko
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.5054

Abstract

Cabbage plants are a commodity needed by the community and an export commodity that must have good quality and be worth selling. There are approaches to create detection systems, namely rule-based and image-based. The use of images allows the system to be reorganized by training data, resulting in a flexible system. The image will be detected by the model and then predict the cabbage plant disease. The data used is image data, namely Alternaria Spots, Healthy, Black Root, and White Rust. Implementation This research tests the YOLO model in making a detection system with the highest precision-confidence result for all labels is 78,5%. While in confusion-matrix testing, the highest result is 0.67 in White Rust disease. This indicates that the YOLO model can identify diseases in cabbage plants based on data that has been trained with great results.
Pengembangan Bank Sampah menggunakan Aplikasi E-WASTE di TPS 3R Baratan Jember Fadhil, Martiana Kholila; Soepandi, Harry; Leba, Katarina; Darmawan, Muhammad Riza; Novtahaning, Damar; Fitriyasari, Maliatul
Room of Civil Society Development Vol. 4 No. 5 (2025): Room of Civil Society Development
Publisher : Lembaga Riset dan Inovasi Masyarakat Madani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59110/rcsd.777

Abstract

Krisis pengelolaan sampah elektronik dan rendahnya digitalisasi sistem bank sampah menjadi tantangan dalam mewujudkan ekonomi sirkular di Indonesia. Penelitian ini bertujuan mengembangkan aplikasi E-WASTE untuk meningkatkan efisiensi dan transparansi pengelolaan bank sampah di TPS 3R Baratan, Kabupaten Jember. Penelitian menggunakan metode deskriptif kualitatif melalui observasi, wawancara mendalam, dan Focus Group Discussion (FGD) yang melibatkan 33 peserta dari berbagai kecamatan. Hasil penelitian menunjukkan peningkatan signifikan pengetahuan masyarakat dari nilai pre-test 4,61 menjadi post-test 8,58 (kenaikan 86,16%). Aplikasi E-WASTE dikembangkan dengan fitur utama berupa pencatatan digital berbasis mobile, klasifikasi otomatis jenis sampah, sistem poin reward, dan dashboard pemantauan real-time. Implementasi aplikasi ini meningkatkan partisipasi dan kesadaran masyarakat dalam memilah sampah, sekaligus memperkuat penerapan prinsip ekonomi sirkular di tingkat komunitas. Penelitian ini berkontribusi pada model replikasi program “1 Desa 1 Bank Sampah” sebagai inovasi digital berkelanjutan.
Pengembangan Bank Sampah menggunakan Aplikasi E-WASTE di TPS 3R Baratan Jember Fadhil, Martiana Kholila; Soepandi, Harry; Leba, Katarina; Darmawan, Muhammad Riza; Novtahaning, Damar; Fitriyasari, Maliatul
Room of Civil Society Development Vol. 4 No. 5 (2025): Room of Civil Society Development
Publisher : Lembaga Riset dan Inovasi Masyarakat Madani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59110/rcsd.777

Abstract

Krisis pengelolaan sampah elektronik dan rendahnya digitalisasi sistem bank sampah menjadi tantangan dalam mewujudkan ekonomi sirkular di Indonesia. Penelitian ini bertujuan mengembangkan aplikasi E-WASTE untuk meningkatkan efisiensi dan transparansi pengelolaan bank sampah di TPS 3R Baratan, Kabupaten Jember. Penelitian menggunakan metode deskriptif kualitatif melalui observasi, wawancara mendalam, dan Focus Group Discussion (FGD) yang melibatkan 33 peserta dari berbagai kecamatan. Hasil penelitian menunjukkan peningkatan signifikan pengetahuan masyarakat dari nilai pre-test 4,61 menjadi post-test 8,58 (kenaikan 86,16%). Aplikasi E-WASTE dikembangkan dengan fitur utama berupa pencatatan digital berbasis mobile, klasifikasi otomatis jenis sampah, sistem poin reward, dan dashboard pemantauan real-time. Implementasi aplikasi ini meningkatkan partisipasi dan kesadaran masyarakat dalam memilah sampah, sekaligus memperkuat penerapan prinsip ekonomi sirkular di tingkat komunitas. Penelitian ini berkontribusi pada model replikasi program “1 Desa 1 Bank Sampah” sebagai inovasi digital berkelanjutan.
Co-Authors Darmawan, Muhammad Riza Dwi Wijonarko Fadhil, Martiana Kholila FITRIYASARI, MALIATUL Harry Soepandi Leba, Katarina Muhammad Andryan Wahyu Saputra Narandha Arya Ranggianto