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All Journal Jurnal Hutan dan Masyarakat Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL GALUNG TROPIKA Gorontalo Journal of Forestry Research Jurnal Pengabdian Masyarakat Abdimas Madani ILTEK : Jurnal Teknologi Journal of Embedded Systems, Security and Intelligent Systems Jurnal Pengabdian Sosial Ase Journal
Muh. Ichwan Kadir
Fakultas Pertanian, Universitas Islam Makassar
Religion Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Nursing Public Health Social Sciences

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RANCANG BANGUN SISTEM INFORMASI DATA KEBUTUHAN PETANI JAGUNG HIBRIDA KUNING BERBASIS ANDROID (STUDI KASUS DESA TOLADA - KABUPATEN LUWU UTARA) Husain, Nursuci Putri; Suradi, Suradi; Kadir, Muh. Ichwan; Herwinsyah, Herwinsyah; Futriani, Riski
ILTEK : Jurnal Teknologi Vol. 19 No. 01 (2024): ILTEK : Jurnal Teknologi
Publisher : Fakultas Teknik Universitas Islam Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47398/iltek.v19i01.154

Abstract

Pertanian jagung hibrida kuning di Desa Tolada, Kabupaten Luwu Utara, merupakan salah satu sektor penting yang mendukung ekonomi lokal. Namun, berbagai tantangan yang dihadapi petani dalam pengelolaan pertanian seringkali menghambat produktivitas dan efisiensi. Tujuan penelitian ini adalah merancang sebuah sistem untuk memfasilitasi pengumpulan, pengelolaan, dan penyajian data kebutuhan petani. Metode penelitian yang digunakan adalah Research and Development (R&D), yang melibatkan beberapa tahap utama. Pertama, dilakukan analisis kebutuhan untuk mengidentifikasi kebutuhan petani jagung hibrida kuning melalui wawancara dan observasi. Selanjutnya, perancangan sistem dilakukan untuk membuat desain arsitektur aplikasi berbasis Android. Setelah itu, pengembangan sistem dilakukan dengan mengimplementasikan desain menjadi aplikasi nyata. Tahap berikutnya adalah pengujian sistem untuk memastikan semua fitur berfungsi dengan baik, diikuti oleh evaluasi dan penyempurnaan berdasarkan umpan balik pengguna. Hasil dari penelitian ini adalah adanya sistem informasi berbasis Android yang dapat mendata kebutuhan petani jagung hibrida kuning di Desa Tolada, Kabupaten Luwu Utara. Sistem informasi ini juga telah diuji menggunakan metode Blackbox Testing dan telah divalidasi oleh pakar. Sistem ini mampu meningkatkan efisiensi pengelolaan data kebutuhan petani sehingga diharapkan dapat berkontribusi positif terhadap peningkatan produktivitas pertanian jagung hibrida kuning di wilayah tersebut.
A Multi-Branch EfficientNet-U-Net Hybrid Framework for Segmentation of Oyster Mushrooms in Cultivation Media Husain, Nursuci Putri; Kadir, Muh Ichwan
Journal of Embedded Systems, Security and Intelligent Systems Vol 7 No 1 (2026): March 2026
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v7i1.2607

Abstract

Purpose – This study aims to develop a semantic segmentation model for oyster mushrooms in cultivation media to support automated monitoring, growth analysis, and yield estimation in smart farming systems. Design/methods/approach – A Multi-Branch EfficientNet-U-Net hybrid architecture was proposed, using EfficientNet-B0 as the encoder and a multi-branch fusion strategy to integrate multi-scale features from three encoder levels. The dataset consisted of 150 manually annotated oyster mushroom images collected from two cultivation sites under varying illumination, mushroom cluster density, and background texture. The model was evaluated using Intersection over Union (IoU) and Dice Coefficient metrics on training, validation, and testing subsets. Findings – Experimental results show that the proposed model achieved high segmentation performance, with a median IoU of approximately 0.90 and a Dice coefficient of 0.93. Compared with the baseline U-Net, the proposed architecture produced cleaner segmentation boundaries and more consistent detection of mushroom regions under complex environmental conditions. Research implications/limitations – This study is limited by the relatively small dataset and evaluation on images from only two cultivation sites. Further studies should involve larger and more diverse datasets to assess robustness across broader cultivation environments. Originality/value – This study offers an effective semantic segmentation framework that combines EfficientNet-B0 encoding and multi-branch multi-scale feature fusion to improve oyster mushroom segmentation accuracy in real cultivation settings, with potential application in smart agriculture monitoring systems.
Co-Authors Ainun Nur, Rikhzan Amir, Nurjannah Anwar Umar Arman Awaluddin Yunus, Awaluddin Emban Ibnurusyd Mas'ud Futriani, Riski Hardiani, A. Susilawaty Hardiyanti Hardiyanti Hasanuddin Molo Herwinsyah Muh. Dzulkifli P Muh. Tahnur Nasir, Anugrahandini Nursuci Putri Husain Rihan Rosmiati Selamet Riyadi Supratman Supratman Suradi Suradi Syamsinar, S