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All Journal ComEngApp : Computer Engineering and Applications Journal Jurnal Teliska Bulletin of Electrical Engineering and Informatics Sinergi Annual Research Seminar Proceeding of the Electrical Engineering Computer Science and Informatics VOLT : Jurnal Ilmiah Pendidikan Teknik Elektro Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal SOLMA Journal of Applied Smart Electrical Network and System (JASENS) Jurnal Rekayasa Elektro Sriwijaya International Journal of Research in Vocational Studies (IJRVOCAS) Aptekmas : Jurnal Pengabdian Kepada Masyarakat Sriwijaya Electrical and Computer Engineering (Selco) Journal
Yurni Oktarina
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Model Deep Learning Hybrid CNN-AE untuk Klasifikasi Presisi Warna Buah Melon Oktarina, Yurni; Dewi, Tresna; Septiyani AR, Dini
Journal of Applied Smart Electrical Network and Systems Vol. 6 No. 2 (2025): Vol. 6 No. 02 (2025): Vol 06, No. 02 Desember 2025
Publisher : Indonesian Society of Applied Science (ISAS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/d3hydf28

Abstract

Melon fruit color classification is a critical step in assessing fruit ripeness and quality. This study proposes a hybrid deep learning model that integrates Convolutional Neural Network (CNN) and Attention Enhancement (AE) for accurate classification of melon fruit color. The model leverages CNN’s strength in visual feature extraction while enhancing focus on crucial image regions through the attention mechanism. A diverse image dataset of melon fruits was collected under various lighting conditions and angles. Pre-processing steps, including data augmentation, normalization, and image scaling, were applied to improve model generalization. The CNN-Attention hybrid architecture incorporates an attention module into the CNN layers to emphasize significant features. Comparative experiments between the standard CNN and the hybrid model demonstrate that the latter achieves superior classification accuracy, with an average improvement of 5%. Moreover, the hybrid model exhibits better robustness against image noise and lighting variations. These results indicate that incorporating Attention Enhancement can yield a more adaptive and reliable model for melon fruit color classification. The proposed approach is expected to support the development of automated systems for fruit sorting in agriculture and distribution, enhancing speed, accuracy, and efficiency for farmers, traders, and consumers.
Diseminasi Inkubator Cerdas Berbasis PLTS Untuk Penguatan Manajemen Penetasan Telur pada Peternak Ayam Mikro Risma, Pola; Oktarina, Yurni; Dewi, Tresna; Yahya, M. Amri; Al-Rasyid, Johansyah
Jurnal SOLMA Vol. 15 No. 1 (2026)
Publisher : Universitas Muhammadiyah Prof. DR. Hamka (UHAMKA Press)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/solma.v15i1.21625

Abstract

Background: Rendahnya tingkat keberhasilan penetasan telur ayam pada peternak skala mikro masih menjadi tantangan utama, yang tidak hanya disebabkan oleh ketergantungan pada sumber listrik konvensional tapi juga disebabkan proses inkubasi alamiah yaitu pengeraman menggunakan induk ayam yang kerap tidak mampu menjaga kestabilan suhu dan kelembapan telur secara optimal. Kegiatan pengabdian ini bertujuan memperkenalkan dan meningkatkan pemahaman peternak mengenai teknologi inkubator cerdas berbasis energi surya (PLTS). Metode: Program dilaksanakan dengan pendekatan kolaboratif partisipatif melalui kegiatan diseminasi pengetahuan, demonstrasi/simulasi serta evaluasi yang disertai pendampingan pada peternak selama satu siklus penetasan. Hasil: Hasil evaluasi menunjukkan keberhasilan kegiatan ini, yang dijunjukkan oleh kemampuan inkubator dalam mempertahankan suhu pada kisaran optimal 37-38 0C dan kelembapan 55-60 % sehingga mencapai tingkat keberhasilan penetasan sebesar 76%, serta meningkatkan rata-rata pemahaman peternak sebesar 30 poin. Kesimpulan: Kegiatan diseminasi teknologi inkubator cerdas berbasis PLTS berhasil memperkuat kapasitas pengetahuan dan ketrampilan peternak dalam manajemen penetasan dan menjadi solusi inovatif yang tepat guna untuk mendukung produktivitas penetasan dan kemandirian energi peternak ayam skala mikro.
Co-Authors Ahmad Fudholi Al-Rasyid, Johansyah Alkausar, Muhammad Fajri Amperawan Amperawan Anggraini, Citra Auliya, Annisa Azhar, M. Sayid Bambang, Muhammad Refo Bhakti Yudho Suprapto Citra Anggraini Dadi Setiadi Daniesar, Muhammad Nouval Destri Zumar Sastiani Dewi, Tresna Dewi, Tresna Dewi Dicky Astra Yudha Edo Triyandi Evelina Ginting Hendra Marta Yudha Husni, Nyayu Latifah Juwita, Aulia Ratna Liwijaya, Angga Lukman Nul Hakim M. Nawawi Mardiyati, Elsa Nurul Mayastri Devana Muhammad Dede Yusuf Muhammad Nawawi Muhammad Ridho Kenawas Muhammad Taufik Roseno Mulya, Zarqa Muslikhin Nawawi, M. Neta Larasati Noer, Mohammad Nawawi Nur Aina Okta Ferrisa Pola Risma Pratama, Yudha Wira Putri Repina Kesuma Rahman, Raihan Aldiaz Rapli Wijaya RD Kusumanto RD Kusumanto Rinaldi Rinaldi Riyo Irawan Ronald Sukwadi Rusdianasari Rusdianasari Sakuraba, Takahiro Sastiani, Destri Zumar SELAMET MUSLIMIN Septiyani AR, Dini Siproni Umar Siti Afiyah Qatrunnada Solly Aryza Sri Rezki Artini Tresna Dewi Tresna Dewi Tresna Dewi Tulak, Windy Gafrila Wahju, Marsellinus Bachtiar Windy Gafrila Tulak Yahya, M. Amri Yolanda Eka Pratiwi Yudha Wira Pratama Yudi Wijanarko, Yudi Zainuddin Nawawi Zarqa Mulya