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All Journal Jurnal Informatika JURNAL SISTEM INFORMASI BISNIS TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Sarjana Teknik Informatika JUITA : Jurnal Informatika Jurnal Aplikasi Bisnis dan Manajemen (JABM) E-Journal Jurnal Teknologi dan Sistem Komputer Indonesian Journal of Information System JITK (Jurnal Ilmu Pengetahuan dan Komputer) JMM (Jurnal Masyarakat Mandiri) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan ILKOM Jurnal Ilmiah MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal GERVASI: Jurnal Pengabdian kepada Masyarakat INSIST (International Series on Interdisciplinary Research) Jurnal Informatika Global Jurnal Teknologi Terpadu bit-Tech Jurnal Abdimas Mandiri Indonesian Journal of Electrical Engineering and Computer Science Reswara: Jurnal Pengabdian Kepada Masyarakat Teknosains : Jurnal Sains,Teknologi dan Informatika Journal of Computer Networks, Architecture and High Performance Computing Idealis : Indonesia Journal Information System Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Indonesian Community Journal Jurnal Teknologi Sistem Informasi Jurnal INFOTEL SISFOTENIKA
Rendra Gustriansyah
Universitas Indo Global Mandiri, Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Journal : Jurnal Teknologi Terpadu

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Klasifikasi Penyakit Daun Pisang menggunakan Convolutional Neural Network (CNN) Pratama, M Duta; Gustriansyah, Rendra; Purnamasari, Evi
Jurnal Teknologi Terpadu Vol 10 No 1 (2024): Juli, 2024
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v10i1.1167

Abstract

Bananas are a fruit with promising economic value in Indonesia. They are an essential commodity for farmers, but diseases affecting banana plants can harm their livelihoods. Banana diseases initially attack the leaves, and in the early stages, they are difficult to differentiate with the naked eye due to farmers’ limited knowledge of pathogens. This research utilized the Convolutional Neural Network (CNN) method with transfer learning assistance using Google Colab to facilitate the classification of banana leaf diseases. The trained model experienced overfitting, so regularization was applied using dropout. The best model achieved an accuracy of 92%, precision of 92%, sensitivity of 91%, and an F1-score of 91% at a 70:20:10 ratio on epoch 80, as evaluated and validated using a confusion matrix. This study produced a reliable model for classifying banana leaf disease.
Co-Authors Ade Fathurahman Adhe Suryani Agung Prakesakwa Ahmad Sanmorino Ahmad Sanmorino Amalia, Marshanda Aminuyati Andri Agus Agus S Antony, Fery Ariati, Nining Arief Ramadhan Cahyani, Septa Dana Indra Sensuse Darius Antoni Desfourtheen, Rinda Destria, Abel Dewi Sartika DEWI SARTIKA Dhamayanti Dhamayanti Dhamayanti, Dhamayanti Ditho Hersilava Dwi Asa Verano Ermatita - Febrianty Fery Antony Fery Antony Filian Falanda Hartini Hartini Hartini Hartini Hastha Sunardi Haversyalapa, Ditho Isabella, Isabella Juhaini Alie Kris, Via M. Ricky Hikmawan Megat Norulazmi Megat Mohamed Noor Mitha Sofiana Muhammad Farhan Nadia Damayanti Nazori Suhandi Nazori Suhandi Pratama, M Duta Purbasari, Nadira Putri Purnamasari, Evi Reza Iman Pribadi Rudi Heriansyah Ryan Ramanda Putra Sari, Nursella Sartika, Dewi Shinta Puspasari Shinta Puspasari Shinta Puspasari Suryati Suryati Suryati Suryati Terttiaavini, Terttiaavini Verano, Dwi Asa Wilza Nadia Wiyanto, Ari Zulkifli Zulkifli