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I Made Budi Suksmadana
Universitas Mataram
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Implementasi Deteksi Penyakit Tanaman Menggunakan Aplikasi Harvest Scan Berbasis Analisis Visual dengan Integrasi Cloud Computing Erna Wati; I Made Budi Suksmadana
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 7, No 6 (2024): Desember 2024
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v7i6.8292

Abstract

Abstrak - Cloud computing memainkan peran penting dalam mendukung aplikasi Harvest Scan untuk deteksi penyakit tanaman melalui analisis visual. Dengan memanfaatkan teknologi ini, Harvest Scan memproses dan menyimpan data gambar tanaman secara efisien, memungkinkan analisis kesehatan tanaman dan memberikan rekomendasi perawatan secara real-time kepada pengguna. Hasil uji menunjukkan akurasi deteksi sebesar 75%, yang membuktikan kemampuan aplikasi dalam mengenali dan mengklasifikasikan berbagai masalah tanaman secara cepat dan tepat. Teknologi cloud mendukung pengelolaan data skala besar dan pemantauan kondisi tanaman berkelanjutan, memberikan solusi praktis dan tepat waktu bagi petani untuk meningkatkan produktivitas dan kualitas hasil pertanian. Studi ini mengkaji bagaimana integrasi cloud computing dalam Harvest Scan mempercepat proses deteksi dan meningkatkan akurasi diagnosis, serta membahas tantangan dan manfaat implementasinya di sektor pertanian.Kata kunci: Kesehatan tanaman, deteksi penyakit, teknologi pertanian, analisis gambar, dan Harvest Scan.  Abstract  - Cloud computing plays a crucial role in supporting the Harvest Scan application for plant disease detection through visual analysis. By leveraging this technology, Harvest Scan efficiently processes and stores images of plants, enabling health analysis and providing real-time care recommendations to users. Test results indicate a detection accuracy of 75%, demonstrating the application's ability to quickly and accurately recognize and classify various plant issues. Cloud technology supports the management of large-scale data and continuous monitoring of plant conditions, providing practical and timely solutions for farmers to enhance productivity and the quality of agricultural yields. This study examines how the integration of cloud computing in Harvest Scan accelerates the detection process and improves diagnostic accuracy, while also discussing the challenges and benefits of its implementation in the agricultural sector.Keywords: Plant health, disease detection, agricultural technology, image analysis, and Harvest Scan.
Co-Authors A. Sjamsjiar Rachman Agil Maulana Nanda Riady Bagus Widhi Dharma S. Bulkis Kanata Cipta Ramadhani Danar Hadi Bachtiar Erna Wati Giri Wahyu Wiriasto I Ketut Wiryajati I Made Ary Swantika I Made Ginarsa I Nengah Suhartawan I Nyoman Wahyu Satiawan Ida Ayu Sri Adnyani Ida Bagus Fery Citarsa Ida Bagus Fery Citarsa Ida Bagus Fery Citarsa Ida Rofaida Indira Puteri Kinasih M. Laylul Mustagfirin Ni Made Seniari Paniran Paniran Supriono . Supriono Supriono Supriono Supriono Supriono Supriono Supriono Supriyatna Supriyatna Warindi D