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All Journal Bulletin of Electrical Engineering and Informatics Jurnal Teknik Elektro ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika JETT (Jurnal Elektro dan Telekomunikasi Terapan) Emerging Science Journal JMM (Jurnal Masyarakat Mandiri) Jurnal Elektronika dan Telekomunikasi Jurnal ULTIMA Computing TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika Journal of Electronics, Electromedical Engineering, and Medical Informatics JTIM : Jurnal Teknologi Informasi dan Multimedia JMECS (Journal of Measurements, Electronics, Communications, and Systems) Indonesian Journal of Electrical Engineering and Computer Science Charity : Jurnal Pengabdian Masyarakat Proceedings Series on Physical & Formal Sciences Prosiding Konferensi Nasional PKM-CSR Jurnal Ilmiah Teknik Elektro eProceedings of Engineering Buletin Pos dan Telekomunikasi
Fiky Y. Suratman
Universitas Telkom
Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Nursing Public Health Social Sciences Other

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Journal : Emerging Science Journal

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Empoasca Pest Attack Classification on Tea Plantations Using Multispectral Imaging and Deep Learning Kurniawan, Bella K.; Suratman, Fiky Y.; Fauziah, Fani; Vidyaningtyas, Hurianti; Saputri, Desti M.; Pramudita, Aloysius A.
Emerging Science Journal Vol. 9 No. 4 (2025): August
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-04-04

Abstract

This study aims to enhance the management of Empoasca pests in tea cultivation, a critical sector for Indonesia’s economy, by developing an innovative detection method. The challenge of pest infestations may significantly reduce tea production yields, and the misuse of chemical pesticides further compromises tea quality. We propose a novel approach that integrates multispectral imaging with Convolutional Neural Networks (CNN), specifically employing ResNet-50 and AlexNet architectures to accurately detect Empoasca infestations. We begin with the data collection process, followed by the development of the preprocessing model and evaluation of its performance. We classify tea leaves affected by Empoasca pests using spectral data obtained from a multispectral camera operating across Green, NIR (Near Infrared), REG (Red Edge), and RED channels. We evaluated various spectral channels and identified the green spectrum as the most effective for revealing visual characteristics, such as curled leaves associated with Empoasca damage. Experimental results demonstrated that ResNet-50 outperformed AlexNet, achieving a remarkable accuracy of 99% on the green channel, while AlexNet showed notable accuracy declines on other channel combinations. These findings underscore the effectiveness of the green spectrum and the superiority of ResNet-50 in achieving precise pest detection, offering a reliable technological solution for modern tea plantation management.
Co-Authors -, Sugihartono A. A. Pramudita Achmad Rizal Adinda Mutiara Hakim Adriani Rizka Amalia Agung Chrisyancandra Mobonguni Ali Muayyadi Ali, Erfansyah Aloysius Adya Pramudita Alyani Durrah Fauzan Andika Pradana Arif Wicaksono Angga Rusdinar Angga Wijaya Anhar Ari Widodo Aptadarya, Harwin Arentaka, Fiendo Mahendra Argaloka, Aditya Adni Arif Abdul Aziz Arifyandy, Rachmat Ario Wicaksono ARIS HARTAMAN Aurelia, Felicia Bunga Azhar Sukarna Putra Azhar Yunda Ramadhan Azizah Yusrina Bambang Hidayat Bambang Setia Nugroho Budi Permana Dami Mahardiwana Daud, Pamungkas De Fitrah, Figo Azzam Denny Darlis Dharu Arseno Dhiky Wahyu Santoso Dias Daffa Wiwaha Dien Rahmawati Dimas Mustaqim Dwi Esti Kusumandari Ekki Kurniawan Erwin Susanto Estananto Fadhli Rahman Faishal Adli Fani Fauziah, Fani Farhan Ramadhan FARIED IZZANTAMA NUGRAHA HARSWA Figo Azzam De Fitrah Fikry Lazuardi Fitrah, Figo Azzam De Giashinta Larashati Grace Bobby GRACE BOBBY, GRACE Hana Pratiwi Hasbian Fauzi Perdana Heni Pujiastuti Heroe Wijanto Hidayat, Mujib R. HIDAYAT, MUJIB RAMADAN Hurianti Vidyaningtyas I Wayan Oka Krismawan Putra Ig. Prasetya Dwi Wibawa Imam Darmawan Istiqomah Istiqomah istiqomah istiqomah Jody H, Amadeus Evan Junartho Halomoan Juse Wisman Oktabri Kalfika Yani Khalisa Khairuna Khilda Afifah Kirana, Tsania Puspa Koredianto Usman Krisna Muhammad Luthfi Kurniawan, Bella K. Lyra Vega Ugi M. Reza Raihan N.R MAARIF, AHMAD FATHAN Made Indra Wira Pramana Marchellyn, Ferryn Mochammad Haldi Widianto Mohamad Ramdhani Muhamad Ridwan Widyantara Muhamad Riswan Nurfadilah Muhammad Adi Nurhidayat Muhammad Ary Murti Muhammad Hablul Barri Muhammad Hegi Rinaldi Muhammad Nashih Rabbani Muhammad Zakiyullah Romdlony Mujib R. Hidayat Mumtazanisa Fairuzen Nasrullah Armi Neina Oktavia Sariningsih Nelson, Garry Nina Mardiana (F01108057) Nurhidayat, Muhammad Adi Nurul Qashri Mahardika T Nusharatul Lailiyya Nushrotul Lailiyya Patriananda, Teguh Porman Pangaribuan Pramudita, A. A. Pramudita, Aloysius A. PRATIWI, HANA Qolbiyah, Nada Syifa Rachmita Hasni.H1 Radika Gitatama Rahmad Rahmad Ramadhan, Azhar Yunda Ramdhan Nugraha Ratri Dwi Atmaja Rebecca Chittra Widyaparamitha Reyhan Fahmirakhman Abdullah Reynaldo Sandy Montolalu Reza Nurul Fajri Rheza Faurizki Rahayu Rifqy Miftahul Hidayat Rissa Rahmania Rizal Akhlaqul Rizki Ardianto Priramadhi Rizkia Dwi Auliannisa Rizky Ardianto Priramadhi Salwa Nur Rohmah Santosh Poudel Saputri, Desti M. Sari, Nurlina Satyawan , Arief Suryadi Satyawan, Arief Suryadi Seno Nugroho Siburian, Sebastian Edward Slamet Widodo Slamet Widodo Sony Sumaryo Sugihartono - Suputra , Mahesa Wisnu Suryo Adhi Wibowo Unang Sunarya Widyantara, Muhamad Ridwan Y. R, Azhar Yohana Jayanti Aruan Yudha Purwanto Yudha Setyawan, Raden Rofiq Zahwa Rizzi Ani