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Yulisda, Desvina
Universitas Malikussaleh
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Journal : JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING

 1 
Performance Evaluation of Augmented Reality-Based Smart Farming for Rice and Corn Pest Detection Faridhatul Ulva, Ananda; Yulisda, Desvina; Baidhawi, Baidhawi; Nurhasanah, Nurhasanah
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 9 No. 2 (2026): Issues January 2026
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v9i2.16996

Abstract

An Augmented Reality application for detecting pests and diseases in rice and corn has been developed to overcome the limitations of visual identification in the field, which still relies on subjective interpretation by users. This system utilises image processing and AR overlay based on smart farming to classify symptoms in real time, improving the precision of diagnosis and consistency in control decision-making. This study aims to design, implement, and evaluate the performance of an augmented reality (AR)-based smart farming system for the visual and interactive detection of pests and diseases in rice and corn crops. The research method uses an evaluative approach by assessing the performance of the Augmented Reality system in the field based on detection accuracy, operational reliability, and the suitability of the results to the predetermined performance indicators. Testing was conducted in Gampong Releut Barat, Dewantara District, North Aceh. The results showed that pest and disease detection accuracy increased from 42.4% to 66.7%, with a system response time of <2 seconds, accompanied by an 18% reduction in crop damage and a 24% increase in productivity, confirming the reliability of the system for field diagnosis. This achievement is significant because it meets the operational performance threshold for smart farming and demonstrates the system's readiness for adoption as an Augmented Reality-based decision support tool at the farmer level. The research conclusion indicates that Augmented Reality-based smart farming has the potential to improve detection accuracy, control efficiency, and crop productivity as a support for precision agriculture and sustainable village food security.
Co-Authors -, Badriana -, Bakhtiar Agam Muarif Agus Adi Nursalim Ahmad Fikri Ahmad Fikri Ahmad Fikri Ahmad Nayan Akbar, Anggi Rizki Al Kautsar Aidilof, Hafizh Alfarizi, Reza Amalia, Nabila Ananda Faridhatul Ulva Andik Bintoro Angga Pratama Angga Pratama Apriani Riski Ar Razi Ar Razi Ashari, Muhammad Rayhan Aulia, Rika Baidhawi Baidhawi Balqis Yafis Chairil Anwar Cut Aura Putri K.D Dahlan Abdullah Dedi Fariadi Dini Rizki Ebi Putra Eka Susanti Eka Susanti Emi Maulani Eri Saputra Fadhliani, Fadhliani Fajar, Mutiara Febriandirza, Arafat Habib Muharry Yusdartono Hanif Hanif Himmatur Rijal Hisyam Maulana Hadi Hussain, Azham Ida Ayu Putu Sri Widnyani Iswadi Iswadi Kamila, Raisya Khairul Anshar Khairul Anshar Kurniawati Kurniawati Kurniawati Laila, Dwi Nur'aini Marina Marina Maulida, Fika Melani, Siska Amelia Muhammad Aufa Aslami Muhammad Fauzan MUHAMMAD HABIB Muhammad Ikhwani Mukti Qamal Muliana, Erna Mulyawan, Rizka Munirul Ula Mutammimul Ula Muthmainnah Muthmainnah Muthmainnah Muthmainnah Mutiara Fajar Muzakir Nur Nita, Erlija Nosari, Yulia Nurdin Nurdin Nurfasha , Salsa Nurhasanah Nurhasanah Nurlaila, Rizka Nurmalita Nurmalita Nurul Hayati Harahap Perdinanta, Gita Rafika Rafika Rahayu Rahayu Rahma Fitria Rahma Fitria, Rahma Rahma, Hilmia Rahmah, Chatrine Aulia Razi, Ar Razif, Razif Reza Putra Rizka Mulyawan Rizki Setiawan Rizki, Dini Rizky Putra Fhonna Sahputra, Ilham Salsa Nurfasha Salwan, Defri Sayed Fachrurrazi Sri Wilujeng Susanti Susanti Syakhila, Amanda Syamsul Bahri Sylvie Anastasya Utami Tarigan, Anjasmara Teguh Gunawan Veri Ilhadi Zulnazri, Z Zurhijjah Zurhijjah