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Subarkah, Pungkas
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Journal : Building of Informatics, Technology and Science

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Classification of Rice Plant Disease Image Using Convolutional Neural Network (CNN) Algorithm based on Amazon Web Service (AWS) Anggraini, Nova; Kusuma, Bagus Adhi; Subarkah, Pungkas; Utomo, Fandy Setyo; Hermanto, Nandang
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.5883

Abstract

− In agriculture, rice plays an important role in the Indonesian economy. Rice produces rice, one of the most widely consumed staple food sources in Indonesia. Many factors can cause rice production failure, one of which is leaf pests and diseases. Therefore, early identification and management of plant diseases is an important step in an effort to increase crop yields and ensure food safety. One way to detect rice leaf images early is to perform an image classification process and create a web-based application. The method that has the ability in image processing is deep learning technique with convolutional neural network (CNN) method. The Convolutional Neural Network (CNN) method works to perform and predict diseases in plants by using image categorization or object images. This research aims to apply the web application of image classification of rice plant diseases to the Amazon Web Service (AWS) by identifying and classifying various types of rice leaf diseases using the CNN algorithm, so that farmers can detect rice plant diseases quickly and accurately through image analysis. This application was created using Convolutional Neural Network (CNN) methodology and Software Development Life Cycle (SDLC). The result of this study is that researchers created a web application for the classification of rice plant diseases through leaf images which are divided into 4 categories, namely Healthy, Leaf Blight, Brown Leaf Blight and Hispa, which is made a classification model using CNN with an accuracy value of 0. 8608, then using the streamlit framework to build a website, and utilizing AWS services in the form of Amazon Elastic Compute Cloud (Amazon EC2) as a hosting service, Amazon Simple Storage Service (Amazon S3) as a service for storing rice plant disease classification models and for storing web files, and Amazon Identity and Access Management Role (Amazon IAM) as a service to create a role that gives permission to connect between AWS S3 and AWS EC2. Testing the disease classification model in rice plants implemented on the web in EC2 shows quite good results with an accuracy of 78.5%. This can affect the model's ability to recognize specific disease patterns
Co-Authors Adam Prayogo Kuncoro Adhimah, Laily Farkhah Aditya Permana, Reza Afifah, Erika Luthfi Alifian , Raditya Sani Amin, M. Syaiful Anggraeni, Epri Anggraini, Nova Anshari, Muhammad Rifqi Anunggilarso, Luky Rafi Arief Rachman Hakim Arsi, Primandani Astrida, Deuis Nur Aunillah, Puteri Johar Awal Rozaq, Hasri Akbar Awali, Uston Azhar Andika Putra Azzahra, Delia Oktaviana Bagus Adhi Kusuma Baihaqi, Wiga Maulana Busyro, Muhammad Damayanti, Wenti Risma Darmo, Cahyo Pambudi Dermawan, Riky Dimas Dhanar Intan Surya Saputra Dias Ayu Budi Utami, Dias Ayu Budi Dwi Krisbiantoro, Dwi Elistiana, Khoerotul Melina Fadilah, Alif Nur Fandy Setyo Utomo Firmanda, Reza Arief Hellik Hermawan Hendra Marcos Hendra Marcos, Hendra hidayatulloh, hanif Ikhsan, Ali Nur Ilham, Fatah Irma Damayanti Irma Darmayanti Katiandhago, Bryan Jerremia Khoerida, Nur Isnaeni Khofiyah, Salma Ngarifatul Kholifah Dwi Prasetyo Kartika, Nur Kisma, Atmaja Jalu Narendra Kusuma, Bagus Adhi Kusuma, Velizha Sandy Lestari, Vika Febri Marlita, Reva Merliani, Nanda Nurisya Mohammad Imron Muflikhatun, Siti Mustolih, Akhmad Nandang Hermanto Nasar Ghanim, Nadif Nuraini , Rema Sekar Nurul Hidayati Pramudya, Reyvaldo Shiva Prasetya, Eko Budi Prasetyo Kartika, Nur Kholifah Dwi Prastyadi Wibawa Rahayu Prayoga, Iphang Primandani Arsi Purba, Mariana Ramadani, Nevita Cahaya Riandini, Dini Riyanto Riyanto Rizki Wahyudi Rofiqoh, Dayana Rohman, M. Abdul Romadoni, Nova Salma Rujianto Eko Saputro Sabaniyah, Arbangi Puput Sadewo, Rizki Salsabiela, Ayuni Saputra, Dhanar Sari, Rida Purnama Sarmini Sarmini Satrio Nugroho, Chendri Irawan Septiana Putri, Refida Sugiarti Sugiarti Suhaman, Jali Susanto, Wachyu Dwi Syabani, Amin Syamsiar, Syamsiar Tarwoto, Tarwoto Tri Astuti Triana, Latifah Adi Umma, Rofiqul Utami, Melida Ratna Utomo, Anwar Tri V, Jay Wahyu, Herta Tri WIDI LESTARI, TRI ENDAH Widiawati, Neta Tri Yunita, Ika Romadhoni