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All Journal Journal of Information Systems and Informatics Jurnal Nasional Ilmu Komputer Klik - Jurnal Ilmu Komputer Dikdimas : Jurnal Pengabdian Kepada Masyarakat
Oktarina, Serly
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Education Engineering Law, Crime, Criminology & Criminal Justice Nursing Social Sciences

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Journal : Journal of Information Systems and Informatics

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Comparing CNN Models for Rice Disease Detection: ResNet50, VGG16, and MobileNetV3-Small Roseno, Muhammad Taufik; Oktarina, Serly; Nearti, Yuwinti; Syaputra, Hadi; Jayanti, Nirmala
Journal of Information System and Informatics Vol 6 No 3 (2024): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i3.865

Abstract

The Oryza sativa (rice) plant is an important staple food source, especially in the Asian region. Rice production is often disrupted by diseases such as Brown Spot, Leaf Scald, Rice Blast, Rice Tungro, and Sheath Blight, which can reduce yield and crop quality. This research aims to classify rice plant diseases using a deep learning approach with Convolutional Neural Networks (CNN) architecture, namely ResNet50, VGG16, and MobileNetV3-Small. The dataset used is Rice Leaf Disease Classification which consists of 1305 images with five disease labels. The data is divided into training, validation, and testing sets with proportions of 70%, 15%, and 15%. The results showed that the MobileNetV3-Small model provided the best accuracy on the test data of 79%, while VGG16 achieved the validation accuracy of 78.84%. Based on these results, MobileNetV3-Small is considered the most superior model for rice disease classification. This research shows the great potential of applying deep learning in automatic rice disease detection.
Development of a Digital Village Concept based on Information Technology Infrastructure and Strategy Management to Facilitate SPBE Ogan Ilir Regency Oktarina, Serly; Roseno, Muhammad Taufik; Ubaidillah, Ubaidillah; Antoni, Darius; Zahro, Lailatuz; Syaputra, Hadi
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.875

Abstract

Technology in the digital era is currently progressing very rapidly. This is marked by the increasingly massive number of social media users in everyday life. Survey results from the Indonesian Internet Service Providers Association (APJII) in 2022 recorded that the number of internet users in Indonesia reached 196.7 million people. This number increased by 23.5 million or 8.9% compared to 2018. With information technology and the internet, information is now becoming more easily spread and can be accessed by all levels of society thanks to the internet, not just people in urban areas, but people living there. in rural areas too. The Ogan Ilir Regency Government initiated information technology infrastructure including village internet or Digital Village to solve the problem of inequality in digitalization of society in rural and urban areas. Development and implementation of a digital village is a program that implements electronic-based government system (SPBE) services to the community and empowers the community based on the use of technology. This research aims to conduct a survey of information technology infrastructure to identify village potential, marketing and accelerating access and public services. Apart from that, this research also identifies digital-based life patterns of people in rural and urban areas, as well as to advance economic development in rural areas to improve SPBE services in Ogan Ilir Regency. The method used is a quantitative method for surveying and mapping the use of information technology in villages and ultimately producing the concept of an independent digital village. Research data was obtained from surveys and FGDs with the Ogan Ilir district government, village heads, village communities and micro, small and medium enterprises. Meanwhile, secondary data will be obtained through the results of MSME and village profiles from the Central Statistics Agency.
Co-Authors Ahmadi, Zahra Antoni, Darius Ariska, Dempi Aryo P, Anggoro Daniel Udjulawa Diah Triesia Dwipa, Ruswa Emilia Emilia Hermansyah Hermansyah Jaka Pangestu, Muhammad Jayanti, Nirmala Khoirulloh, Muhammad Hadi Muhammad Iqbal Muhammad Taufik Roseno, Muhammad Taufik Nearti, Yuwinti Ramadhani, Zahra Roseno, M. Taufik Siti Zubaidah SRI RAHAYU Supratman, Edi Syaputra, Hadi Teisnajaya, Usep Ubaidillah Ubaidillah Zahro, Lailatuz