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All Journal MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Jurnal Buana Informatika Jurnal Transformatika Proceeding of the Electrical Engineering Computer Science and Informatics JOIN (Jurnal Online Informatika) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) SemanTIK : Teknik Informasi Jurnal CoreIT IT JOURNAL RESEARCH AND DEVELOPMENT Indonesian Journal of Artificial Intelligence and Data Mining Techne : Jurnal Ilmiah Elektroteknika JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Compiler MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Sistem Cerdas Applied Technology and Computing Science Journal JISKa (Jurnal Informatika Sunan Kalijaga) Jurnal Teknologi Informasi dan Terapan (J-TIT) International Journal of Informatics and Computation Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Jurnal Informatika dan Rekayasa Perangkat Lunak Respati Letters in Information Technology Education (LITE) Jurnal Teknik Informatika (JUTIF) Teknika Jurnal Computer Science and Information Technology (CoSciTech) Prosiding Seminar Nasional Sains Teknologi dan Inovasi Indonesia (Senastindo) Jurnal Ilmu Komputer dan Teknologi (IKOMTI) Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC) International Journal of Informatics Engineering and Computing
Mohammad Diqi
Universitas Respati Yogyakarta
Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Library & Information Science Mechanical Engineering Social Sciences Other

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Journal : International Journal of Informatics and Computation

 1 
Implementation of CNN for Plant Leaf Classification Mohammad Diqi; Sri Hasta Mulyani
International Journal of Informatics and Computation Vol 2 No 2 (2020): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v2i2.28

Abstract

Many deep learning-based approaches for plant leaf stress identification have been proposed in the literature, but there are only a few partial efforts to summarize various contributions. This study aims to build a classification model to enable people or traditional medicine experts to detect medicinal plants by using a scanning camera. This Android-based application implements the Java programming language and labels using the Python programming language to build deep learning applications. The study aims to construct a deep learning model for image classification for plant leaves that can help people determine the types of medicinal plants based on android. This research can help the public recognize five types of medicinal plants, including spinach Duri, Javanese ginseng, Dadap Serep, and Moringa. In this study, the accuracy is 0.86, precision 0.22, f-1 score 0.23, while recall is 0.2375.
Design and Building Javanese Script Classification in The State Museum of Sonobudoyo Yogyakarta Mohammad Diqi; Mujastia Muhdalifah
International Journal of Informatics and Computation Vol 1 No 2 (2019): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v1i2.18

Abstract

The Sonobudoyo State Museum is one of the state museums in Yogyakarta where stores historical objects like the Javanese script. This Javanese script presents in street names, especially in the city of Yogyakarta to represent local content for elementary, middle, and high schools. To read and understand Javanese script, people must learn it within a specified period, whereas with Latin letters are easier and faster to understand. The purpose of this paper is to design and build a Javanese script classification dataset to attract both adults, children, and parents as effective learning media. We construct the dataset by using Deep Learning with the Convolutional Neural Network (CNN). Stages of making a dataset are input data, the process of building models, and training can then recognize Javanese script images. We collect the dataset from the internet and several different people to train computer machines. In this paper, we construct the Javanese script classification dataset to help users to detect Javanese characters. The results of this training the application of Javanese script classification can produce a certain level of recognition of Javanese script patterns in a real application.
Co-Authors Ahmad Wakhid Ariani, Rahayu Cahya Arum Kurnia Sulistyawati Arum Kurnia Sulistyowati Azijah, Izattul Bagus Subekti Nuswantoro Basuki, Umar Dian Rhesa Rahmayanti Dyan Avando Meliala Eka Damayanti Elisabeth Deta Lustiyati Ema Utami Erizal Erizal Farida Nur Aini Fathinah, Azzah FAUZIYYAH, ANNUR Ferry Wahyu Wibowo HAFIZAH, IDA Hamzah Hamzah Hamzah Hasta Mulyani, Sri Hidayatulloh, M. Riyan Husna Arwa Salsabil I Wayan Ordiyasa Ikhwan Mustiadi Indra Listiawan Jelina Imlabla Junia Sipit, Marselina Kristian, Tadem Vergi Kusrini Kusrini Lestari, Sri Listiawan, Indra Marselina Endah Hiswati Martin, Benedicto Reynaka Filio Meliala, Dyan Avando Mujastia Muhdalifah Noverianus, Noverianus nur aini, farida Ordiyasa, I Wayan Putra Wanda Putra Wanda, Putra Romana Herlinda Sahal, Ahmad Salsabela, Marcella Sri Hasta Mulyani Sri Lestari Sriwidodo B, Sriwidodo Subandi, Yeyen Sugeng Winardi Suwarto Suwarto Syafitri, Endang Nurul Syihab, Namira Anjani Rahmadina Wandani, Aulia Fadillah Wani Widyaningrum, Rini Wijaya S, R Nurhadi Wijaya Sugiarto, R. Nurhadi Wijaya, Nurhadi Wiratma, Harits Dwi Zaidir