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All Journal IAES International Journal of Robotics and Automation (IJRA) Jurnal Terapan Abdimas JOIV : International Journal on Informatics Visualization BAREKENG: Jurnal Ilmu Matematika dan Terapan Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Teknologi Informasi dan Terapan (J-TIT) Journal of Information Systems and Informatics Jurnal Daya Mas : Media Komunikasi dan Informasi Hasil Pengabdian dan Pemberdayaan Masyarakat Pilar Teknologi : Jurnal Penelitian Ilmu-ilmu Teknik Journal of Computer and Information Systems Ampera Jurnal Pengabdian pada Masyarakat Ilmu Pengetahuan dan Teknologi Terintegrasi Journal of Information Systems and Technology (JISTech) TENANG : Teknologi, Edukasi, dan Pengabdian Multidisiplin Nusantara Gemilang International Journal of Artificial Intelligence and Science Journal Information System and Computer Application Jurnal Nasional Teknologi Informasi dan Aplikasinya
Pradityo Utomo
Unknown Affiliation
Humanities Automotive Engineering 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 Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Yolo-Drone: Detection Paddy Crop Infected Using Object Detection Algorithm Yolo and Drone Image Masykur, Fauzan; Prasetyo, Angga; Zulkarnain, Ismail Abdurrozaq; Kumalasari, Ellisia; Utomo, Pradityo
JOIV : International Journal on Informatics Visualization Vol 9, No 5 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.5.3472

Abstract

Crop failure is an undesirable result of rice planting for every farmer because it disrupts the economic stability of the family. One of the factors of crop failure in the rice planting process is the disease attack factor, which causes infection. Infected plants will interfere with the growth of rice, not optimally, because the green leaf substance, which is key to processing sunlight's nutrients, is unable to function. After all, it is covered by infection. Infection in the leaves covers the green leaf substance, or chlorophyll, so that the leaves are unable to absorb nutrients from sunlight. This problem is a separate concern in overcoming rice plant infections, which will result in crop failure. This paper discusses the detection of infected rice plants, particularly leaf infections, using drone camera images. Unmanned aircraft, also known as drones, fly above rice fields to capture images of rice plants, which are then used as datasets in training models to detect infected and healthy rice plants. The detection of disease presence in rice leaves is carried out using the You Only Look Once version 8 (YOLOv8) object detection algorithm, with a model trained using Google Colab Pro+. The results of training the model to detect healthy and infected plant leaves are the primary objectives of this study. The YOLOv8 object detection model, when applied to detect rice plants with two classes (healthy and infected), shows quite good results. This is indicated by the recall, precision, and F1-score values (0.99, 0.814, 0.90) approaching 1 in all classes.
Web-Based Electric Bicycle Fault Diagnosis Using the Backward Chaining Method Nugroho, Satrio Wicaksono; Dwi Nor Amadi; Pradityo Utomo; Candra Budi Susila
International Journal of Artificial Intelligence and Science Vol. 2 No. 2 (2025): September
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/IJAIS.v2i2.35

Abstract

This study aims to develop a web-based expert system for diagnosing electric bicycle faults using the backward chaining method. It addresses the limitation of previous systems that did not support user input of fault hypotheses. The research stages include literature review, data collection (31 faults and 5 symptoms), implementation of web-based inference, and black box testing. The results demonstrate that the system successfully accommodates user-input hypotheses and related symptoms, then matches them with rules to generate diagnoses. Functional testing confirms all features operate as intended. The research novelty lies in: (1) the first comprehensive knowledge base for electric bicycles (31 faults), (2) an interactive web interface supporting hypothesis input, and (3) dynamic database storage for rule updates.
Rancang Bangun Sistem Pendukung Keputusan untuk Pemilihan Tema Tugas Akhir Mahasiswa Manajemen Informatika Universitas Merdeka Madiun Pinaring Gusti, Alexander Kenzy; Utomo, Pradityo; Sukadi
MEKAR : Journal Information System and Computer Application Vol. 1 No. 1 (2025): AGUSTUS
Publisher : PT Mekar Research and Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65475/nx70d190

Abstract

Abstract: - Students in the Informatics Management Study Program at Universitas Merdeka Madiun must complete a Final Project (TA) as part of their graduation requirements. However, choosing a project topic that matches their interests and abilities can be difficult. To help solve this problem, a web-based Decision Support System (DSS) was developed using the Weighted Sum Model (WSM). This study focuses on designing and developing a system to assist students in selecting appropriate final project topics more efficiently and objectively. The WSM method is used to assess several theme options based on a set of established criteria. The system was built using the Waterfall development model, which involves analysis, design, implementation, testing, and maintenance stages. Black Box Testing was conducted to verify the system's functionality. The application supports two user roles: administrators and students. Administrators manage the system’s data, including criteria, theme options, evaluations, and user accounts. Students can view recommended project topics and update their profiles. Testing showed a 100% success rate, indicating the system’s reliability. By using this DSS, students can make more informed decisions about their final project themes, improving both the selection process and the overall quality of their research through the use of educational technology.
Selection of the Best Futsal Player at the Bhirawa Cup Event Using the Simple Multi Attribute Rating Technique Method Fatah, Arjulian; Utomo, Pradityo; Susila, Candra Budi
International Journal of Artificial Intelligence and Science Vol. 2 No. 2 (2025): September
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/IJAIS.v2i2.40

Abstract

The selection of the best futsal player is an important aspect of a tournament, as it can motivate athletes to continuously improve their performance. However, manual selection processes tend to be subjective and prone to bias, thus reducing the objectivity of the assessment results. This study aims to design and develop a web-based decision support system using the Simple Multi-Attribute Rating Technique (SMART) method to assist the organizing committee in objectively and standardizedly evaluating player performance at the Bhirawa Cup 2024 futsal event. The research method used is the Waterfall software engineering model, which consists of the stages of requirements analysis, system design, implementation, testing, and maintenance. The system evaluates player performance based on four main criteria: contribution to the team, number of fouls, attitude, and leadership, each of which is assigned a weight according to its level of importance. The result of this study is a web-based decision support system that can be used by the event committee to assess and determine the best player. The strength of this system lies in its ability to present structured data and minimize assessment subjectivity. A suggestion for future development is to make the system accessible online to increase its flexibility
Prototype Aplikasi Edukasi Cyberbullying Berbasis Mobile Android Fiki Nur Rahman; Shendy Aditayahya Wardana; Pradityo Utomo
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 1 No. 4 (2023): JNATIA Vol. 1, No. 4, Agustus 2023
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2023.v01.i04.p01

Abstract

As technology develops rapidly, it has not only positive but also negative impacts; one of the negative impacts is the case of cyberbullying. Cyberbullying is an unpleasant action towards other people on the internet. One way to reduce cyberbullying is to create educational applications about cyberbullying. This application will provide an explanation of what cyberbullying is and how to prevent cyberbullying by providing an explanation that is light and easy to understand. This application is based on Android mobile, so it can more easily reach more users, using Java programming and display design using figma. 
Clustering Analysis for Green Economy and Citizens-Based Social Forestry Business Development Model Utomo, Pradityo; Amadi, Dwi Nor; Setiahadi, Rahmanta
Jurnal Teknologi Informasi dan Terapan Vol 12 No 2 (2025): December
Publisher : Jurusan Teknologi Informasi Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/jtit.v12i2.463

Abstract

This study aims to prove that clustering analysis can optimize the development model of social forestry businesses based on green economy and citizens. Clustering analysis can use machine learning methods. Some of these methods are K-Means and K-Medoids. First, the research data was obtained from the assessment results of forest edge residents. Residents assessed 13 green economy variables. The social forestry business development model based on green economy and citizens requires labeled data. Therefore, this study compares the performance of K-Means and K-Medoids to cluster the assessment data of forest edge residents. To determine its performance, this study uses three variations of k values, namely K = 4, K = 8, and K = 12. Performance testing uses the Davies Bouldin Index (DBI) method and computation time. Based on Davies Bouldin test, K-Means method is better than K-Medoids at K = 4, but K-Medoids method is better than K-Means at K = 8 and K = 12. Based on computation time test, K-Means method is better than K-Medoids. Based on this test, K-Means method is more suitable for big data and fast computing time.
Co-Authors Andreas Rendiana Sulistyana Angga Prasetyo Arief Budiman Atina, Vihi Bimantara, Eka Bayu Bimantara, Eka Bayu Candra Budi Susila Chatarina Umbul Wahyuni Dede Sopiandy Eka Bayu Bimantara Eka Bayu Bimantara Ellisia Kumalasari Esti Suryani Ezra Gayu Fatah, Arjulian Fauzan Masykur Fiki Nur Rahman Gayu, Ezra Johar Nur Iin Joko Triono Muh Nurtanzis Sutoyo Murhaban Murhaban Nor Amadi, Dwi Nugroho, Satrio Wicaksono Pinaring Gusti, Alexander Kenzy Putri, Della K. Rahman, Fiki Nur Rendrarini, Diana Sapriyadi Seno Aji Setiahadi, Rahmanta Setiyo Daru Cahyono Shendy Aditayahya Wardana Sihwi, Sari W. SRI RAHAYU Sukadi Sulistyana, Andreas Rendiana Tomi Tristono Umi Salamah Wahyuddin Wardana, Shendy Aditayahya Wiharto Wiharto Yayi Suryo Prabandari Zulkarnain, Ismail Abdurrozaq