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All Journal IPTEK The Journal for Technology and Science CommIT (Communication & Information Technology) ComTech: Computer, Mathematics and Engineering Applications International Journal of Computer Science and Humanitarian AI
Widodo Budiharto
Bina Nusantara University
Humanities Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Mathematics

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Journal : International Journal of Computer Science and Humanitarian AI

 1 
Development of Telegram-Based Home Automation and Data Acquisition System Widodo Budiharto; Heri Ngarianto
International Journal of Computer Science and Humanitarian AI Vol. 1 No. 1 (2024): IJCSHAI
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/ijcshai.v1i1.12030

Abstract

Home automation and data acquisition system using Telegram application makes us able to automate tasks related to control and monitoring through a system installed at home or building. In this research, we propose an algorithm and architecture used for Telegram-based home automation and data acquisition with environmental sensors such has temperature, humidity, CO2, and Volatile Organic Compounds (VOC) measurement (air quality) as indicator of good air quality. Based on experiment, we can detect the condition of environment, control the relay and the system able to give information about the quality of air from smartphone.
Editorial, Foreword, and Table of Content Widodo Budiharto
International Journal of Computer Science and Humanitarian AI Vol. 1 No. 1 (2024): IJCSHAI
Publisher : Bina Nusantara University

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The Framework of Vehicle Detection and Counting System for Handling of Toll Road Congestion using YOLOv8 Widodo Budiharto; Heri Ngarianto
International Journal of Computer Science and Humanitarian AI Vol. 2 No. 1 (2025): IJCSHAI
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/ijcshai.v2i1.13020

Abstract

The Global COVID-19 pandemic and the increasing number of vehicles have exacerbated traffic congestion, particularly in developing countries. In Jakarta, Indonesia, congestion on toll roads is a significant issue that needs to be addressed through an Intelligent Transportation System (ITS). One of the key solutions proposed is vehicle detection and traffic prediction on toll roads. This study introduces a computer vision-based approach utilizing YOLOv8 to detect, track, and count vehicles to predict traffic congestion. The system operates by identifying vehicles (cars and trucks), preprocessing the data, and calculating the total number of vehicles within the camera’s range. If the vehicle count surpasses the threshold set by the toll road provider, the system updates the traffic status (normal or congested) and triggers a warning. The vehicle detection system can identify cars and trucks within a range of up to 150 meters. Experimental results using test videos demonstrate that the YOLOv8-based system achieves an accuracy of 98% with an average detection speed of 83.6 milliseconds, ensuring highly efficient performance. With its high accuracy and speed, this system can be effectively integrated into traffic management solutions to alleviate congestion and enhance transportation efficiency in Jakarta.
Editorial, Foreword, and Table of Content Widodo Budiharto
International Journal of Computer Science and Humanitarian AI Vol. 2 No. 1 (2025): IJCSHAI
Publisher : Bina Nusantara University

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Design and Implementation of Chatbot Pancasila for Teaching Pancasila and Character Building for University’s Students Karina Dwinovera Mulia; Widodo Budiharto; Heri Ngarianto; Frederikus Fios
International Journal of Computer Science and Humanitarian AI Vol. 2 No. 2 (2025): IJCSHAI
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/ijcshai.v2i2.14418

Abstract

In the modern era, where global influences are rapidly shaping young minds, the need to maintain strong national identity and moral values is more crucial than ever. For Indonesian students, Pancasila education and character building play a central role in developing not only academic competence but also personal integrity and social responsibility.  The design approach involved analyzing student needs, integrating Pancasila-based content, as well as applying automated learning algorithms so that the chatbot can provide answers that match the context of the conversation especially Character-Building Pancasila topics. This Pancasila Character Building Chatbot is designed with Natural Language Processing (NLP) technology to provide creative, interactive, and interesting learning experiences that are easily understood by students. Implementation is done through a digital platform that allows students to interact in real-time in understanding the values of Pancasila, such as divinity, humanity, unity, democracy, and social justice. Furthermore, this innovation aims to bridge the gap between traditional moral education and modern digital learning methods. By utilizing artificial intelligence, the chatbot can adapt to different learning styles and provide personalized feedback to each student. It is hoped that the presence of Chatbot Character Building Pancasila can increase the enthusiasm for learning and curiosity of students so that learning character building Pancasila is more creative and interesting for students in university classrooms.
Obstacle Avoidance Method using Stereo Camera for Autonomous Robot Nabeel Kahlil Maulana; Widodo Budiharto; Hanis Amalia Saputri
International Journal of Computer Science and Humanitarian AI Vol. 2 No. 2 (2025): IJCSHAI
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/ijcshai.v2i2.14617

Abstract

This paper presents the development and implementation of an obstacle avoidance system for an autonomous robot using a stereo camera setup. The system enables the robot to navigate its environment safely by identifying obstacles and making real-time movement decisions based on depth perception. The stereo vision configuration allows the robot to estimate distances through disparity computation and polynomial linear regression modeling. The proposed algorithm performs stereo matching, image rectification, and depth estimation to generate disparity maps representing obstacle distances. The robot uses this information to figure out if the items it sees are close, medium, or far away, and then it chooses the right move, such stopping, turning left, or turning right. The robot can find and avoid obstacles in different indoor settings, as shown by the experimental findings. The regression model employed for depth estimation attained a high degree of accuracy, evidenced by a R² value of 0.97 and a minimal mean absolute error, signifying robust reliability in distance prediction. The research validates that the amalgamation of stereo vision with regression-based distance estimate yields a resilient and economical method for autonomous navigation. This study advances the ongoing evolution of intelligent robotic systems that can execute autonomous decision-making with limited human oversight
Editorial, Foreword, and Table of Content Widodo Budiharto
International Journal of Computer Science and Humanitarian AI Vol. 2 No. 2 (2025): IJCSHAI
Publisher : Bina Nusantara University

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Abstract

Co-Authors Alexander Agung Gunawan Antoni Wibowo Christian Tarunajaya Frederikus Fios Hanis Amalia Saputri Heri Ngarianto Ilvico Sonata Iman Herwidiana Kartowisastro Karina Dwinovera Mulia Nabeel Kahlil Maulana Oey, Kevin Wijaya Putri Nurmala Reinard Lazuardi Kuwandy Wikaria Gazali Yaya Heryadi Yulianto, Budi