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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Komputer Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURNAL INSTEK (Informatika Sains dan Teknologi) CCIT (Creative Communication and Innovative Technology) Journal E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi Infotek : Jurnal Informatika dan Teknologi Indonesian Journal of Technology, Informatics and Science (IJTIS) DEVICE EXPLORE
Anggit Dwi Hartanto
STMIK AMIKOM Yogyakarta
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Enhanced Yolov8 with OpenCV for Blind-Friendly Object Detection and Distance Estimation Erwin Syahrudin; Ema Utami; Anggit Dwi Hartanto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 2 (2024): April 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i2.5529

Abstract

The development of computer technology and computer vision has had a significant positive impact on the daily lives of blind people, especially in efforts to improve their navigation skills. This research aims to introduce a superior object detection method, especially to support the sustainability and effectiveness of blind navigation. The main focus of the research is the use of YOLOv8, the latest version of YOLO, as an object detection method and distance measurement technology from OpenCV. The main challenge to address involves improving object detection accuracy and performance, which is an important key to ensuring safe and effective navigation for blind people. In this context, blind people often face obstacles in their mobility, especially when walking in environments that may be full of obstacles or obstacles. Therefore, better object detection methods become essential to ensure the identification of nearby objects that may involve obstacles or potential threats, thus preventing possible accidents or difficulties in daily commuting. Involving YOLOv8 as an object detection method provides the advantage of a high level of accuracy, although with a slight increase in detection duration and GPU power consumption compared to previous versions. The research results show that YOLOv8 provides a low error rate, with an average error percentage of 3.15%, indicating very optimal results. Using a combined performance evaluation approach of YOLOv8 and OpenCV distance measurement metrics, this research not only seeks to improve accuracy but also efficiency in detection time and power consumption. This research makes an important contribution to the presentation of technological solutions that can help improve mobility and safety for blind people, bringing a real positive impact on the facilitation of their daily lives.
The Effect of Resampling Techniques on Model Performance Classification of Maternal Health Risks Nia Mauliza; Aisha Shakila Iedwan; Yoga Pristyanto; Anggit Dwi Hartanto; Arif Nur Rohman
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 4 (2024): August 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i4.5934

Abstract

Indonesia's maternal mortality rate was the second highest in ASEAN, reflecting the problem of class imbalance in maternal health data. This research aimed to improve prediction accuracy in the classification of pregnant women's diseases through the application of various resampling methods. The methods used in this research included Synthetic Minority Over-sampling Technique (SMOTE), SMOTE-Edited Nearest Neighbor (SMOTE-ENN), Adaptive Synthetic Sampling (ADASYN), and ADASYN-ENN, using five classification algorithms: Decision Tree, K-Nearest Neighbor (KNN), Naïve Bayes, Random Forest, and Support Vector Machine (SVM). Performance evaluation was carried out using accuracy, precision, recall, and F1-score metrics to determine the best method and algorithm. The results showed that the SMOTE-ENN and ADASYN-ENN methods significantly improved the model's performance in predicting maternal disease. Random Forest and Decision Tree algorithms showed the best results in terms of accuracy and consistency. These findings provided practical guidance for the application of resampling techniques in the classification of pregnant women's health data, which could contribute to improving the quality of maternal health services in Indonesia.
Implementation of Scrum Method in the Learning Activity Monitoring Feature Outside the Study Program -, Atik Nurmasani; Ilham, Muhammad Rohmadi; Anggit Dwi Hartanto
Jurnal Komputer Terapan Vol 10 No 1 (2024): Jurnal Komputer Terapan
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35143/jkt.v10i1.5972

Abstract

Learning activities outside the study program can be participated by active students in the current semester through the credit recognition mechanism according to the study program policy. These activities are monitored by Field Supervisors (DPL) through certain communication media. The obstacles that arise such as students not contacting DPL or communicating with DPL, not reporting activities regularly, only asking for a signature on the final report, and only asking DPL to fill out an activity assessment. The activity recording information system that available only has features for submitting proposals, recording activities and reporting activities for study program admin users. So that it is necessary to develop a feature for monitoring learning activities outside the study program to make it easier for DPL to monitor student activities in certain semesters. The information system was created using the MySQL database and the Codeigniter 3 framework. Feature development was created using the Scrum method with a focus on determining priority features, working on priority features and reviewing the results of feature work. This can help to get information system output quickly according to development needs
Co-Authors -, Atik Nurmasani Ahmad Almas'ud ZD Aisha Shakila Iedwan Aji Surya Mandala Andika Yudirianto Andri Faisal Sentosa Arian Wahyu Dewantara Arief Setyanto Arif Nur Rohman Dimas Rio P.L. Ema Utami Erwin Syahrudin Fajar Eko Nugroho Hizbul Izzi Ikhsan Subagyo Ilham, Muhammad Rohmadi Kholiq Prajatama KUSRINI Kusrini Kusrini Lukman Dwi Yulianto Ma'ruf Aziz Muzani Marta Ardiyanto Nia Mauliza Safor Madianto Septa Najibul Wahid Sidiq Aminudin Syifa Fauziah Wahyu Permadi wahyuni, wenti ayu Yoga Pristyanto