Article Per Year (5 Year)
p-Index From 2020 - 2025
0.61
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Jurnal Teknik Informatika (JUTIF)
Fachri, Moch
Unknown Affiliation
Religion Arts Humanities Computer Science & IT Economics, Econometrics & Finance Engineering Social Sciences

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Vehicle Counter in Traffic Using Pixel Area Method with Multi-Region of Interest Fachri, Moch; Hikmah, Nur; Chusna, Nuke Lu'lu ul
Budapest International Research and Critics Institute (BIRCI-Journal): Humanities and Social Sciences Vol 4, No 4 (2021): Budapest International Research and Critics Institute November
Publisher : Budapest International Research and Critics University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33258/birci.v4i4.3264

Abstract

Traffic density data plays an important role in decision making by the Intelligent Transportation System (ITS). This system uses this data in the process of adaptive traffic management. The inaccuracy of the data provided into the ITS system can result in errors in decision making. This study utilizes digital image engineering technology in the detection of four-wheeled vehicles in traffic traffic for the purpose of acquiring traffic density data. In this study, we propose a multi-ROI (pixel area methodRegion of Interest). This multi-ROI proposal is to be put forward to improve reading accuracy compared to just one ROI. With the use of this multi-ROI, the information obtained from the overall ROI can strengthen the accuracy of the data of vehicles passing in a lane. Our experimental results show that the use of multi-ROI with a certain amount of ROI can produce an accuracy rate of up to 88.66% compared to single-ROI which has an accuracy rate of 84.65%.
Crowd navigation for dynamic hazard avoidance in evacuation using emotional reciprocal velocity obstacles Fachri, Moch; Prasetyo, Didit; Damastuti, Fardani Annisa; Ramadhani, Nugrahardi; Susiki Nugroho, Supeno Mardi; Hariadi, Mochamad
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp1371-1379

Abstract

Crowd evacuation can be a challenging task, especially in emergency situations involving dynamically moving hazards. Effective obstacle avoidance is crucial for successful crowd evacuation, particularly in scenarios involving dynamic hazards such as natural or man-made disasters. In this paper, we propose a novel application of the emotional reciprocal velocity obstacles (ERVO) method for obstacle avoidance in dynamic hazard scenarios. ERVO is an established method that incorporates agent emotions and obstacle avoidance to produce more efficient and effective crowd navigation. Our approach improves on previous research by using ERVO to model the perceptive danger posed by dynamic hazards in real-time, which is crucial for rapid response in emergency situations. We conducted experiments to evaluate our approach and compared our results with other velocity obstacle methods. Our findings demonstrate that our approach is able to improve agent coordination, reduce congestion, and produce superior avoidance behavior. Our study shows that incorporating emotional reciprocity into obstacle avoidance can enhance crowd behavior in dynamic hazard scenarios.
APPLICATION OF MULTI-CRITERIA PROMETHEE METHOD TO ASSIST CHARACTER SELECTION IN THE ENDLESS RUNNER GAME Nurrahma, Alfina; Nugroho, Fresy; Buditjahjanto, I.G.P. Asto; Pebrianti, Dwi; Hammad, Jehad A.H.; Fachri, Moch; Lestari, Tri Mukti; Maharani, Dian; Prakasa, Aji Bagas
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2183

Abstract

The endless runner game is one of the most popular game genres, but selecting the optimal character for different map challenges poses a significant problem for players. In this context, this research was conducted to help select characters in the endless runner game using the PROMETHEE method. This selection is recommended based on the weight and difficulty of each map which varies, including the rice field map, road map and alley map. The implementation of calculating character recommendations uses the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method with the highest score as the best ranking. Rank suitability can be determined by comparing the PROMETHEE method with the TOPSIS method on 15 characters alternatives with 6 criteria. As a result, the PROMETHEE method has significant value, but some still have the same best ranking as the TOPSIS method. Furthermore, usability testing was carried out on 57 respondents using the System Usability Scale (SUS) with an overall score from the evaluation of 78,8. The final score obtained based on the acceptance scale was included in the category suitable for use.
Co-Authors Chusna, Nuke L Damastuti, Fardani Annisa Dian Maharani, Dian Fresy Nugroho Hammad, Jehad A.H. I Gusti Putu Asto Buditjahjanto Lestari, Tri Mukti Mochamad Hariadi Nugrahardi Ramadhani Nur Hikmah Nurrahma, Alfina Pebrianti, Dwi Prakasa, Aji Bagas Prasetyo, Didit Supeno Mardi Susiki Nugroho, Supeno Mardi