Rahmat Budiarto
College of Computer Science and Information Technology, Albaha University, Saudi Arabia

Published : 15 Documents
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Journal : International Journal of Electrical and Computer Engineering (IJECE)

SeamSAR: Seamless, Secure And Robust Handover Model for Mobile IPTV Network Using Enhanced FMIPv6 Aldmour, Ismat; Al-Dala?in, Thair; Siregar, Lelyzar; Budiarto, Rahmat
International Journal of Electrical and Computer Engineering (IJECE) Vol 5, No 2: April 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (347.926 KB) | DOI: 10.11591/ijece.v5i2.pp371-378

Abstract

Multimedia becomes one of the most wanted content in the modern Internet world. Since the Mobile Internet Protocol version 6 (MIPv6) was proposed, many researchers have tried to develop a new protocol based on this technology in order to improve the performance of mobile multimedia services. The world is emerging toward the Mobile Internet Protocol Television (MIPTV) era where people are enabled to watch television while roaming. The MIPTV technology requires high bandwidth and low latency handover. This paper proposes a new model of secure and robust handover with low handover latency, called SeamSAR. The model introduces a new way to perform home binding update and correspondent binding update simultaneously. Simulation results show that the proposed model reduced the handover latency to 63% compared to FMIPv6. Moreover, the secureness of the proposed model was verified using CMurphi simulator.
An Investigation Study on Optimizing Enterprise Resource Planning (ERP) Implementation in Emerging Public University: Al Baha University Case Study Shakkah, Moh?D Suliman; Alaqeel, Khaled; Alfageeh, Ali; Budiarto, Rahmat
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 4: August 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (149.296 KB) | DOI: 10.11591/ijece.v6i4.pp1920-1928

Abstract

This project investigates the correlation between the organizational readiness in Albaha University (ABU) and the respective Critical Success Factors (CSFs) with regards to the Enterprise Resource Planning (ERP) implementation. The investigation also considers some suggestions to improve the ABU?s ERP systems and roadmap towards the self ?development strategy and reduce vendor-dependency. A survey regarding ERP to the end-user, expert and developer in ABU was conducted. The analysis of the results in this work confirmed with the results of an existing work. The four significance success factors: Project Management, Business Process Re-engineering (BPR), System Integration, and Training and Education are recommended to be adopted to assure the smooth adoption of ERP at Albaha University
Random forest age estimation model based on length of left hand bone for Asian population Darmawan, Mohd Faaizie; Zainal Abidin, Ahmad Firdaus; Kasim, Shahreen; Sutikno, Tole; Budiarto, Rahmat
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 1: February 2020 (PART I)
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (625.495 KB) | DOI: 10.11591/ijece.v10i1.pp549-558

Abstract

In forensic anthropology, age estimation is used to ease the process of identifying the age of a living being or the body of a deceased person. Nonetheless, the specialty of the estimation models is solely suitable to a specific people. Commonly, the models are inter and intra-observer variability as the qualitative set of data is being used which results the estimation of age to rely on forensic experts. This study proposes an age estimation model by using length of bone in left hand of Asian subjects range from newborn up to 18-year-old. One soft computing model, which is Random Forest (RF) is used to develop the estimation model and the results are compared with Artificial Neural Network (ANN) and Support Vector Machine (SVM), developed in the previous case studies. The performance measurement used in this study and the previous case study are R-square and Mean Square Error (MSE) value. Based on the results produced, the RF model shows comparable results with the ANN and SVM model. For male subjects, the performance of the RF model is better than ANN, however less ideal than SVM model. As for female subjects, the RF model overperfoms both ANN and SVM model. Overall, the RF model is the most suitable model in estimating age for female subjects compared to ANN and SVM model, however for male subjects, RF model is the second best model compared to the both models. Yet, the application of this model is restricted only to experimental purpose or forensic practice.