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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) ASEAN Journal of Science and Engineering Education (AJSEE)
S. Suparman
Universitas Ahmad Dahlan
Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Education Engineering Materials Science & Nanotechnology Other

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Hierarchical Bayesian of ARMA Models Using Simulated Annealing Algorithm S. Suparman; Michel Doisy
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 1: March 2014
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v12i1.12

Abstract

When the Autoregressive Moving Average (ARMA) model is fitted with real data, the actual value of the model order and the model parameter are often unknown. The goal of this paper is to find an estimator for the model order and the model parameter based on the data. In this paper, the model order identification and model parameter estimation is given in a hierarchical Bayesian framework. In this framework, the model order and model parameter are assumed to have prior distribution, which summarizes all the information available about the process. All the information about the characteristics of the model order and the model parameter are expressed in the posterior distribution. Probability determination of the model order and the model parameter requires the integration of the posterior distribution resulting. It is an operation which is very difficult to be solved analytically. Here the Simuated Annealing Reversible Jump Markov Chain Monte Carlo (MCMC) algorithm was developed to compute the required integration over the posterior distribution simulation. Methods developed are evaluated in simulation studies in a number of set of synthetic data and real data.
The Challenges of Remote E-Assessments During Covid-19 Outbreaks Among Undergraduate Engineering Programs Asnul Dahar Minghat; Noor Azihah Abdullah; S. Suparman
ASEAN Journal of Science and Engineering Education Vol 2, No 3 (2022): AJSEE: December 2022
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ajsee.v2i3.45323

Abstract

This study aims to identify the challenges faced by undergraduate students with remote e-assessments during Covid-19 outbreaks. The study was guided by the following specific objectives: to identify the level of students’ challenges to remote e-assessments in four major areas which are internet connectivity, academic integrity, disturbance in-home learning, and overflow of assignments, to identify significant differences between student’s location and family income category with four major areas of challenges to remote e-assessments. To achieve the objectives, students from one of the undergraduate programs at University Teknologi Malaysia have been chosen as the sample size. This study was designed to follow a single approach which is quantitative methods by means questionnaire surveys were distributed among the students and the data gathered was analyzed using SPSS software. The results from the analysis indicated that students facing the highest level of challenges to remote e-assessments during Covid-19 outbreaks are the overflow of assignments. The result from the study also showed that there is a significant difference between students’ family income and four major challenges to remote e-assessments. The recommendations are that organizations, especially at the university level should try to give great emphasis on e-assessments activities to develop those smooth practices to a great extent since the practice may eventually replace the traditional examination.
Co-Authors Asnul Dahar Minghat Michel Doisy Noor Azihah Abdullah