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Journal : IJID (International Journal on Informatics for Development)

Topology Analysis of iBGP Confederation Case : Indonesia Research and Education Network (IdREN) Irwin Wijaya Lahusen; Widyawan Widyawan; Sri Suning Kusumawardani
IJID (International Journal on Informatics for Development) Vol. 8 No. 1 (2019): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (710.743 KB) | DOI: 10.14421/ijid.2019.08104

Abstract

Implementation of the BGP Confederation topology scenario, found a number of new facts that influence the final decision making for BGP network managers. In previous studies it has been mentioned a number of factors that influence QoS from a topology scheme, among others, the number of Sub AS and the number of routers that make up the iBGP topology. In this study, a number of scenarios were developed by giving variants to bandwidth parameters and adding measurement parameters to Lost Datagram in all scenarios. The results obtained are quite significant, affecting QoS and finding a number of new facts related to the effect of using traffic generators. This research was tested on the Indonesia Research and Education Network (IdREN) network using GNS3.
Research Trend of Causal Machine Learning Method: A Literature Review Arti, Shindy; Hidayah, Indriana; Kusumawardani, Sri Suning
IJID (International Journal on Informatics for Development) Vol. 9 No. 2 (2020): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2020.09208

Abstract

Machine learning is commonly used to predict and implement  pattern recognition and the relationship between variables. Causal machine learning combines approaches for analyzing the causal impact of intervention on the result, asumming a considerably ambigous variables. The combination technique of causality and machine learning is adequate for predicting and understanding the cause and effect of the results. The aim of this study is a systematic review to identify which causal machine learning approaches are generally used. This paper focuses on what data characteristics are applied to causal machine learning research and how to assess the output of algorithms used in the context of causal machine learning research. The review paper analyzes 20 papers with various approaches. This study categorizes data characteristics based on the type of data, attribute value, and the data dimension. The Bayesian Network (BN) commonly used in the context of causality. Meanwhile, the propensity score is the most extensively used in causality research. The variable value will affect algorithm performance. This review can be as a guide in the selection of a causal machine learning system.
Accessibility Analysis of Learning Management System Websites Dwi Fithriyaningrum; Kusumawardani, Sri Suning; Wibirama, Sunu
IJID (International Journal on Informatics for Development) Vol. 11 No. 1 (2022): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2022.3485

Abstract

In the digital era, Learning Management System is widely used to spread information in higher education, particularly at the university level. There are, however, issues with the Learning Management System's accessibility for users with disabilities. This research aims to investigate the accessibility issues of learning management websites of 30 universities in Indonesia. The top 30 universities in Indonesia according to Webometrics 2022 are the basis for this study. Accessibility issues will be identified and examined using the Wave evaluation tool which is in accordance with the Web Content Accessibility Guidelines 2.1 used by ISO 40500. Web Content Accessibility Guideline 2.1 has principles that any web should follow: Perceivable, Operable, Understandable, and Robust. Based on the research findings, The low contrast ratio between text and background, the absence of text explanations in the images, the lack of descriptive text on the links, the absence of text labels on the form, and the absence of text description on the button were the most frequently encountered accessibility issues.