AIRCC's International Journal of Computer Science and Information Technology

Bambang Sugiantoro ¹, Retantyo Wardoyo ², Sri Hartati ², Jazi Eko Istiyanto ²

Affiliations
1 Dept. of Informatics Engineering, State Islamic University Sunan Kalijaga, Yogyakarta, ID
2 Dept. of Computer Sciences and Electronics, Gadjah Mada University, Yogyakarta, ID

Abstract

Mobile agent is a certain agent actively able to move from one computer to another or even travel across network to perform the task assigned. This research aimed to develop mobile agent model to detect distributed intrusion (Distributed Intrusion Detection System).

It was expected that the produced model was able to perform its task in nearly real time manner, to be immune against attack, and also fairly small overhead at the host, either in memory consumption or CPU usage. In this research, the Aglets concept was also developed to aid intrusion detection. This approach was also maintained to solve certain issues such as scalability, reliability, and configurability. Hence, the advantages and limitations of agent-based approaches will be when it is applied in real world.

Keywords

Developing Mobile Agent Model, Aglets and Intrusion Detection.

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Andi Wahju Rahardjo Emanuel ¹, Retantyo Wardoyo ², Jazi Eko Istiyanto ², Khabib Mustofa ²

Affiliations
1 Maranatha Christian University, ID
2 Department of Computer Science and Electronics, Gadjah Mada University, ID

Abstract

Modularity has been identified by many researchers as one of the success factors of Open Source Software (OSS) Projects. This modularity trait are influenced by some aspects of software metrics such as size, complexity, cohesion, and coupling. In this research, we analyze the software metrics such as Size Metrics (NCLOC, Lines, and Statements), Complexity Metrics (McCabe's Cyclomatic Complexity), Cohesion Metrics (LCOM4), and Coupling Metrics (RFC, Afferent coupling and Efferent coupling) of 59 Java-based OSS Projects from Sourceforge.net. By assuming that the number of downloads can be used as the indication of success of these projects, the OSS Projects being selected are the projects which have been downloaded more than 100,000 times. The software metrics reflecting the modularity of these projects are collected using SONAR tool and then statistically analyzed using scatter graph, Pearson r product-moment correlation, and least-square-fit linear approximation. It can be shown that there are only three independent metrics reflecting modularity which are NCLOC, LCOM4, and Afferent Coupling, whereas there is also one inconclusive result regarding Efferent Coupling.

Keywords

Open Source Software Project, Modularity, Software Metrics, Statistical Analysis, Java.

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Ermatita ¹, Sri Hartati ², Retantyo Wardoyo ², Agus Harjoko ²

Affiliations
1 Department of Information System, Computer Science Faculty of Sriwijaya University, ID
2 Departement of Computer Science and Electronics, Gadjah Mada University, ID

Abstract

Analysis of genes expression can be done with the investigation of a particular microarray data for the description of a gen. This is done to identify what genes that were active in the human body. Detection of gene mutation is an activity that can provide contribution in the medical field. Detection of mutated gene is needed to avoid the diseases caused by them such as cancer. The detection of gene mutations can be performed by utilizing computer-based system. Group Decision Support System (GDSS) is a computer-based system that can be utilized in detecting human gene mutations that cause disease. The ELECTRE method, which is a Multi-Attribute Decision Making, is a method in modeling multi-criteria GDSS. In this paper we propose implementation of model for multi-criteria GDSS in which the simulation data is the mutated genes that can cause cancer.

Keywords

Bioinformatics, Group Decision Support System, ELECTRE, Gene Mutation.

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