People now trying to maximizing function of Virtual Learning Environment. Virtual Learning Environment, not only as a place to help learning system but now has become a place of learning itself. But with the change of the learning system, teacher now have difficulty to monitor the activity of the student and the learning material. Although there is data that is considered capable become a benchmark for students and the interaction with Virtual Learning Activity. This paper will make a data prediction using Naïve bayes and C4.5 Algorithm using the Web History data and the sum of webpage interaction of the students in Virtual Learning Environment.

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SVM method performs a non-linear mapping of original data space into a high-dimensional feature space. The construction of linear discrimination function is useful for replacing the non-linear function in the original data space. This paper aims to efficiently explore the accuracy of SVM with the feature selection method. The selected feature selection method is Correlation-based Feature Selection (CFS), due to the approach's simplicity and speed. This research used an illiteracy rate dataset in Indonesia. The research result showed that the optimised method has overcome the original SVM, with 94 % of accuracy.

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Governments are seeking for new ways to fight corruption within their own administration. The opening of data has the potential to involve citizens in detecting corruption by providing them the ability to view and analyze data about what is happening within the government. However, how open data can be used to detect corruption is not clear. In this paper general patterns for detecting corruption using open data are derived. The patterns are derived by analyzing a case study of e-Procurement at the local government level in Indonesia. E-procurement activities and the corresponding audit activities were analyzed. The following patterns for detecting corruption using open data were derived; 1) storing and opening documents, 2) cross-data comparison, 3) four-eyes-principles, 4) segregation of duties, 5) authorization, and 6) publishing application controls. Data about the activities and structure of the administrative processes should be opened to allow the public to scrutinize whether the process has implemented preventive and detective controls following the process patterns derived in this research. Furthermore, data should be opened about all phases of the administrative processes to enable the involvement of the public and use their 'many eyes' for detecting corruption.@en

There has been a lot of research on the use of open data in the fight against corruption. Although there are some promising examples, it appears that a systematic approach is lacking. What are the design principles for an architecture to open up data and thereby reduce corruption? In this paper we use theory about fraud, and about public accountability to derive design principles for an open data architecture. Crucial is the sustained presence of a specific forum: A group of people who are critical, have expertise, are free to challenge the authorities. Unlike the general public, a specific forum has an interest in reviewing the data. The architecture is motivated and illustrated by an extensive example of an E-procurement system in the context of an anticorruption program in Palembang, Indonesia.@en