Opim Salim Sitompul

An extracted social network mining

Future of data mining is the social network mining, especially in connection with the web pages, will incorporate the network timeline that are generated with social network extraction. This approach we use to deal with dynamic and process of evolution in networks. Although there is an increasing interest about the social network analysis, but a little of them has a significant impact to social substructures mining. Therefore this paper proposes the mining of social network based on unit analysis in social network analysis to build a network: vertex and edge. In study we used multiple regression to determine the relations of resources of networks, but we explore naturally formal relation of vertices and edges like leadership of an author, and then we explained in experiments. So there is the role of each actor in the social networks.

Skin color segmentation using multi-color space threshold

Skin color segmentation has proven to be useful in various application, such as face detection, hand gesture analysis, image content filtering, etc. There are some challenges on skin-color detection, such as wide variety of illumination condition and skin-like color objects appear in the background of image. Therefore, a method is required to cope with illumination condition while detecting skin color. In our proposed method, we combine the chrominance channels of three color spaces, namely HSV, YCbCr and Normalized RGB, to produce better rate result for skin color segmentation. The result shows that the proposed method is able to detect skin pixel and get up to 91.05% correct result while being tested in ECU and HGR Dataset. This result is significantly higher than the other single color spaces.

Enhancing Extraction Method for Aggregating Strength Relation Between Social Actors

There are differences in the resultant of extracting the relations between social actors based on two streams of approaches in principle. However, one of the methods like the superficial methods can upgraded to make the information extraction by using the principles of the other methods, and this needs proof systematically. This paper serves to reveal some formulations have the function for resolving this issue. Based on the results of experiments conducted the expanded method is the adequate.

Social network extraction based on Web: 3. the integrated superficial method

The Web as a source of information has become part of the social behavior information. Although, by involving only the limitation of information disclosed by search engines in the form of: hit counts, snippets, and URL addresses of web pages, the integrated extraction method produces a social network not only trusted but enriched. Unintegrated extraction methods may produce social networks without explanation, resulting in poor supplemental information, or resulting in a social network of durmise laden, consequently unrepresentative social structures. The integrated superficial method in addition to generating the core social network, also generates an expanded network so as to reach the scope of relation clues, or number of edges computationally almost similar to n(n − 1)/2 for n social actors.