PEMANFAATAN ALGORITMA WIT-TREE DAN HITS UNTUK KLASIFIKASI TINGKAT KEBERHASILAN PEMBERDAYAAN KELUARGA MISKIN (Studi Kasus Kabupaten Bantul); THE USE OF WIT-TREE AND HITS ALGORITHMS FOR CLASSIFYING SUCCESSFUL RATE OF POOR FAMILIES EMPOWERMENT (Case Study:Bantul District)
Khomsah, Siti, Edi Winarko
2015 | Disertasi | FMIPAThe purpose of this research is to build a classification model to predict the level of successful rate from poor families, who will receive assistance empowerment of poverty. In this research, the success of the empowerment of poor families can be classified by characteristic patterns extracted from the database that contains the data of poor families empowerment. Classification models built with weigthed association rule mining method (WARM), which is a combination of methods Hyperlink Induced Topic Search (HITS) and Weighted Itemset TidSet-tree (WIT-tree). Generaly, the weighting of attributes in WARM determined directly by users without knowing how to determine the exact weight. HITS algorithm is used to obtained the weight of attributes from the database. The weights are used as the weight of the attributes on methods WIT-tree. WIT-tree is used to generate the association rules that satisfy a minimum weight support and a minimum weight confidence. The data used in this study was 831 sample data poor families, who are divided into two classes, namely poor families in the standard of "developing" and poor families in the level of "underdeveloped". Weighting attribute using HITS approaches the accuracy of 86.45% and weighted attributes defined by the user approaches the accuracy of 66.13%. This study shows that the weight of the attributes obtained from HITS method is better than the weight of the attributes specified by the user. The accuracy of the model was measured by k-fold cross validation with minimum weight support thresholds are 0.1, 0.2, 0.3 and minimum weight confidence threshold is 0.5.
Kata Kunci : empowerment of poor families; Weighted Association Rule Mining; HITS; WIT- tree.
