CATEGORIC DATA GROUPING BY ALGORITHM QUICK ROBUST CLUSTERING USING LINKS (QROCK) (Case Study: Status of Value Addrd Tax Payments at the Samarinda Ulu Primary Tax Office in 2018)

Abstract

Clustering is a method for finding and grouping data that have similar characteristics (similarity) between one data and another. The method of grouping used in this study is the Qrock Algorithm (Quick Robust Using Links).The Qrock Algorithm has a more efficient method to produce the final cluster when the Rock Algorithm has no link beetwen the clusters.The concept of the Qrock Algorithm basically has the same principles as the Rock Algorithm, except that the Qrock Algorithm classifies objects only based on the neighbors of each object. The purpose of this study was to classify 200 Value Added Tax Payment Status data at the Samarinda Ulu Tax Service Office in 2018. Based on the analysis results, the threshold value ( ) = 0.1; 0.2; 0.3; 0.4; 0, 5 and 0.6 produce 1 cluster while the threshold values ( ) = 0.7; 0.8 and 0.9 produce 56 clusters.