Haviluddin, Fahrul Agus, Muhamad Azhari, Ansari Saleh Ahmar
A geostatistics practical approach is divided data sample into several groups with certain rules. Then, the data groups are used for spatial interpolation. Furthermore, clustering technique is quite commonly used in order to get distance function between sample data. In this study, Self-Organizing Maps (SOM) optimized by using Learning Vector Quantization (LVQ) especially in distance variance have been implemented. The land value zone datasets in Samarinda, East Kalimantan, Indonesia have been used. This study shows that the SOM optimized by LVQ technique have a good distance variance value in the same cluster than SOM technique. In other words, SOM-LVQ can be alternative clustering technique especially centroid position in clusters. © 2016 Authors.
Faculty of Computer Science and Information Technology, Mulawarman University, Indonesia; Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Negeri, Makassar, Indonesia
