CLUSTERING OF TEMPE INDUSTRIES BASED ON INDUSTRY CLASSIFICATION BY CLUSTER ANALYSIS (Case Study In Tempe Industry Centra Of Malang City) - Hermayudi, Wawan Agus; Effendi, Usman; Hidayat, Nur (Jurnal Teknologi Pertanian, 2004)
The purpose of balancing development protected the wide of gap, especially tempe industries as special produk of Malang City. The research purpose to know tempe industries map in Malang City were known the different of each cluster and how handled its. The local government of Malang City by the information was hoped could serious moved the specific development of otonomi daerah, on the target, and balanced in whole of Malang City area. Clustering in this research used Cluster Analysis by the helped of Statistical Program SPSS 11 version. The research was conducted started January 2004 in industries tempe centras which had chosen by Depperindag of Malang City. The variables which were used were the variables to classify the industry such as worker total, production value, row material total, investment value, and were added used tecnology, and product diversification for more informative. Data analysis were used Korelation Test, Dominant Komponen Searching, and Hierarchy Clustering Method. By the data analysis was known that all of tempe industries in Malang City were micro and small classified still which 17 industries (20%) were micro and 85 industries (80%) were small. If the result was three cluster, Tulusrejo, Merjosari, and Mulyurejo Centra were just made a cluster which had big chance become micro industry. Lesanpuro Centra made two cluster which four industries joined as Cluster One and two industries joined as Cluster Two and eventhough they had small industy classification but had big chance joined as Cluster One. Sanan Centra was centra which spreaded made three cluster such as 64 industries joined as Cluster One, 14 industries joined as Cluster Two, and one industry joined as Cluster Three. The clusters were description about the level which bigger and bigger. Key Word : Tempe Industry, Cluster Analysis