Klasifikasi Algoritma K-Nearest Neighbor Berbasis Particle Swarm optimization Untuk Kelaykan Bantuan Rehabilitasi rumah Tidak Layak Huni Pada Desa Lenek Duren Kecamatan Aikmel Kabupaten Lombok timur - Suhartini, suhartini; bahtiar, hariman (Infotek : Jurnal Informatika dan Teknologi, 2019)
Home is a very basic requirement for all people besides food and clothes. Home can express prosperity level and health level about resident / its dweller. A high quality of home as good shelter can be seen from its building, facility and structure. The local government program to decrease poverty through program of RTLH, have to be supported with data accuration. Besides good data accuration, it is also required data-processing time efficiency of receiver of aid. This research used Data technique of Mining with Algorithm of K-Nearest Neighbor base on Particle Swarm Optimization in classification elegibility of acceptance of aid rehabilitate house improper dwell. By using method of calculation of algorithm of K-Nearest Neighbor base on Particle Swarm Optimization, the accuration value in prediction elegibility of acceptance of aid rehabilitate house improper dwell is calculated. After conducting a test by using algorithm of K-NN and algorithm of K-NN base on Particle Swarm Optimization,Â  the result is algorithm of K-NN yield accuration value equal to 89,29% and value of AUC 0,786. The algorithm of K-NN base on Particle Swarm Optimization yield accuration value equal to 95,33% and value of AUC 0.970. After conducting the tests to both of the model, the difference is showed with 6,04% percentage and difference of value of AUC 0.184.Â DOI : 10.29408/jit.v2i2.1417