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All Journal E-Jurnal Matematika
I GEDE HARDI KARMANA
Udayana University
Mathematics

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PENERAPAN ALGORITMA GLOWWORM SWARM OPTIMIZATION PADA MODEL GEOGRAPHICALLY WEIGHTED REGRESSION DENGAN KERNEL ADAPTIF I GEDE HARDI KARMANA; LUH PUTU IDA HARINI; KETUT JAYANEGARA; I PUTU EKA NILA KENCANA
E-Jurnal Matematika Vol 9 No 1 (2020)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2020.v09.i01.p282

Abstract

This study aimed to apply glowworm swarm optimization (GSO) algorithm as an alternate way to obtain optimal bandwidth in geographically weighted regression (GWR) model with adaptive kernel function. The result showed that GSO was able to obtain optimal bandwidth with lower cross validation (CV) value than the traditional way that was using k-nearest neighbor (KNN) algorithm. Unfortunately, the running time of GSO was far slower than KNN was.
Co-Authors I Putu Eka Nila Kencana Ketut Jayanegara LUH PUTU IDA HARINI