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

doi:10.24843/MTK.2020.v09.i01.p282

PENERAPAN ALGORITMA GLOWWORM SWARM OPTIMIZATION PADA MODEL GEOGRAPHICALLY WEIGHTED REGRESSION DENGAN KERNEL ADAPTIF

I GEDE HARDI KARMANA Udayana University
LUH PUTU IDA HARINI Udayana University http://orcid.org/0000-0003-4439-2643
KETUT JAYANEGARA Udayana University
I PUTU EKA NILA KENCANA Udayana University

DOI: https://doi.org/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.

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Author Biographies

I GEDE HARDI KARMANA, Udayana University

Program Studi Matematika, Fakultas MIPA – Universitas Udayana

LUH PUTU IDA HARINI, Udayana University

Program Studi Matematika, Fakultas MIPA – Universitas Udayana

KETUT JAYANEGARA, Udayana University

Program Studi Matematika, Fakultas MIPA – Universitas Udayana

I PUTU EKA NILA KENCANA, Udayana University

Program Studi Matematika, Fakultas MIPA – Universitas Udayana

Published

2020-01-31

How to Cite

KARMANA, I GEDE HARDI et al. PENERAPAN ALGORITMA GLOWWORM SWARM OPTIMIZATION PADA MODEL GEOGRAPHICALLY WEIGHTED REGRESSION DENGAN KERNEL ADAPTIF. E-Jurnal Matematika, [S.l.], v. 9, n. 1, p. 79-84, jan. 2020. ISSN 2303-1751. Available at: <https://ojs.unud.ac.id/index.php/mtk/article/view/57294>. Date accessed: 21 nov. 2024. doi: https://doi.org/10.24843/MTK.2020.v09.i01.p282.

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