Jurnal Aplikasi Statistika & Komputasi Statistik
Vol 7 No 2 (2015): Journal of Statistical Aplication and Statistical Computing

Analisis Multivariate Adaptive Regression Splines (MARS) pada Prediksi Ketertinggalan Kabupaten Tahun 2014

Siskarossa Ika Oktora (Unknown)



Article Info

Publish Date
31 Dec 2015

Abstract

The purposes of this research are to build underdeveloped regency model and make a prediction in 2014 based on economic categories, Human Resources (HR), infrastructures, fiscal capacity, accessibility, and regional characteristics with MARS method. MARS is a classification method which can handle highdimensional data with unknown pattern in advance, and can be applied to see the interaction between variables. MARS is an alternative method when the data doesn’t fulfil the parametric statistics assumptions. From MARS model, there are three variables that affect underdeveloped regency, they are consumption expenditure per capita, life expectancy, and percentage of household electricity users. The accuracy of MARS model is very high, 97.83 percent and can be used to make a prediction. Based on MARS model, at the end of the National Development Plan 2010-2014 is predicted a significant transitions in regency’s status. This model can also be used to predict the condition of new regency based on empirical data, because in the earlier classification, the status of regency just follows the status of parent region.

Copyrights © 2015






Journal Info

Abbrev

jurnalasks

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Mathematics

Description

Redaksi menerima karya ilmiah atau artikel penelitian mengenai kajian teori statistika dan komputasi statistik pada bidang ekonomi dan sosial dan kependudukan, serta teknologi informasi. Redaksi berhak menyunting tulisan tanpa mengubah makna subtansi tulisan. Isi jurnal Aplikasi Statistika dan ...