Jurnal Varian
Vol 6 No 2 (2023)

Kernel Nonparametric Regression for Forecasting Local Original Income

Joji Ardian Pembargi (University of Mataram, Indonesia)
Mustika Hadijati (University of Mataram, Indonesia)
Nurul Fitriyani (University of Mataram, Indonesia)



Article Info

Publish Date
16 May 2023

Abstract

Regional Original Revenue (ROR) is an income collected based on regional regulations under statutory regulations. ROR aims to give authority to Regional Governments to sponsor the implementation of regional autonomy following regional potential. Every year, the Central Lombok Regency government sets ROR targets to assist the government in formulating regional policies. The targets set by the government are sometimes not following their realization. This study aims to determine a model that can be used in forecasting ROR targets. One way to predict the value of ROR is by using a nonparametric regression approach. This approach is flexible since it is not dependent on a particular model. The use of the nonparametric kernel regression method with the Gaussian kernel function obtained a minimum GCV value of 1,769688931 with an optimum bandwidth value of of 0,212740452 and of 0,529682589. Modeling with optimum bandwidth produces a coefficient of determination of 87,55%. The best model is used for forecasting and produces a MAPE value of 5,4%. The analysis results show that what influences the value of ROR is ROR receipts in the previous month and the previous 12 months.

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Journal Info

Abbrev

Varian

Publisher

Subject

Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Social Sciences Other

Description

Jurnal Varian adalah salah satu Jurnal Ilmiah yang terdapat di Universitas Bumigora. Jurnal ini bertujuan untuk memberikan wadah atau sarana publikasi bagi para dosen, peneliti dan praktisi baik di lingkungan internal maupun eksternal Universitas Bumigora Mataram. Jurnal ini terbit 2 (dua) kali ...