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All Journal VARIANSI: Journal of Statistics and Its Application on Teaching and Research
Muhammad Fahmuddin S
Department of Statistics, Universitas Negeri Makassar
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics

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Analisis Regresi Nonparametrik Spline Truncated untuk Menganalisis Faktor-Faktor yang Mempengaruhi Tingkat Pengangguran Terbuka di Provinsi Sulawesi Selatan Devi Carolin Wongkar; Ruliana Ruliana; Muhammad Fahmuddin S
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 5 No. 02 (2023)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm101

Abstract

The nonparametric regression analysis is a regression model used to determine the relationship between response variable and independent variables with unknown regression curve shapes. In the nonparametric approach, one of the frequently used estimators is the spline truncated. Spline truncated model is a segmented polynomial truncation model. The advantage of this model is that it is flexible because it has knot points that can show changes in data patterns. The unemployment rate in South Sulawesi Province in 2021 reached 5.72% and became the province with the second highest unemployment rate on Sulawesi Island. Therefore, spline truncated nonparametric regression modelling will be carried out in the case of unemployment rate with each of the factors that are thought to be influential because the regression curve is found not to form a certain pattern. Based on the analysis results, the best truncated spline nonparametric regression model was obtained using three knot points and obtained the minimum GCV value of 0.38 with a coefficient of determination (R2) value of 89%. Factors that have a significant effect on the unemployment rate in South Sulawesi are mean years of schooling (x1) and labour force participation rate (x2).
APLIKASI FUNGSI TRANSFER MULTIVARIAT UNTUK PERAMALAN CURAH HUJAN DI KOTA MAKASSAR Idul Fitri Abdullah Abdullah; Ruliana Ruliana; Muhammad Fahmuddin S
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 5 No. 02 (2023)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm117

Abstract

This study aims to determine the transfer function model and factors that significantly affect the level of rainfall in Makassar city. This study uses rainfall data as the output series and air humidity (X1), air temperature (X2) and wind speed (X3) as the input series. The data used is monthly data with a period of January 2013 - December 2022. The initial stage of modeling is done by determining the ARIMA model of each input series which is then used to calculate the identification of the transfer function model Based on the research obtained multivariate transfer function model X1 (b=3, r=0, s=0) X12(b=0, r=0, s=0) ARIMA (2,1,0)(1,1,0)12 with air humidity and air temperature being significant factors affecting rainfall in Makassar city.
Co-Authors Devi Carolin Wongkar Idul Fitri Abdullah Abdullah Ruliana