Modeling Open Unemployment Rate in West Sumatera Province Using Truncated Spline Regression

Aprilla Suhada, Syafriandi, Dodi Vionanda, F. Fitri
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Abstract

The Open Unemployment Rate (TPT) is an indicator used to measure the unemployment rate in the labor force which shows the percentage of the number of job seekers to the total workforce. In 2020 West Sumatra Province occupies the eighth position as the largest contributor to unemployment in Indonesia, this is a problem for the West Sumatra Provincial government. To deal with the unemployment problem, it is necessary to analyze the factors that are thought to affect the open unemployment rate in West Sumatra Province using truncated spline regression on the grounds that the data pattern between the response variables and each predictor variable does not form any pattern. Several factors are thought to influence the open unemployment rate, namely population, labor force participation rate, average length of schooling, dependency ratio. Based on the results of the analysis, the best model for modeling the open unemployment rate in West Sumatra Province is the truncated spline regression using three knot points with a GCV value of 0.061762. Variables that have a significant effect are population, labor force participation rate, average length of schooling and dependency ratio with a coefficient of determination of 99.97%.
基于截断样条回归的西苏门答腊省公开失业率模型
公开失业率(TPT)是一个用来衡量劳动力失业率的指标,它显示了求职者人数占总劳动力人数的百分比。到2020年,西苏门答腊省在印度尼西亚失业人数最多的地区中排名第八,这是西苏门答腊省政府面临的一个问题。为了解决失业问题,有必要利用截断样条回归分析影响西苏门答腊省公开失业率的因素,因为响应变量与每个预测变量之间的数据模式不形成任何模式。有几个因素被认为影响公开失业率,即人口、劳动力参与率、平均受教育年限、抚养比。基于分析结果,西苏门答腊省公开失业率的最佳模型是GCV值为0.061762的3个结点截断样条回归。影响显著的变量为人口、劳动力参与率、平均受教育年限和抚养比,决定系数为99.97%。
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