ITS Campus, ITS News – As the era develops, which produces a lot of data, data analysis has become necessary before making a decision. Based on this, the 163rd professor of the Institut Teknologi Sepuluh Nopember (ITS), Prof Dr Wahyu Wibowo SSi MSi, studied an appropriate method to increase the accuracy of regression modelling (an analytical technique commonly used to see the influence between two or many variables) through an approach semiparametric spline.
In his scientific oration entitled Semiparametric Spline: Strategy for Increasing Regression Modeling Accuracy in the Evidence-Based Decision Making (EBDM) Framework, this Professor at the Department of Business Statistics, ITS Vocational Faculty, explained the importance of data analysis. Data analysis is the basis for the business decision-making process, better known as the Evidence-Based Decision Making (EBDM) concept.
Regression modelling, which plays an essential role as a basis for decision-making, still needs help determining the most accurate regression function. A function can accurately explain the relationship between the response variable and the predictor with minimum error. “In my opinion, a semiparametric approach using spline functions can overcome this problem,” said Wahyu.
This ITS Bachelor of Statistics alumnus chose the semiparametric model not without reason because it has a high accuracy level and is easy to interpret. Wahyu also explained that the reason for using the spline function was because the procedure was simple. “Apart from that, the spline function is adaptive and flexible to the relationship patterns formed between variables,” he explained.
This innovation is not limited to only being implemented in the business world but can also be applied in industry to government. Through his inaugural scientific oration as a professor, the Head of the ITS Business Statistics Department implemented his econometrics model to analyze development gaps between provinces on the island of Java.
In his analysis, the 49-year-old man used several predictor variables: investment, labour, education index, and information and communication technology (ICT) index. From these predictor variables, Wahyu tried to find their relationship with the response variable: the disparity index or difference in income of six provinces on the island of Java from 2010 to 2019.
When analyzed using a spline function with a semiparametric approach, the results show that the investment variable initially reduces the gap. However, investments can increase the gap after reaching a certain point. “Meanwhile, the graphs for other variables are only flat, and there are no significant changes,” explained the lecturer who also taught at the ITS Statistics Department.
After an analysis, the alumnus of the Master of Mathematics at Gadjah Mada University (UGM) concluded that investment is closely related to inter-provincial disparities. Meanwhile, other predictor variables, namely the education index, ICT index, and labor, have yet to explain the development gap between provinces in East Java significantly.
By applying this model, the Professor, who also holds a doctorate from Mathematics UGM in 2015, wants to show that the semiparametric spline regression model can have more than 90 per cent accuracy. This accuracy means this modelling can increase accountability and quality in decision-making.
The Indonesian Statistics Higher Education Forum certification coordinator plans to implement this model in a helpful decision-making dashboard. Hopefully, all parties, especially the government, can take advantage of this model to improve the quality of decision-making. (ITS Public Relations)
Reporter: Mohammad Febryan Khamim
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