MULTIPLE LINEAR REGRESSION ANALYSIS FOR STUDENT ECONOMIC DATA
Every university always issues new policies regarding the cost of education. New students are usually only subject to the education fee component called Single Tuition Money (UKT). At ITB the amount of UKT set in 2013 was Rp. 10 million. In 2018, the UKT amount increased significantly to Rp. 12.5 mi...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/26984 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Every university always issues new policies regarding the cost of education. New students are usually only subject to the education fee component called Single Tuition Money (UKT). At ITB the amount of UKT set in 2013 was Rp. 10 million. In 2018, the UKT amount increased significantly to Rp. 12.5 million for undergraduate students. From the established UKT Undergraduate Programs, students are given the opportunity to apply for relief at a rate of 20%, 40%, 60%, 80%, up to 100% of UKT. A calculation method to determine the amount of UKT subsidies can be designed. Previous methods used to determine UKT subsidies are six-sigma methods and linear equations by considering several economic aspects. The economic aspects to be considered are home ownership, Tax Object Sales Value (NJOP) if you own your own house, the costs incurred for the rent of the house when contracting, the electricity used, per capita income. Each economic aspect has a different contribution to the size of the UKT. NJOP, Rent, and electricity have a contribution of 20% to the large UKT. While per capita income contributes 60% to UKT. This is the reason for developing a new method of regression analysis. Regression analysis is a way to find the best relationship between UKT as a response and economic aspects as its predictors. The data used is economic data of ITB students. The number of students who apply for UKT subsidies is 949 people. In this final project, a multiple linear regression model with a model suitability level of more than 90% is obtained. Variable contribution is not always the same as the formula at the beginning. For example, NJOP : Electricity : capita originally 20 : 20 : 60 changed to 19.8% : 18.4% : 61.8%. The trust interval for each home ownership status obtained can be used as a reference to calculate the amount of UKT in the following year if the type of data and variables used are the same. |
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