Zakaria, Rifki (2025) Pemodelan Pertumbuhan Ekonomi di Indonesia Menggunakan Geographically Weighted Regression. Diploma thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Pertumbuhan Ekonomi menjadi salah satu permasalahan yang harus diperhatikan dalam menghadapi tantangan ketidakpastian dan dinamika global. Pertumbuhan Ekonomi menjadi kunci dalam pembangunan sebuah negara. Namun, Pertumbuhan Ekonomi di Indonesia sangat berfluktuatif pada masing-masing wilayah karena pengaruh dari beberapa faktor baik internal maupun eksternal. Faktor internal meliputi ketidakstabilan kebijakan pemerintah, ketidakmerataan pembangunan, dan lain-lain, Sedangkan faktor eksternal seperti ekonomi global yang tidak menentu yang memiliki karakteristik yang berbeda tiap wilayah nya. Hal tersebut, dapat mendorong pada pemerintah setiap provinsi atau lingkup nasional dalam upaya meningkatkan Pertumbuhan Ekonomi guna mencapainya stabilitas Pertumbuhan Ekonomi nasional dan keberhasilan pembangunan nasional. Oleh karena itu, dilakukan penelitian untuk mengetahui faktor-faktor yang memengaruhi Pertumbuhan Ekonomi pada tahun 2023 di Indonesia menggunakan motode Geographically Weighted Regression dengan harapan dapat mengetahui faktor yang mempengaruhi Pertumbuhan Ekonomi dengan memperhatikan aspek spasial serta dapat meningkatkan faktor yang dapat meningkatkan Pertumbuhan Ekonomi. Berdasarkan hasil penelitian yang dilakukan, Model RLB memperoleh nilai kebaikan model (R2) sebesar 14,14% dimana persentase kebaikan model tersebut terbilang kecil karena tidak mampu menjelaskan variabilitas Pertumbuhan Ekonomi lebih dari 50%. Model GWR memperoleh nilai kebaikan model (R2) sebesar 32,58% dimana persentase kebaikan model tersebut terbilang kecil karena tidak mampu menjelaskan variabilitas Pertumbuhan Ekonomi lebih dari 50%.
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Economic growth is one of the issues that must be considered in facing the challenges of uncertainty and global dynamics. Economic growth is key to a country's development. However, economic growth in Indonesia is highly fluctuating in each region due to the influence of several factors, both internal and external. Internal factors include the instability of government policies, uneven development, and others. While external factors such as the uncertain global economy that has different characteristics each year. This can encourage the government of each province or national level to increase economic growth in order to achieve national economic growth stability and national development success. Therefore, a study was conducted to determine the factors that influence economic growth in 2023 in Indonesia using the Geographically Weighted Regression method with the hope of identifying factors that influence economic growth by paying attention to spatial aspects and can improve factors that can increase economic growth. Based on the research results, the RLB Model obtained a goodness of fit model (R2) of 14.14%, where the percentage of goodness of the model is relatively small because it is unable to explain the variability of economic growth of more than 50%. The GWR Model obtained a goodness of fit model (R2) of 32.58%, where the percentage of goodness of the model is relatively small because it is unable to explain the variability of economic growth of more than 50%.
| Item Type: | Thesis (Diploma) |
|---|---|
| Uncontrolled Keywords: | Geographically Weighted Regression, Indonesia, Pertumbuhan Ekonomi, Economic Growth |
| Subjects: | Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression |
| Divisions: | Faculty of Vocational > 49501-Business Statistics |
| Depositing User: | Rifki Zakaria |
| Date Deposited: | 21 Jul 2026 05:09 |
| Last Modified: | 21 Jul 2026 05:09 |
| URI: | http://repository.its.ac.id/id/eprint/135233 |
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