Pemodelan Indeks Kebahagiaan di Indonesia Berdasarkan Pendekatan Mixed Geographically Weighted Regression
DOI:
https://doi.org/10.33379/gtech.v8i1.3639Keywords:
Happiness Index, Mixed Geographically Weighted Regression, Modelling, R^2, SDGsAbstract
The well-being of society, involving the fulfilment of basic needs and opportunities for education and employment, can be measured through the happiness index. This research aims to assist the Indonesian government in achieving Sustainable Development Goal 3 related to Health and Well-being. It is hoped that by comprehending these factors, the government can improve the health and well-being of the Indonesian population. The happiness index varies across different geographical regions due to factors such as culture, social dynamics, and the environment, which can have different impacts from one region to another. Given the randomness in data patterns stemming from the diverse provinces in Indonesia, this study employs the Mixed Geographically Weighted Regression (MGWR) method. Results reveal that the MGWR model, utilizing a fixed Gaussian kernel weight, yields the lowest Akaike’s Information Criterion Corrected and the highest at 87.2%, underscoring its precision in modeling the happiness index in Indonesia.
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Copyright (c) 2023 Alfredi Yoani, Fina Insyiroh, Leni Sartika Panjaitan, Toha Saifudin, Suliyanto
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