@article{AHMAD_Raupong_2023, title={Estimation Of Parameter Regression Panel Data Model Using Least Square Dummy Variable Method}, volume={20}, url={https://journal.unhas.ac.id/index.php/jmsk/article/view/27530}, DOI={10.20956/j.v20i1.27530}, abstractNote={<p>Panel data regression is a set of techniques for modeling the effect of independent variable on the dependent variable of panel data. The parameter estimation in the panel data regression model used the least squares method, but the difference between the <em>intercept</em> and the <em>slope</em> could not be known between time and between <em>cross-section</em>. One of the methods used is the <em>Least Square Dummy Variable method</em> (LSDV). The LSDV method is a method that has the same stages as the least squares method, but uses <em>dummy</em> variable to get different <em>intercept</em> score. This research uses the LSDV method to explain the differences in <em>intercept</em> between <em>cross-sections</em> using balanced panel data, namely the Human Development Index (HDI) data in South Sulawesi 2011-2017 to get fixed effect panel data regression model parameters on that data and the regencies with Average Length of School (ALS) and Life Expectancy (LE) variable that has the most influence on HDI based on the coefficient of determination criteria. According to the results of this research, the score of the coefficient of determination in the panel data regression model using the fixed effect model in each cross-section (regency), there are also three regencies with the highest coefficient of determination, respectively, Gowa, Pare-pare and Bantaeng regency that ALS and LE are able to explain the HDI variables 98.942%, 98.089% and 97.444%.</p>}, number={1}, journal={Jurnal Matematika, Statistika dan Komputasi}, author={AHMAD, NUR AMINAH and Raupong, Raupong}, year={2023}, month={Sep.}, pages={221- 228} }