Comparing and Analysis of Geospatial Interpolation Prediction Algorithm: Case Study The Quality of Education of Malang and Batu City, Indonesia
DOI:
https://doi.org/10.25126/jitecs.202271373Abstract
Abstract. The number of schools in Indonesia continues to grow. This must also be balanced with improving the quality of education in accordance with the objectives of the 4 SDGs, which as a whole are to improve the quality of education that is inclusive, equitable and provides lifelong learning opportunities. However, until now it is very difficult to determine differences in the quality of education in an area. From the problem of education quality and education equity, it is necessary to have a regional analysis of the quality of education. This analysis can be performed using various geospatial interpolation methods. Geospatial Interpolation is a technique to find the value of a missing variable in a known data range in an area. The data used for the Geospatial interpolation process in this study are School Quality data taken through research questionnaires, as well as school accreditation data at the junior high school level. The geospatial interpolation method used in this study is the Inverse Distance Weighted, Spline, Kriging and Natural Neighbor methods. The use of different interpolation methods can indicate the best method for this research case study. Measurement validation results from each geospatial interpolation method using RMSE. From the results of this accuracy validation, the most accurate method will be obtained in determining the quality of education contained in an area.
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