PEMILIHAN MODEL TERBAIK SPATIAL AUTOREGRESSIVE MODEL (SAR), SPATIAL ERROR MODEL (SEM) DAN GENERAL SPATIAL MODEL (GSM) PADA REGRESI SPASIAL DENGAN MATRIKS PEMBOBOT QUEEN CONTIGUITY (STUDI KASUS: FAKTOR-FAKTOR YANG MEMPENGARUHI INDEKS KEDALAMAN KEMISKINA

Rifa’i Roziqin, NIM.: 20106010004 (2024) PEMILIHAN MODEL TERBAIK SPATIAL AUTOREGRESSIVE MODEL (SAR), SPATIAL ERROR MODEL (SEM) DAN GENERAL SPATIAL MODEL (GSM) PADA REGRESI SPASIAL DENGAN MATRIKS PEMBOBOT QUEEN CONTIGUITY (STUDI KASUS: FAKTOR-FAKTOR YANG MEMPENGARUHI INDEKS KEDALAMAN KEMISKINA. Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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	Text (PEMILIHAN MODEL TERBAIK SPATIAL AUTOREGRESSIVE MODEL (SAR), SPATIAL ERROR MODEL (SEM) DAN GENERAL SPATIAL MODEL (GSM) PADA REGRESI SPASIAL DENGAN MATRIKS PEMBOBOT QUEEN CONTIGUITY (STUDI KASUS: FAKTOR-FAKTOR YANG MEMPENGARUHI INDEKS KEDALAMAN KEMISKINA) 20106010004_BAB-II_sampai_SEBELUM-BAB-TERAKHIR.pdf - Published Version Restricted to Registered users only Download (4MB) | Request a copy

Abstract

Spatial regression is a development of classical linear regression which is based on the influence of location on the data being analysed and provides more precise predictions by utilizing geographic patterns. This research will discuss the selection of the best method Spatial Autoregressive Model (SAR), which handles direct spatial dependence in the dependent variable, Spatial Error Model (SEM), which handles dependence in the error term, and General Spatial Model (GSM), which is a combination of SAR and SEM using Queen Contiguity weighting matrix to determine which model is the best in analysing factors that can reduce poverty by using the best model based on the Akaike's Information Criteria (AIC) value in a case study of factors that influence the Poverty Depth Index in Districts/Cities in East Java Province in 2023. The aim of this research is to compare the best methods for SAR, SEM and GSM using the Queen Contiguity weighting matrix. Based on the analysis in this research, it can be concluded that the GSM model using the Queen Contiguity weighting matrix is the best model because it has the smallest AIC value, namely -123.0501 in modelling a case study in the form of factors that influence the Poverty Depth Index in Districts/Cities in East Java Province in 2023. The results of this analysis are the number of poor people, the percentage of poor people, the poverty line, the index Human development, the human severity index influences the poverty depth index.

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