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Journal : JTAM (Jurnal Teori dan Aplikasi Matematika)

Panel Data Spatial Regression Modeling with a Rook Contiguity Weighting Function on the Human Development Index in West Sumatera Province Arum, Prizka Rismawati; Anggraini, Lisa; Nur, Indah Manfaati; Purnomo, Eko Andy
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 1 (2024): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i1.16675

Abstract

The achievement of the level of welfare of a region or country can be seen from the level of human development as measured by the Human Development Index (HDI). West Sumatra is one of the provinces with HDI achievements above the national average. However, there are still regencies/cities in West Sumatra Province that have HDI achievements below the national average and HDI achievements in West Sumatra Province Regencies/Cities have changed in 2017-2021. Therefore, in this study, spatial analysis of panel data was used. The aim of this research is to find out the general description of the HDI of West Sumatra Province, obtain a panel data spatial regression model and obtain variables that significantly influence on HDI in West Sumatra Province 2017─2021because differences in HDI achievement were suspected to have influences from areas that were side by side and the area was observed more than once. The model formed from this analysis using the rook contigutiy weighting function is Random Effect Spatial Autoregressive because the spatial interactions formed in human development index data in West Sumatra Province are real at lag. This model is a suitable model based on panel spatial model selection and has an R2 value of 92.94%. Analysis of human development index data in regencies/cities in West Sumatra Province using spatial regression panel data obtained results that expectations of school length (X1), average length of schooling (X2), and population density (X3) significantly directly influenced the human development index in regencies/cities in West Sumatra Province.  
Rainfall Forecasting Using an Adaptive Neuro-Fuzzy Inference System with a Grid Partitioning Approach to Mitigating Flood Disasters Fauzi, Fatkhurokhman; Erlinda, Relly; Arum, Prizka Rismawati
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 2 (2024): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i2.20385

Abstract

Hydrometeorological disasters are one of the disasters that often occur in big cities like Semarang. Hydrometeorological disasters that often occur are floods caused by high-intensity rainfall in the area. Early mitigation needs to be done by knowing about future rain. Rainfall data in Semarang City fluctuates, so the Adaptive Neuro-Fuzzy Inference System (ANFIS) method approach is very appropriate. This research will use the Grid Partitioning (GP) approach to produce more accurate forecasting. The data used in this research is daily rainfall observation data from the Meteorology Climatology Geophysics Agency (BMKG). The membership functions used are Gaussian and Generalized Bell. The two membership functions will be compared based on the RMSE and MAPE values to get the best one. The data used in this research is daily rainfall data. Rainfall in Semarang City every month experiences anomalies, which can result in flood disasters. The ANFIS-GP method with a Gaussian membership function is the best, with an RMSE value of 0.0898 and a MAPE of 5.2911. Based on the forecast results for the next thirty days, a rainfall anomaly of 102.53 mm on the thirtieth day could cause a flood disaster.