The Spatial Lag X Method Using Three Types of Distance Weighting in Food Security Data Analysis in Central Sulawesi
DOI:
https://doi.org/10.55927/modern.v4i1.13266Keywords:
Food Security, Spatial Lag X, Inverse Distance Weighting, Exponential Distance Decay, Double Power Distance Weights WeightingAbstract
Food security is a critical global issue due to rapid population growth and the increasing impacts of climate change. This study aims to analyze food security and identify spatial patterns among regions in Central Sulawesi in 2022. A Spatial Lag X method was applied, enhanced with three distance weighting techniques: Inverse Distance Weighting (IDW), Exponential Distance Decay (EXP), and Double Power Distance (DPD). These were used to assess the spatial influence on food security data, sourced from the Central Sulawesi Statistics Bureau. The Spatial Lag X approach integrates neighboring regions’ variables to explain the dependent variable. The findings reveal that with IDW and EXP weights at a 10% significance level, no variables significantly influenced the Food Security Index. However, using DPD weights, Gross Regional Domestic Product (GRDP) per capita at current prices (X4) significantly influenced the Food Security Index at a 10% level. The DPD-weighted Spatial Lag X model was identified as the best model for analyzing food security in Central Sulawesi in 2022, achieving an AIC value of 23.91885 and an R² of 0.9977. This study highlights the importance of spatial factors in understanding regional food security dynamics.
Downloads
References
Alamsyar, A. (2022). Damak alih fungsi lahan padi sawah tergapad ketahanan Pangan di Kabupaten. Agrotekbis : E- Jurnal Ilmu Pertanian, 10(1),176-185.
BPS, T. (2022). Provinsi Sulawesi Tengah. Sulawesi Tengah: Palu.
BPS, T. (2022). Provinsi Sulawesi Tengah Dalam Angka 2022. Sulawesi Tengah: Palu.
DP, P. R. (2018). Perbandingan Metode Spatial Lag X, Spatial Autogressive Model, dan Spatial Error Model untuk Faktor-Faktor yang mempengaruhi Kemiskinan di Jawa Tengah. Semarang: Diss.
Hanafie, R. (2010). Penyediaan pangan yang aman dan berkelanjutan guna mendukung tercapainya ketahanan pangan. JSEP(Journal of Social and Agricultural Economics0, 4(3), 38-43.
Hanafie, R. (2010). Penyediaan pangan yang aman dan berkelanjutan guna mendukung tercapainya ketahanan pangan. JSEP(Journal of Social and Agricultural Economics), 4(3),38-43.
Iriyani, A. B. (2022). Pengaruh Biaya Lingkungan dan Pengungkapan Kinerja Lingkungan terhadap Profitabilitas . Malang: Doctoral dessertation.
Nugraha, B. (2022). Implementasi metode regresi linear berganda dengan pertimbangan uji asumsi klasik. Pengembangan uji statistika, 34-45.
Punggodewi, P. &. (2020). Pemodelan faktor-faktor yang mempengaruhi indeks ketahanan pangan dengan menggunakan pendekatan multivariate adaptive regression spline(Mars). Jurnal Statistika Industri dan Komputasi, 5(01),93-106.
Soinbala, E. K. (2023). Perbandingan Metode Spatial Lag X, Spatial Autogressive Model dan Spatial error Model untuk faktor-faktor yang mempengaruhi tingkat pengangguran terbuka di Provinsi NTT. Jurnal Statistika Industri dan Komputasi,, 38-47.
Tobari, T. (2008). PROFIL PENGEMBANGAN TANAMAN PANGAN DI KECAMATAN CILCAP JAWA TENGAH. Agrin, 12(2).
Wehantouw, D. V. (2021). Analisis Faktor-Faktor yang Mempengaruhi Tingkat Ketahanan Pangan di Provinsi Sulawesi Utara. Jurnal Pembangunan Ekonomi Dan Keuangan Daerah,, 22(3),132-151.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Roselina Lucia Ketty Mbete, Miswanto, Frasto Biyanto, Baldric Siregar

This work is licensed under a Creative Commons Attribution 4.0 International License.