Pendekatan Regresi Spline Multivariabel untuk Pemodelan Indeks Ketahanan Pangan Provinsi Sumatera Utara

  • Zulaika Zulaika Universitas Islam Negeri Sumatera Utara
  • Hendra Cipta Universitas Islam Negeri Sumatera Utara
  • Machrani Adi Putri Siregar Universitas Islam Negeri Sumatera Utara
Keywords: Food Security Index, Nonparametric Regression Spline, Knot Point

Abstract

Food security is a condition where food is fulfilled for a household which is reflected in the availability of sufficient food both in terms of quantity and quality, safe, and equitable and affordable. In Government Regulation No. 38 of 2007 Food security has become a basic prerequisite that must be owned by autonomous regions where food security is a mandatory matter for the central, provincial, and district / city governments. To measure the food security of a region, the Government makes an indicator in looking at the achievement of food security of a region. This indicator is the Food Security Index. For this reason, it is necessary to conduct an analysis to model factors related to food security through the Food Security Index to see how much these factors contribute to the ups and downs of the Food Security Index. One statistical method that can explain the relationship between predictor variables and response variables is spline nonparametric regression analysis. Spline is an approach towards matching data while taking into account the smoothness of curves. Splines have the advantage of overcoming data patterns that show sharp rises / downs with the help of knot points, and the resulting curve is relatively smooth. The research objective of this study was to determine the modeling of the Food Security Index in North Sumatra using the Multivariable Spline Regression Method. Based on the analysis that has been done, a spline regression model for the Food Security Index in North Sumatra was obtained at three knot points with a minimum GCV value of 27.39 and R^2 is 92.76%.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

References

Afa, Ihdayani Banun. Suparti. Rita, Rahmawati. 2018. Pemodelan Indeks Harga Saham Gabungan Menggunakan Regresi Spline Multivariabel. Jurnal Gaussian. 7(3) : 260-269

Afriani, Ricka. 2022. Penduga Harga Cabai dengan Model Regresi Spline di Kota Medan. Journal of Maritime and Education. 4(1) : 364-367

Aryati, N.L.G.S. I Komang, G.S. I Gusti, A.M.S. 2021. Pemodelan Rata-Rata Lama Sekolah Menggunakan Pendekatan Regresi Nonparametrik Spline Multivariabel. E-Jurnal Matematika, 10(2). 53-58

Badan Ketahanan Pangan (2014). Badan Ketahanan Pangan. diambil dari Kementrian Pertanian Republik Indonesia : bkp.pertanian.go.id

Litawati, Elfrida Kurnia. I Nyoman, Budiantara. 2013. Pendekatan Regresi Nonparametrik Spline Untuk Pemodelan Laju Pertumbuhan Ekonomi (LPE) di Jawa Timur. Jurnal Sains dan Seni Pomits. 2(2) : 123-128

Megawati. Bahriddin, Abapihi. Irma, Yahya. Ruslan. Lilis, Laome. Mukhsar. 2022. Pemodelan Angka Morbiditas dengan Menggunakan Regresi Nonparametrik Spline di Indonesia. Prosiding Seminar Nasional Sains dan Terapan. 79-84

Mubarak, Reza. I Nyoman, Budiantara. 2012. Analisis Regresi Spline Multivariable untuk Pemodelan Kematian Penderita Demam Berdarah Dengue (DBD) di Jawa Timur. Jurnal Sains dan Seni ITS. 1(1) : 224-229

Nisa, Azizatun. Makkulau. Lilis, L. Edi, C. Norma, M. 2022. Pemodelan Indeks Harga Konsumen Dengan Regresi Nonparametrik Spline Multivariabel. Jurnal Matematika, Komputasi dan Statistika. 2(1). 1-5

Prahutama, Alan. Tiani, W.U. Rezy, Eko. Dede, Zumrohtuliyosi. 2014. Pemodelan Inflasi Berdasarkan Harga-Harga Pangan Menggunakan Spline Multivariabel. Media Statistika. 7(2). 89-94

Punggodewi, Prismakawa. Noviana, Pratiwi. 2020. Pemodelan Faktor-Faktor Yang Mempengaruhi Indeks Ketahanan Pangan dengan Menggunakan Pendekatan Multivariabel Adaptive Regression Spline (MARS). Jurnal Statistika Industri dan Komputasi. 5(1) : 93-106

Rumana Sari, S. U. 2017. Perbandingan Model Regresi Nonparametrik Spline Multivariabel dengan Menggunakan Metode Generalized Cross Validation (GCV) dan Metode Unbiassed Risk (UBR) dalam Pemilihan Titik Knot Optimal. Prosiding SI MaNIs. 1(1) : 154-166

Saputro, Wahyu Adhi. Yuli, Fidayani. 2020. Faktor-Faktor Yang Mempengaruhi Ketahanan Pangan Rumah Tangga Petani di Kabupaten Klaten. Jurnal Agribisnis Sumatera Utara. 13(2) : 115-123

Sari, R. S. I Nyoman, Budiantara. 2012. Pemodelan Pengangguran Terbuka di Jawa Timur dengan Menggunakan Pendekatan Regresi Spline Multivariabel. Jurnal Sains dan Seni ITS. 1(1) : 236-241

Tono. 2021. Indeks Ketahanan Pangan 2021. Hal 3-5

Veronioka, Herlina. Setia, N.L. Bilter, S. 2021. Analisis Konsumsi Rumah Tangga Rawan Pangan di Kota Medan. Jurnal Darma Agung. 29(3). 393-403

Wahyuningsih, T, Dian. Sri, S.H. Indriati, Diari, I. 2018. Penerapan Generalized Cross Validation dalam Model Regresi Smoothing Spline Pada Produksi Ubi Jalar di Jawa Tengah. Indonesian Jurnal Of Applied Statistic. 1(2). 117-125

Published
06-05-2024
How to Cite
Zulaika, Z., Cipta, H., & Siregar , M. A. P. (2024). Pendekatan Regresi Spline Multivariabel untuk Pemodelan Indeks Ketahanan Pangan Provinsi Sumatera Utara. Proximal: Jurnal Penelitian Matematika Dan Pendidikan Matematika, 7(1), 387-400. https://doi.org/10.30605/proximal.v7i2.3666

Most read articles by the same author(s)