Izza, M. Ridhlotul (2023) Pemodelan Status Ketahanan Pangan di Indonesia Tahun 2021 Menggunakan Metode Regresi Logistik Ridge. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Pangan merupakan kebutuhan dasar manusia yang harus dipenuhi. Kebijakan tentang pangan di Indonesia diatur dalam Undang-Undang No.18 Tahun 2012. Peta Ketahanan dan Kerentanan Pangan (FSVA) merupakan salah satu program pemerintah yang dilaksanakan dalam rangka mewujudkan kedaulatan dan kemandirian pangan. Terdapat tiga pilar utama yang digunakan untuk mengukur Food Security and Vulnerability, yaitu pilar ketersediaan, pilar keterjangkauan, dan pilar pemanfaatan dimana faktor-faktor dalam setiap pilar memiliki kecenderungan tinggi untuk terjadi kasus multikolinearitas. Adanya kasus multikolinearitas menyebabkan variansi dari hasil estimasi parameter menjadi besar yang berakibat pada banyaknya variabel prediktor tidak signifikan. Untuk mengatasi hal tersebut digunakan metode Regresi Logistik Ridge dalam pemodelan status ketahanan pangan di Indonesia. Terdapat dua variabel yang berpengaruh signifikan terhadap status ketahanan pangan di Indonesia, yaitu gini ratio (X2) dan persentase rumah tangga tanpa akses listrik (X4). Dari hasil model terbaik Regresi Logistik Ridge didapatkan ketepatan klasifikasi 75,87%.
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Food is a fundamental human necessity that requires fulfillment. The policies governing food in Indonesia are stipulated in UU No. 18 Tahun 2012. The Food Security and Vulnerability Map (FSVA) is a government program implemented to achieve food sovereignty and self-sufficiency. Food Security and Vulnerability are measured through three primary pillars: availability, affordability, and utilization. These pillars exhibit a high tendency for multicollinearity, wherein factors within each pillar may display a correlation. Multicollinearity can lead to an increased variance in parameter estimation, resulting in a larger number of non-significant predictor variables. To address this issue, the Ridge Logistic Regression method is utilized for modeling the food security status in Indonesia. Two variables, namely the Gini ratio (X2) and the percentage of households without access to electricity (X4), significantly influence the food security status in Indonesia. From the results of the best Ridge Logistic Regression model, the classification accuracy is 75.87%.
Item Type: | Thesis (Other) |
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Uncontrolled Keywords: | FSVA, Ketahanan Pangan, Multikolinearitas, Regresi Logistik Ridge. Food Security, FSVA, Multicollinearity, Ridge Logistic Regression. |
Subjects: | Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression |
Divisions: | Faculty of Mathematics and Science > Statistics > 49201-(S1) Undergraduate Thesis |
Depositing User: | Izza M Ridhlotu |
Date Deposited: | 15 Sep 2023 06:42 |
Last Modified: | 15 Sep 2023 06:42 |
URI: | http://repository.its.ac.id/id/eprint/104502 |
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