Pemodelan Indeks Ketahanan Pangan di Indonesia Dengan Metode Regresi Nonparametrik Spline Truncated

Maharani, Shafira Aisyah (2023) Pemodelan Indeks Ketahanan Pangan di Indonesia Dengan Metode Regresi Nonparametrik Spline Truncated. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Indonesia menempati peringkat keempat sebagai negara dengan jumlah penduduk terbesar di dunia pada tahun 2021, lebih tepatnya sebanyak 273.879.750 jiwa dan akan terus meningkat dari waktu ke waktu. Semakin banyak jumlah penduduk maka semakin besar pula kebutuhan akan pangan. Oleh sebab itu, ketahanan pangan menjadi prioritas utama dalam pembangunan mengingat pangan adalah kebutuhan paling dasar umat manusia. Ketahanan pangan dapat diartikan sebagai keadaan terpenuhinya pangan bagi suatu wilayah hingga perseorangan. Salah satu indikator yang dapat menggambarkan situasi pencapaian ketahanan pangan adalah IKP (Indeks Ketahanan Pangan). Terdapat 12 provinsi di Indonesia dengan nilai IKP di bawah rata-rata, sehingga situasi ketahanan pangan belum dapat dikatakan merata. Pada penelitian ini dilakukan pemodelan Indeks Ketahanan Pangan pada 34 provinsi di Indonesia menggunakan regresi nonparametrik spline truncated karena hubungan antara variabel respon dan prediktor tidak berpola atau terdapat perubahan pola perilaku pada sub interval tertentu. Model terbaik menggunakan titik knot optimal berdasarkan nilai GCV minimum. Data yang digunakan merupakan data sekunder yang dikeluarkan Badan Pusat Statistik dan Badan Ketahanan Pangan. Hasil penelitian menunjukkan bahwa model regresi nonparametrik spline truncated terbaik menggunakan 3 titik knot dengan nilai GCV 48,2753646 dan koefisien determinasi sebesar 84,9%. Adapun keempat variabel prediktor yang digunakan yaitu variabel persentase pengeluaran per kapita sebulan makanan, Tingkat Partisipasi Angkatan Kerja, Indeks Pembangunan Manusia, dan persentase rumah tangga dengan air minum layak berpengaruh signifikan terhadap IKP di Indonesia tahun 2021.
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Indonesia is ranked fourth as the country with the largest population in the world in 2021, more precisely as many as 273.879.750 people which continues to increase from time to time. The increased in population will be accompanied by an increase in the need for food. Therefore, food security is a top priority in development strategy, considering that food is the most basic need of humans. Food security can be interpreted as the condition of food fulfillment for an area to individuals. One indicator that can describe the situation of achieving food security is the IKP (Food Security Index). Three main aspects of food security are used as components in the calculation of IKP, namely availability, affordability, and utilization. There are 12 provinces in Indonesia with IKP values below average, so the food security situation cannot be said to be evenly distributed. In this study, Food Security Index modeling was carried out in 34 provinces in Indonesia using truncated spline nonparametric regression because the relationship between response variables and predictors was not patterned or there was a change in behavior patterns at certain sub-intervals. The best models use optimal knot points based on minimum GCV values. The data used is secondary data issued by the Central Bureau of Statistics and the Food Security Agency. The results showed that the best truncated spline nonparametric regression model used 3 knot points with a GCV value of 48,27536459 and a coefficient of determination of 84,9%. The four predictor variables used, namely the percentage of per capita expenditure on food a month, the Labor Force Participation Rate, the Human Development Index, and the percentage of households with adequate drinking water have a significant effect on the IKP in Indonesia 2021.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Indonesia, Food Security Index, Knot, Spline Truncated Nonparametric Regression, Indonesia, Ketahanan Pangan, Regresi Nonparametrik Spline Truncated.
Subjects:	Q Science > QA Mathematics
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User:	Shafira Aisyah Maharani
Date Deposited:	06 Sep 2023 01:29
Last Modified:	06 Sep 2023 01:29
URI:	http://repository.its.ac.id/id/eprint/104422

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