Septiadi, Moch. Wahyu (2025) Pemodelan Persentase Penduduk Miskin di Provinsi Aceh Menggunakan Regresi Nonparametrik Spline Truncated. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Kemiskinan adalah masalah kompleks yang menjadi tantangan utama dalam pencapaian Sustainable Development Goals (SDGs). Provinsi Aceh menghadapi fluktuasi persentase penduduk miskin sejak 2020, dengan tren penurunan hingga mencapai 14,23% pada Maret 2024. Meski begitu, Aceh tetap berada di 10 besar provinsi dengan persentase kemiskinan tertinggi di Indonesia. Pemerintah Aceh diharapkan dapat fokus menerapkan kebijakan efektif untuk mendukung target nasional penurunan kemiskinan sebesar 7,5% pada 2024 sesuai dengan Rencana Pembangunan Jangka Menengah Nasional (RPJMN) 2020–2024. Dalam penelitian ini, pemodelan dilakukan terhadap persentase penduduk miskin di Provinsi Aceh menggunakan analisis regresi nonparametrik spline truncated. Pendekatan tersebut dipilih karena hubungan antara persentase penduduk miskin dan variabel-variabel yang diduga berpengaruh tidak mengikuti pola tertentu serta cenderung berubah di setiap sub-interval. Kemudian, variabel-variabel prediktor yang digunakan dalam analisis meliputi PDRB per kapita, rata-rata lama sekolah, tingkat pengangguran terbuka, dan laju pertumbuhan penduduk. Pemilihan model regresi nonparametrik spline truncated terbaik dilakukan dengan menentukan titik knot optimum berdasarkan nilai Generalized Cross Validation (GCV) minimum. Hasil penelitian menunjukkan bahwa titik knot optimum yang terpilih pada model terbaik adalah tiga knot, dengan tetap melibatkan keempat variabel prediktor karena memiliki pengaruh yang signifikan terhadap persentase penduduk miskin di Provinsi Aceh. Kemudian, koefisien determinasi yang dihasilkan oleh model terbaik sebesar 99,143%.
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Poverty is a complex issue and a major challenge in achieving the Sustainable Development Goals (SDGs). Aceh Province has experienced fluctuations in the percentage of its poor population since 2020, with a declining trend reaching 14.23% in March 2024. However, Aceh remains among the top 10 provinces with the highest poverty rates in Indonesia. The Aceh government is expected to focus on implementing effective policies to support the national poverty reduction target of 7.5% by 2024, as outlined in the National Medium-Term Development Plan (RPJMN) 2020–2024. This study models the percentage of poor people in Aceh Province using nonparametric truncated spline regression analysis. This approach was chosen because the relationship between poverty and the predictor variables does not follow a specific pattern and tends to vary across sub-intervals. The predictor variables used in the analysis include GDP per capita, average years of schooling, open unemployment rate, and population growth rate. The selection of the best nonparametric truncated spline regression model was based on the minimum value of Generalized Cross Validation (GCV). The results show that the optimal knot points for the best model are three knots, while all four predictor variables were retained in the model due to their significant influence on the poverty percentage in Aceh Province. The best model achieved a coefficient of determination of 99.143%.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Generalized Cross Validation, Koefisien Determinasi, Persentase Penduduk Miskin, Regresi Nonparametrik Spline Truncated, Rencana Pembangunan Jangka Menengah Nasional, Sustainable Development Goals, Coefficient of Determination, Generalized Cross Validation, National Medium-Term Development Plan, Nonparametric Truncated Spline Regression, Percentage of Poor Population, Sustainable Development Goals. |
| Subjects: | H Social Sciences > H Social Sciences (General) H Social Sciences > HA Statistics > HA31.3 Regression. Correlation. Logistic regression analysis. H Social Sciences > HA Statistics > HA31.7 Estimation |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Moch. Wahyu Septiadi |
| Date Deposited: | 01 Feb 2025 08:13 |
| Last Modified: | 01 Feb 2025 08:13 |
| URI: | http://repository.its.ac.id/id/eprint/117409 |
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