Aji, Wahyu Pangestu (2018) Pemodelan Faktor-Faktor Yang Mempengaruhi Keparahan Kemiskinan Di Indonesia Pada Tahun 2015 Menggunakan Regresi Nonparametrik Spline Truncated. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Masalah kemiskinan adalah masalah kritis yang harus ditangani demi tercapainya pembangunan nasional. Badan Pusat Statistik menetapkan indikator-indikator yang menjadi dasar tolak ukur kemiskinan salah satunya adalah Indeks Keparahan Kemiskinan (Poverty Severity Index-P2). Indeks Keparahan Kemiskinan adalah ukuran rata-rata ketimpangan pengeluaran setiap penduduk miskin pada garis kemiskinan.. Pada tahun 2014 Indeks Keparahan Kemiskinan sebesar 43 % sedangkan pada tahun 2015 meningkat menjadi 52%.. Untuk mengatahui faktor-faktor yang menjadi penyebab tingginya angka Indeks Keparahan Kemiskinan di Indonesia maka digunakan sebuah metode statistik. Metode statistik yang bisa digunakan untuk mengatasi masalah ini adalah regresi nonparamerik. Menurut (Eubank,1988) regresi nonparametrik adalah metode regresi yang digunakan ketika kurva regresinya tidak diketahui sehingga mempunyai fleksibelitas tinggi dan dapat menyesuaikan diri terhadap karakteristik lokal suatu data.. Pemodelan ini menghasilkan koefisien determinasi sebesar 93%
================================================================================================================== The problem of poverty is a critical issue that must be addressed in order to achieve national development. Central Bureau of Statistics has set the indicators that become the basis of poverty benchmarks one of them is the Poverty Severity Index (P2). Poverty Severity Index is a measure of the average inequality of spending of each poor on the poverty line. The higher the index value of poverty severity, the higher the inequality of expenditure among the poor. In 2014 the Poverty Severity Index is 43% while in 2015 the Poverty Severity Index of Indonesia increases to 52%. Of course, the increase of Poverty Severity Index from 2014 to 2015 is caused by various factors. These factors need to be known so that it can be used as a reference to handle the severity of poverty in Indonesia. To know the factors that cause the high number of Poverty Severity Index in Indonesia then used a statistical method. Statistical methods that can be used to overcome this problem is nonparamerik regression. This method can be recommended because according to (Eubank, 1988) nonparametric regression is a regression method used when the regression curve is unknown so that it has high flexibility and can adapt to the local characteristics of a data. This modelling has 93% determination coeficient.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | RSSt 519.54 Aji p |
| Uncontrolled Keywords: | index of poverty severity; spline truncated nonparametric regression |
| Subjects: | H Social Sciences > HA Statistics H Social Sciences > HA Statistics > HA31.3 Regression. Correlation Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression |
| Divisions: | Faculty of Mathematics, Computation, and Data Science > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Wahyu Pangestu Aji |
| Date Deposited: | 26 Apr 2018 01:42 |
| Last Modified: | 30 Jun 2020 07:35 |
| URI: | http://repository.its.ac.id/id/eprint/51114 |
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