Pemodelan penerima bantuan sosial masyarakat kota Surabaya tahun 2021 menggunakan metode regresi logistik multinominal

Hartono, Muhammad Ekki (2022) Pemodelan penerima bantuan sosial masyarakat kota Surabaya tahun 2021 menggunakan metode regresi logistik multinominal. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Masyarakat Surabaya yang membutuhkan bantuan akan berstatus MBR atau Masyarakat Berpenghasilan Rendah. Bantuan yang diberikan kepada MBR di antaranya BPNT dan PKH. Permasalahan yang terjadi adalah tidak meratanya bantuan yang diterima oleh MBR. Untuk mengatasi permasalahan tersebut, dilakukan penelitian ini untuk melihat hubungan antara masyarakat berstatus MBR yang menerima bantuan sosial dengan variabel yang diduga memengaruhinya. Hasil analisis yang dilakukan diketahui bahwa variabel yang memiliki pengaruh signifikan terhadap penerimaan bantuan sosial adalah variabel desil, usia, dan pekerjaan. Karakteristik data MBR Surabaya yang berstatus desil 1 menerima BPNT dan PKH terbanyak, dengan pekerjaan lainnya seperti pelaut, ibu rumah tangga, dan lain-lain, sedangkan MBR penerima BPNT dan PKH terendah adalah desil 3 dan desil 4 yang tidak memiliki pekerjaan. Kategori usia tertinggi penerima BPNT dan PKH adalah yang berusia 31–59 tahun, sedangkan MBR penerima BPNT dan PKH terendah berada pada usia ≤ 20 tahun. Peluang jika seorang MBR yang berstatus desil 1, berusia 21–30 tahun, dengan pekerjaan karyawan/pegawai/buruh untuk menerima BPNT dan PKH masing-masing sebesar 0,023 dan 0,138\. Peluang lainnya, jika seorang MBR yang berstatus desil 1, berusia 31–45 tahun, dan tidak bekerja, untuk menerima BPNT dan PKH masing-masing sebesar 0,046 dan 0,248. Hasil ketepatan klasifikasi model yang didapatkan antara hasil observasi dan prediksi sebesar 67,7%.
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The people of Surabaya who need assistance are classified as MBR, or low-income people. The assistance provided to MBR includes BPNT and PKH. The problem that occurs is the unequal distribution of assistance received by MBR. To overcome this problem, this study was conducted to examine the relationship between MBR recipients of social assistance and the variables suspected of influencing it. The results of the analysis revealed that the variables that had a significant influence on the receipt of social assistance were decile, age, and occupation. The characteristics of MBR data in Surabaya showed that those classified in decile 1 received the most BPNT and PKH, with various occupations such as seafarers, housewives, and others, while the lowest number of BPNT and PKH recipients were those in deciles 3 and 4 who were unemployed. The highest age category among BPNT and PKH recipients was those aged 31–59 years, while the lowest number of MBR recipients of BPNT and PKH were those aged ≤ 20 years. The probability that an MBR classified in decile 1, aged 21–30 years, and employed as an employee or laborer would receive BPNT and PKH was 0.023 and 0.138, respectively. Another probability was that an MBR classified in decile 1, aged 31–45 years, and unemployed would receive BPNT and PKH with probabilities of 0.046 and 0.248, respectively. The model classification accuracy, based on the comparison between observed and predicted results, was 67.7%.

Item Type:	Thesis (Other)
Additional Information:	519.536 Har p-1
Uncontrolled Keywords:	Bantuan Sosial, Masyarakat Berpenghasilan rendah, Regresi Logistik Multinomial, Social Assistance, Low-Income Communities, Multinomial Logistic Regression
Subjects:	Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression
Divisions:	Faculty of Vocational > 49501-Business Statistics
Depositing User:	magang .
Date Deposited:	05 Oct 2026 06:51
Last Modified:	05 Oct 2026 06:51
URI:	http://repository.its.ac.id/id/eprint/145263

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