IMPLEMENTATION OF THE SEM-PLS APPROACH TO ANALYZE THE IMPACT OF SOCIAL AID AND APBD ON POVERTY IN THE BOJONEGORO DISTRICT
Abstract
Poverty is the socio-economic condition of individuals or groups whose fundamental rights to maintain and develop a decent life are unmet. The poverty rate in Bojonegoro was 12.21% in 2022. In order to solve this problem, a poverty model is needed to serve as a reference for the further development of Bojonegoro district. This study aimed to determine the impact of social aid and APBD on poverty in Bojonegoro district. The methodology used in this study is his SEM-PLS quantitative research modeling of poverty using the WarpPLS application. The data sources for this study are the following secondary data in the form of Bojonegoro District Poverty Data, Area Appropriations Budget (APBD), and Social Aid (Bansos) from 2019 to 2022. Survey data were accessed online through the official website. Information from the Central Bureau of Statistics (BPS) and Satu Data Bojonegoro website. The results of this study show that SEM-PLS was applied correctly, and satisfactory results were obtained in terms of overall fit size, measured fit size, and structural fit size. The analysis results show that the variable APBD significantly impacts poverty with a proportion of -0.91. It means that the higher the realization of APBD, the lower the existing poverty rate. Social Aid variables up to -0.09 do not significantly impact poverty. It means that the amount of social benefits you receive does not affect poverty. The conclusion is that the factors that influence poverty in Bojonegoro district are its APBD variables.
Downloads
References
B. Rylko-Bauer and P. Farmer, “Structural Violence, Poverty, and Social Suffering,” in The Oxford Handbook of the Social Science of Poverty, Oxford University Press, 2017, pp. 47–74. doi: 10.1093/oxfordhb/9780199914050.013.4.
T. Kassahun, A. Tessema, and K. Adbib, “Analysis of rural household food and non‐food poverty status in Ethiopia: The Case Study from Meskan District,” Food Energy Secur., vol. 11, no. 2, May 2022, doi: 10.1002/fes3.363.
Andryan, S. S. Sururin, W. S. Akbar, and E. Widodo, “Peramalan Garis Kemiskinan Provinsi Daerah Istimewa Yogyakarta Menggunakan Metode Double Exponential Smoothing,” J. Ilmu Pendidik. Mat. Mat. dan Stat., vol. 3, no. 2, pp. 338–343, 2022, doi: 10.46306/Ib.v3i2.
I. Riyansuni and J. Devitra, “‘ Analisis Dan Perancangan Sistem Pendukung Keputusan Penerima Bantuan Pangan Non Tunai ( BPNT ) Dengan Simple Additive Weighting ( SAW ) Pada Dinas Sosial Kota Jambi ,’” Manaj. Sist. Inf., vol. 5, no. 1, pp. 151–163, 2020.
R. M. Titmuss, “The Social Division of Welfare,” in Essays on The Welfare State, Policy Press, 2018, pp. 17–30. doi: 10.51952/9781447349532.ch002.
L. Arisa and D. Yuningsih, “Planning and Preparation of The Operational Budget of The Investment Service Department,” J. Appl. Business, Tax. Econ. Res., vol. 2, no. 5, pp. 527–545, Jun. 2023, doi: 10.54408/jabter.v2i5.197.
S. Riyadi, S. Wijiastuti, and Darsono, “Analysis of the Effectiveness and Efficiency of the Realisation of the Regional Revenue and Expenditure Budget at the Regional Financial Management Agency of the District Wonogiri Period 2019 - 2021,” Int. J. Bus. Appl. Econ., vol. 2, no. 5, pp. 771–780, Sep. 2023, doi: 10.55927/ijbae.v2i5.5551.
Kemenkeu, “Peran APBN Berhasil Menahan Kenaikan Angka Kemiskinan,” Kementrisn Keuangan Republik Indonesia, 2023.
A. Sopiah, “Garis Kemiskinan 2022 Tertinggi dalam 9 Tahun Terakhir,” CNBC Indonesia, 2023.
Afifah, “Penurunan Kemiskinan Ekstrem Bojonegoro Lebih Besar dari Jatim dan Nasional di 2022,” 2022. https://bojonegorokab.go.id/berita/6875/penurunan-kemiskinan-ekstrem-bojonegoro-lebih-besar-dari-jatim-dan-nasional-di-2022 (accessed Jan. 07, 2023).
Nugroho, “Penurunan Angka Kemiskinan di Bojonegoro Masih Rendah,” Suarabanyuurip.com, 2022.
E. Febrianti, “Poverty Reduction In Bojonegoro Regency Based On Regional Autonomy Implementation,” J. Ilmu Sos. Mamangan, vol. 12, no. 1, pp. 251–261, Feb. 2023, doi: 10.22202/mamangan.v12i1.6440.
H. Fitriyah, E. M. Safitri, N. Muna, M. Khasanah, D. A. Aprilia, and D. Nurdiansyah, “IMPLEMENTASI ALGORITMA CLUSTERING DENGAN MODIFIKASI METODE ELBOW UNTUK MENDUKUNG STRATEGI PEMERATAAN BANTUAN SOSIAL DI KABUPATEN BOJONEGORO,” J. Lebesgue J. Ilm. Pendidik. Mat. Mat. Dan Stat., vol. 4, no. 3, pp. 1598–1607, 2023, doi: https://doi.org/10.46306/lb.v4i3.453.
R. Nabilah, D. Sugiri, P. Keuangan, and N. Stan, “Apakah Bantuan Sosial dan Belanja Modal Mempengaruhi Tingkat Kemiskinan Daerah di Provinsi Sumatera Selatan ?,” Media Pengkaj. Manajemn dan Akuntasi, vol. 21, no. 1, pp. 85–98, 2022, doi: 10.32639/fokbis.v21i1.115.
W. Hartanto, N. N. Islami, L. O. Mardiyana, F. A. Ikhsan, and A. Rizal, “Analysis of human development index in East Java Province Indonesia,” IOP Conf. Ser. Earth Environ. Sci., vol. 243, p. 012061, Apr. 2019, doi: 10.1088/1755-1315/243/1/012061.
R. N. Calheiros, E. Masoumi, R. Ranjan, and R. Buyya, “Workload Prediction Using ARIMA Model and Its Impact on Cloud Applications’ QoS,” IEEE Trans. Cloud Comput., vol. 3, no. 4, pp. 449–458, Oct. 2015, doi: 10.1109/TCC.2014.2350475.
A. Riyanti, “SEM-PLS Untuk Analisis Struktur Kemiskinan Di Provinsi Jawa Tengah Tahun 2017,” J. Math. Math. Educ., vol. 8, no. 1, pp. 46–55, 2018.
D. Nurdiansyah, “The Investigation of the Acceptance of Students Against Microsoft Teams Learning with the SEM- PLS Approach,” J. Pendidik. Mat. dan Mat., vol. 5, no. February, pp. 13–28, 2023.
E. D. Anggita, A. Hoyyi, and A. Rusgiyono, “Analisis Structural Equation Modelling Pendekatan Partial Least Square Dan Pengelompokan Dengan Finite Mixture PLS (Fimix-PLS) (Studi Kasus : Kemiskinan Rumah Tangga Di Indonesia 2017),” J. Gauss, vol. 8, no. 1, pp. 35–45, 2019.
Suharto and F. Ligery, ANALISIS SEM. 2018.
G. Dash and J. Paul, “CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting,” Technol. Forecast. Soc. Change, vol. 173, p. 121092, Dec. 2021, doi: 10.1016/j.techfore.2021.121092.
W. Kusuma, R. N. Sindy Setiawan, K. Verma, and C. F. Utomo, “Structural Equation Modeling-Partial Least Square for Poverty Modeling in Papua Province,” J. Varian, vol. 4, no. 2, pp. 79–90, Apr. 2021, doi: 10.30812/varian.v4i2.852.
N. Ardi and Isnayanti, “Structural Equation Modelling-Partial Least Square to Determine the Correlation of Factors Affecting Poverty in Indonesian Provinces,” IOP Conf. Ser. Mater. Sci. Eng., vol. 846, no. 1, p. 012054, May 2020, doi: 10.1088/1757-899X/846/1/012054.
Copyright (c) 2025 Denny Nurdiansyah, Diah Ayu Novitasari, Sari Lestari Zainal Ridho, Muchammad Chandra Cahyo Utomo, Dewi Putri Nur Oktafiya
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this Journal agree to the following terms:
- Author retain copyright and grant the journal right of first publication with the work simultaneously licensed under a creative commons attribution license that allow others to share the work within an acknowledgement of the work’s authorship and initial publication of this journal.
- Authors are able to enter into separate, additional contractual arrangement for the non-exclusive distribution of the journal’s published version of the work (e.g. acknowledgement of its initial publication in this journal).
- Authors are permitted and encouraged to post their work online (e.g. in institutional repositories or on their websites) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published works.
1.gif)
