Peran Teknologi Informasi dan Komunikasi serta Kondisi Sosial Ekonomi terhadap Kemiskinan Indonesia
Abstract
Penelitian ini bertujuan mengetahui gambaran umum kemiskinan beserta faktor-faktor yang diduga memengaruhi kemiskinan dan mengidentifikasi faktor-faktor yang memengaruhi kemiskinan di Indonesia. Metode yang digunakan yaitu analisis regresi spasial data panel. Hasil penelitian menemukan bahwa terdapat efek spasial pada kemiskinan di Indonesia. Indeks Pembangunan TIK (IP-TIK), persentase pengguna telepon seluler, dan indeks pembangunan manusia (IPM) signifikan menurunkan tingkat kemiskinan di Indonesia. Sebaliknya, angka buta huruf dan tingkat pengangguran terbuka signifikan meningkatkan tingkat kemiskinan di Indonesia. Oleh karena itu, selain dari sisi sosial ekonomi juga perlu menjadikan TIK sebagai bagian penting dari strategi pembangunan yang lebih luas untuk mengentaskan kemiskinan di Indonesia.
References
Abisuga-Oyekunle, O. A., Patra, S. K., & Muchie, M. (2020). SMEs in sustainable development: Their role in poverty reduction and employment generation in sub-Saharan Africa. African Journal of Science, Technology, Innovation and Development, 12(4), 405-419. doi: https://doi.org/10.1080/20421338.2019.1656428.
Adera, E. O., Waema, T. M., May, J. D., Mascarenhas, O., & Diga, K. (eds.). (2014). ICT pathways to poverty reduction: Empirical evidence from East and Southern Africa. International Development Research Centre.
Aghion, P., & Howitt, P. (1992). A model of growth through creative destruction. Econometrica, 60(2), 323-351. doi: https://doi.org/10.2307/2951599.
Amar, S., Satrianto, A., & Kurniadi, A. P. (2022). Determination of poverty, unemployment, economic growth, and investment in West Sumatra Province. International Journal of Sustainable Development and Planning, 17(4), 1237-1246. doi: https://doi.org/10.18280/ijsdp.170422.
Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93-115. doi: https://doi.org/10.1111/j.1538-4632.1995.tb00338.x.
Anselin, L., & Rey, S. (1991). Properties of tests for spatial dependence in linear regression models. Geographical Analysis, 23(2), 112-131. doi: https://doi.org/10.1111/j.1538-4632.1991.tb00228.x.
Asongu, S., Amari, M., Jarboui, A., & Mouakhar, K. (2021). ICT dynamics for gender inclusive intermediary education: Minimum poverty and inequality thresholds in developing countries. Telecommunications Policy, 45(5), 102125. doi: https://doi.org/10.1016/j.telpol.2021.102125.
Aurellia, N. A., Ramadhani, A. A., Pamungkas, K. A., & Kartiasih, F. (2023). Determinan kejadian wasting pada balita: Studi kasus: Provinsi Nusa Tenggara Timur tahun 2021. Prosiding Seminar Nasional Official Statistics 2023, 1, 167-178. doi: https://doi.org/10.34123/semnasoffstat.v2023i1.1901.
Belantika, B. T., Rohmad, B., Arandita, H. D. N., Hutasoit, D. R., & Kartiasih, F. (2023). Factors affecting poverty using a geographically weighted regression approach (case study of Java Island, 2020). Optimum: Jurnal Ekonomi dan Pembangunan, 13(2), 141-154. doi: https://doi.org/10.12928/optimum.v13i2.7993.
Berdiev, A. N., Saunoris, J. W., & Schneider, F. (2020). Poverty and the shadow economy: The role of governmental institutions. The World Economy, 43(4), 921-947. doi: https://doi.org/10.1111/twec.12917.
Beuermann, D.W., McKelvey, C., & Vakis, R. (2012). Mobile phones and economic development in rural Peru. The Journal of Development Studies, 48(11), 1617-1628. doi: https://doi.org/10.1080/00220388.2012.709615.
BPS. (2021, 5 Februari). Pertumbuhan Ekonomi Indonesia Triwulan IV-2020. Berita Resmi Statistik, 13/02/Th. XXIV. Badan Pusat Statistik. https://www.bps.go.id/pressrelease/2021/02/05/1811/ekonomi-indonesia-2020-turun-sebesar-2-07-persen--c-to-c-.html.
BPS (2022a). Keadaan angkatan kerja di Indonesia (Februari dan Agustus 2022). Badan Pusat Statistik. https://www.bps.go.id/id/publication?keyword=Keadaan%20Angkatan%20Kerja%20di%20Indonesia&onlyTitle=true&year=2022&sort=latest.
BPS. (2022b). Penghitungan dan analisis kemiskinan makro Indonesia tahun 2022. Badan Pusat Statistik. https://www.bps.go.id/id/publication/2022/11/30/041b11a57ce8fe671631f684/penghitungan-dan-analisis-kemiskinan-makro-indonesia-tahun-2022.html.
BPS (2022c). Statistik Indonesia 2022. Badan Pusat Statistik. https://www.bps.go.id/id/publication/2022/02/25/0a2afea4fab72a5d052cb315/statistik-indonesia-2022.html.
Callinicos, A. (2004). Equality of what?. in Farrelly, C. (ed.), Contemporary political theory: A reader, pp. 36-44, Sage Publications. doi: https://doi.org/10.4135/9781446215272.n5.
Chang, H. H., & Just, D. R. (2009). Internet access and farm household income–empirical evidence using a semi-parametric assessment in Taiwan. Journal of Agricultural Economics, 60(2), 348-366. doi: https://doi.org/10.1111/j.1477-9552.2008.00189.x.
Deganis, I., Haghian, P. Z., Tagashira, M., & Alberti, A. (2021). Leveraging digital technologies for social inclusion. UN/DESA Policy Brief, 92. United Nations Department of Economic and Social Affairs. https://www.un.org/development/desa/dpad/publication/un-desa-policy-brief-92-leveraging-digital-technologies-for-social-inclusion/.
Dzator, J., Acheampong, A. O., Appiah-Otoo, I., & Dzator, M. (2023). Leveraging digital technology for development: Does ICT contribute to poverty reduction?. Telecommunications Policy, 47(4), 102524. doi: https://doi.org/10.1016/j.telpol.2023.102524.
Elhorst, J. P. (2014). Spatial econometrics: From cross-sectional data to spatial panels. Springer.
Fernández-Portillo, A., Almodóvar-González, M., & Hernández-Mogollón, R. (2020). Impact of ICT development on economic growth. A study of OECD European union countries. Technology in Society, 63, 101420. doi: https://doi.org/10.1016/j.techsoc.2020.101420.
Fingleton, B., & Le Gallo, J. (2008). Estimating spatial models with endogenous variables, a spatial lag and spatially dependent disturbances: Finite sample properties. Papers in Regional Science, 87(3), 319-340. doi: https://doi.org/10.1111/j.1435-5957.2008.00187.x.
Galperin, H., & Fernanda Viecens, M. (2017). Connected for development? Theory and evidence about the impact of internet technologies on poverty alleviation. Development Policy Review, 35(3), 315-336. doi: https://doi.org/10.1111/dpr.12210.
Griffith, D. A. (1989). [Review of Spatial Econometrics: Methods and Models, by L. Anselin]. Economic Geography, 65(2), 160-162. doi: https://doi.org/10.2307/143780.
Hardinata, R., Oktaviana, L., Husain, F. F., Putri, S., & Kartiasih, F. (2023). Analisis faktor-faktor yang memengaruhi stunting di Indonesia tahun 2021. Seminar Nasional Official Statistics, 2023(1), 817-826. doi: https://doi.org/10.34123/semnasoffstat.v2023i1.1867.
Harum, N. S., Aini, M., Risxi, M. A., & Kartiasih, F. (2023). Pengaruh sosial ekonomi dan kesehatan terhadap pengeluaran konsumsi pangan rumah tangga Provinsi Jawa Tengah tahun 2020. Seminar Nasional Official Statistics, 2023(1), 899-908. doi: https://doi.org/10.34123/semnasoffstat.v2023i1.1919.
Hatcher, A. M., Gibbs, A., Jewkes, R., McBride, R. S., Peacock, D., & Christofides, N. (2019). Effect of childhood poverty and trauma on adult depressive symptoms among young men in peri-urban South African settlements. Journal of Adolescent Health, 64(1), 79-85. doi: https://doi.org/10.1016/j.jadohealth.2018.07.026.
Hausman, J. A. (1978). Specification tests in econometrics. Econometrica: Journal of the Econometric Society, 46(6), 1251-1271. doi: https://doi.org/10.2307/1913827.
Haveman, R. H. (2015). Poverty: Measurement and analysis. in Wright, J. D. (ed.), International Encyclopedia of the Social & Behavioral Sciences (Second Edition), 741-746. Elsevier. https://doi.org/10.1016/B978-0-08-097086-8.71035-X.
Kanjo, C. (2020). Poverty by design: The role of ICT. In Hamada, B. I., & Wok, S. (eds.), Off and Online Journalism and Corruption - International Comparative Analysis, pp. 85-100. IntechOpen.
Kartiasih, F., & Setiawan, A. (2019). Efisiensi teknis usaha tani padi di Provinsi Kepulauan Bangka Belitung. Analisis Kebijakan Pertanian, 17(2), 139-148.
Kartiasih, F., Djalal Nachrowi, N., Wisana, I. D. G. K., & Handayani, D. (2023a). Inequalities of Indonesia’s regional digital development and its association with socioeconomic characteristics: a spatial and multivariate analysis. Information Technology for Development, 29(2-3), 299-328. doi: https://doi.org/10.1080/02681102.2022.2110556.
Kartiasih, F., Nachrowi, N. D.,Wisana, I. D. G. K., & Handayani, D. (2023b). Potret ketimpangan digital dan distribusi pendapatan di Indonesia: Pendekatan regional digital development index. UI Publishing.
Kartiasih, F., Nachrowi, N. D.,Wisana, I. D. G. K., & Handayani, D. (2023c). Towards the quest to reduce income inequality in Indonesia: Is there a synergy between ICT and the informal sector?. Cogent Economics & Finance, 11(2), 2241771. doi: https://doi.org/10.1080/23322039.2023.2241771.
Kenny, C. (2002). Information and communication technologies for direct poverty alleviation: costs and benefits. Development Policy Review, 20(2), 141-157. doi: https://doi.org/10.1111/1467-7679.00162.
Kopczewska, K., Kudła, J., & Walczyk, K. (2017). Strategy of spatial panel estimation: Spatial spillovers between taxation and economic growth. Applied Spatial Analysis and Policy, 10, 77-102. doi: https://doi.org/10.1007/s12061-015-9170-2.
Kroll, C., Warchold, A., & Pradhan, P. (2019). Sustainable Development Goals (SDGs): Are we successful in turning trade-offs into synergies?. Palgrave Communications, 5(1), 140. doi: https://doi.org/10.1057/s41599-019-0335-5.
Latifa, A., Primadani, A. D., Fitriyyah, N. R., & Kartiasih, F. (2023). Mapping and estimating the impact of drought on food crop farmers using remote sensing in East Nusa Tenggara Province. TheJournalish: Social and Government, 4(5), 309-335. doi: https://doi.org/10.55314/tsg.v4i5.619.
Lechman, E., & Popowska, M. (2022). Harnessing digital technologies for poverty reduction. Evidence for low-income and lower-middle income countries. Telecommunications Policy, 46(6), 102313. doi: https://doi.org/10.1016/j.telpol.2022.102313.
Liu, Y., Liu, J., & Zhou, Y. (2017). Spatio-temporal patterns of rural poverty in China and targeted poverty alleviation strategies. Journal of Rural Studies, 52, 66-75. doi: https://doi.org/10.1016/j.jrurstud.2017.04.002.
Liu, Y., Amin, A., Rasool, S. F., & Zaman, Q. U. (2020). The role of agriculture and foreign remittances in mitigating rural poverty: Empirical evidence from Pakistan. Risk Management and Healthcare Policy, 13, 13-26. doi: https://doi.org/10.2147/RMHP.S235580.
Luo, Y., Yan, J., McClure, S. C., & Li, F. (2022). Socioeconomic and environmental factors of poverty in China using geographically weighted random forest regression model. Environmental Science and Pollution Research, 29, 33205-33217. doi: https://doi.org/10.1007/s11356-021-17513-3.
Ma, Z., Chen, X., & Chen, H. (2018). Multi-scale spatial patterns and influencing factors of rural poverty: A case study in the Liupan Mountain Region, Gansu Province, China. Chinese Geographical Science, 28, 296-312. doi: https://doi.org/10.1007/s11769-018-0943-9.
Ma, W., Nie, P., Zhang, P., & Renwick, A. (2020). Impact of internet use on economic well-being of rural households: Evidence from China. Review of Development Economics, 24(2), 503-523. doi: https://doi.org/10.1111/rode.12645.
Mathy, S., & Blanchard, O. (2016). Proposal for a poverty-adaptation-mitigation window within the Green Climate Fund. Climate Policy, 16(6), 752-767. doi: https://doi.org/10.1080/14693062.2015.1050348.
Mendoza, M. M., Dmitrieva, J., Perreira, K. M., Hurwich-Reiss, E., & Watamura, S. E. (2017). The effects of economic and sociocultural stressors on the well-being of children of Latino immigrants living in poverty. Cultural Diversity & Ethnic Minority Psychology, 23(1), 15-26. doi: https://doi.org/10.1037/cdp0000111.
Meo, M. S., Kumar, B., Chughtai, S., Khan, V. J., Dost, M. K. B., & Nisar, Q. A. (2023). Impact of unemployment and governance on poverty in Pakistan: A fresh insight from non-linear ARDL co-integration approach. Global Business Review, 24(5), 1007-1024. doi: https://doi.org/10.1177/0972150920920440.
Nugraha, A. T., Prayitno, G., Nandhiko, L., & Nasution, A. R. (2021). Socioeconomic conditions on poverty levels a case study: Central Java Province and Yogyakarta in 2016. Revista de Economia e Sociologia Rural, 60, e233206. doi: https://doi.org/10.1590/1806-9479.2021.233206.
Ofori, I. K., Armah, M. K., Taale, F., & Ofori, P. E. (2021). Addressing the severity and intensity of poverty in Sub-Saharan Africa: How relevant is the ICT and financial development pathway?. Heliyon, 7(10), e08156. doi: https://doi.org/10.1016/j.heliyon.2021.e08156.
Olopade, B. C., Okodua, H., Oladosun, M., & Asaleye, A. J. (2019). Human capital and poverty reduction in OPEC member-countries. Heliyon, 5(8), e02279. doi: https://doi.org/10.1016/j.heliyon.2019.e02279.
Palvia, P., Baqir, N., & Nemati, H. (2018). ICT for socio-economic development: A citizens’ perspective. Information & Management, 55(2), 160-176. doi: https://doi.org/10.1016/j.im.2017.05.003.
Pan, X., Guo, S., Han, C., Wang, M., Song, J., & Liao, X. (2020). Influence of FDI quality on energy efficiency in China based on seemingly unrelated regression method. Energy, 192, 116463. doi: https://doi.org/10.1016/j.energy.2019.116463.
Pan, Y., Chen, J., Yan, X., Lin, J., Ye, S., Xu, Y., & Qi, X. (2022). Identifying the spatial–temporal patterns of vulnerability to Re-poverty and its determinants in rural China. Applied Spatial Analysis and Policy, 15(2), 483-505. doi: https://doi.org/10.1007/s12061-021-09407-1.
Prawidia, D., Zhafirah, L., Saputra, N., Kartiasih, F., & Sahu, U. (2023). Determinants of under-five mortality due to pneumonia: A negative binomial regression analysis. Jurnal Varian, 7(1), 59-66. doi: https://doi.org/10.30812/varian.v7i1.2768.
Pribadi, W., & Kartiasih, F. (2020). Environmental quality and poverty assessment in Indonesia. Journal of Natural Resources and Environmental Management, 10(1), 89-97. doi: https://doi.org/10.29244/jpsl.10.1.89-97.
Purwono, R., Wardana, W. W., Haryanto, T., & Mubin, M. K. (2021). Poverty dynamics in Indonesia: empirical evidence from three main approaches. World Development Perspectives, 23, 100346. doi: https://doi.org/10.1016/j.wdp.2021.100346.
Putri, C. K. L., Zhafarina, N., Putri, N. Y., & Kartiasih, F. (2023). Pengaruh pandemi COVID-19 dan variabel sosial ekonomi terhadap prevalensi ketidakcukupan konsumsi pangan di Indonesia tahun 2021. Seminar Nasional Official Statistics, 2023(1), pp. 73-82. doi: https://doi.org/10.34123/semnasoffstat.v2023i1.1836.
Rambe, R. A., Purmini, P., Armelly, A., Alfansi, L., & Febriani, R. E. (2022). Efficiency comparison of pro-growth poverty reduction spending before and during the COVID-19 pandemic: A study of regional governments in Indonesia. Economies, 10(6), 150. doi: https://doi.org/10.3390/economies10060150.
Ravallion, M., & Chen, S. (2003). Measuring pro-poor growth. Economics Letters, 78(1), 93-99. doi: https://doi.org/10.1016/S0165-1765(02)00205-7.
Ravallion, M., & Chen, S. (2007). China’s (uneven) progress against poverty. Journal of Development Economics, 82(1), 1-42. doi: https://doi.org/10.1016/j.jdeveco.2005.07.003.
Ren, Z., Ge, Y., Wang, J., Mao, J., & Zhang, Q. (2017). Understanding the inconsistent relationships between socioeconomic factors and poverty incidence across contiguous poverty-stricken regions in China: Multilevel modelling. Spatial Statistics, 21(Part B), 406-420. doi: https://doi.org/10.1016/j.spasta.2017.02.009.
Todaro, M. P. (2003). Pembangunan ekonomi di dunia ketiga (Jilid 2, Edisi 8). Erlangga.
Turriago-Hoyos, Á., Martínez Mateus, W. A., & Thoene, U. (2020). Spatial analysis of multidimensional poverty in Colombia: Applications of the Unsatisfied Basic Needs (UBN) Index. Cogent Economics & Finance, 8(1), 1837441. doi: https://doi.org/10.1080/23322039.2020.1837441.
Yang, Y., de Sherbinin, A., & Liu, Y. (2020). China’s poverty alleviation resettlement: Progress, problems and solutions. Habitat International, 98, 102135. doi: https://doi.org/10.1016/j.habitatint.2020.102135.
Yang, L., Lu, H.,Wang, S., & Li, M. (2021). Mobile internet use and multidimensional poverty: Evidence from a household survey in rural China. Social Indicators Research, 158(3), 1065-1086. doi: https://doi.org/10.1007/s11205-021-02736-1.
Zhang, J., Zuo, F., Zhou, Y., Zhai, M., Mei, L., Fu, Y., & Cheng, Y. (2018). Analyzing influencing factors of rural poverty in typical poverty areas of Hainan Province: A case study of Lingao County. Chinese Geographical Science, 28, 1061-1076. doi: https://doi.org/10.1007/s11769-018-1008-9.
Zheng, X., & Lu, H. (2021). Does ICT change household decision-making power of the left-behind women? A case from China. Technological Forecasting and Social Change, 166, 120604. doi: https://doi.org/10.1016/j.techfore.2021.120604.