Human Resources Investment through the Scholarship Program Implementation for Sustainable Development in the Local Region

Handoko Wijoyo; Faridatul Istighfaroh; Saiful Anam

doi:10.29259/jep.v20i1.17393

Human Resources Investment through the Scholarship Program Implementation for Sustainable Development in the Local Region

Handoko Wijoyo, Faridatul Istighfaroh, Saiful Anam

Abstract

Bojonegoro is the region that contributes 30 percent of national oil, so it is hoped that natural resources can be converted into human resources which are sustainable development investments, looking at the future of Bojonegoro Regency from the HDI perspective to achieve the largest target, whether the policy about scholarships taken has full implications for sustainable development, the researcher is using the Double Exponential Smoothing method. Data were obtained from the Regional Development Planning Agency and the Statistics of Bojonegoro report. Based on the calculation results, the best forecasting is obtained based on the measurement accuracy value of 0.7 MAPE 0.385 persen means that its very good criteria, with many scholarship programs from 2019-2021, concludin using qualitative methods plus 2022 Village RPL scholarships with the number of thousands of people, after graduating in 2024 IPM Bojonegoro is predicted to enter the high category, namely the highest score of 72.08 even more, as an outcome of the program it can be practiced because it is intended for stakeholders and structural drivers of villages in Bojonegoro, and this is in line with sustainable development.

Keywords

scholarship, forecasting, HDI, Bojonegoro

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References

Airlangga, G., Rachmat, A., & Lapihu, D. (2019). Comparison of exponential smoothing and neural network method to forecast rice production in Indonesia. Telkomnika (Telecommunication Computing Electronics and Control), 17(3), 1367–1375. https://doi.org/10.12928/TELKOMNIKA.V17I3.11768.

Bojonegoro Health Department. (2020). Bojonegoro Health Office received a 100% predict universal Health Coverage(UHC) in 2020. Bojonegoro Health Department. Accessed from https://dinkes.bojonegorokab.go.id

BPS Bojonegoro Regency. (2021). Bojonegoro Regency Human Development Index. Bojonegoro: Central Bureau of Statistics of Bojonegoro Regency.

Dewi, N. L. S., & Sutrisna, I. K. (2012). Pengaruh komponen indeks pembangunan manusia terhadap pertumbuhan ekonomi Provinsi Bali. E-Jurnal Ekonomi Pembangunan Universitas Udayana, 3(3), 76–123.

Edwards III, G. C. (1980). Implementing Public Policy. Washington D.C: Congressional Quarterly Inc.

Farida, Y., Sulistiani, D. A., & Ulinnuha, N. (2021). Forecasting the Human Development Index (IPM) of Bojonegoro Regency Using the Double Exponential Smoothing Brown Method. Journal of Theorems: Mathematical Theory and Research, 6(2), 173–183. https://jurnal.unigal.ac.id/index.php/teorema/article/view/5521

Fauziah, F.N., & Gunaryati, A. (2017). Comparison Forecasting with Double Exponential Smoothing and Artificial Neural Network to Predict the Price of Sugar. International Journal of Simulation: Systems, Science & Technology, 18(4), 1–8. https://doi.org/10.5013/IJSSST.a.18.04.13

Hansun, S. (2016). A new approach of brown’s double exponential smoothing method in time series analysis. Balkan Journal of Electrical and Computer Engineering, 4(2), 75–78. https://doi.org/10.17694/bajece.14351

Hyndman, R.J., Koehler, A.B., Snyder, R.D., & Grose, S. (2002). A state space framework for automatic forecasting using exponential smoothing methods. International Journal of Forecasting, 18(3), 439–454. https://doi.org/10.1016/S0169-2070(01)00110-8

LaViola Jr., J. J. (2003). Double Exponential smoothing: an alternative to kalman filter-based predictive tracking. In EGVE '03: Proceedings of the workshop on Virtual environments 2003. International Immersive Projection Technologies Workshop. 199-206. https://doi.org/10.1145/769953.769976

Liantoni, F., & Agusti, A. (2020). Forecasting bitcoin using double exponential smoothing method based on mean absolute percentage error. International Journal on Informatics Visualization, 4(2), 91–95. http://dx.doi.org/10.30630/joiv.4.2.335

Miles, B. M., & Huberman, A. M. (1992). Analisis Data Kualitatif: Buku Sumber tentang Metode Baru. (Translate by Rohidi, T.R, & Mulyarto). Jakarta: Universitas Indonesia Press.

Ouedraogo, N. S. (2013). Energy consumption and human development : evidence from a panel cointegration and error correction model. Energy, 63(1A), 28–41. https://doi.org/10.1016/j.energy.2013.09.067

Rana, M., & Koprinska, I. (2016). Neurocomputing forecasting electricity load with advanced wavelet neural networks. Neurocomputing, 182, 118–132. https://doi.org/10.1016/j.neucom.2015.12.004

Region Development Planning Agency.(2019). Scholarship in Bojonegoro. Bojonegoro Regency Regional Development Planning Agency.

Regional Development Planning Agency. (2018). Regional Medium-Term Development Plan (RPJMD) of Bojonegoro Regency 2018-2023. Bojonegoro Regency Regional Development Planning Agency.

Responding to Global Challenges. (2022). The PDTT Village Minister Together with the Regent of Bojonegoro Inaugurate the 2022 Unesa Scholarship. Accessed from https://bojonegorokab.go.id/berita/6439

Setyowibowo, S., As’ad, M., Sujito., & Farida, E. (2021). Forecasting of Daily Gold Price using ARIMA-GARCH Hybrid Model. Jurnal Ekonomi Pembangunan, 19(2), 257-270. https://doi.org/10.29259/jep.v19i2.13903

Sugiyono. (2014). Metode Penelitian Kualitatif dan Kuantitatif R & D. Bandung: Alphabeta.

Syafwan, H., Syafwan, M., Syafwan, E., & Hadi, A. F., Putri, P. (2021). Forecasting unemployment in north sumatra using double exponential smoothing method. Journal of Physics: Conference Series, in Annual Conference on Science and Technology Research (ACOSTER) 2020, 1783 (1), 012008. https://doi.org/10.1088/1742-6596/1783/1/012008

Teguh, M., & Bashir, A. (2019). Indonesia’s Economic Growth Forecasting. Sriwijaya International Journal of Dynamic Economics and Business, 3(2), 134-145. https://doi.org/10.29259/sijdeb.v3i2.134-145

Wang, J., Wang, J., Zhang, Z., & Guo, S. (2012). Stock index forecasting based on a hybrid model. Omega, 40(6), 758–766. https://doi.org/10.1016/j.omega.2011.07.008 c

DOI: https://doi.org/10.29259/jep.v20i1.17393

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Jurnal Ekonomi Pembangunan
Jalan Raya Palembang-Prabumulih Km. 32
Jurusan Ekonomi Pembangunan, Fakultas Ekonomi Universitas Sriwijaya
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