Implementasi Desa Cinta Statistik (Desa Cantik) di Kabupaten Situbondo
DOI:
https://doi.org/10.47134/pssh.v1i2.112Keywords:
Implementasi, Desa Cinta Statistik, Kabupaten SitubondoAbstract
Penelitian ini membahas implementasi program desa cinta statistik di Kabupaten Situbondo dalam meningkatkan standarisasi pengelolaan data statistik, optimalisasi penggunaan dan pemanfaatan data statistik, dan meningkatkan kesadaran perangkat desa serta masyarakat dalam kegiatan statistik. Badan Pusat Statistik (BPS) Kabupaten Situbondo melakukan pembinaan terhadap tiga desa yang terpilih sebagai pilot projek untuk pelaksanaan kegiatan pembinaan statistik untuk meningkatkan literasi statistik pemerintah desa dalam rangka pembangunan yang lebih baik. Penelitian ini dilakukan menggunakan pendekatan deskriptif kualitatif, dengan pengumpulan metode pengumpulan data berupa wawancara kepada beberapa narasumber dengan menggunakan teknik purposive sampling. Hasil penelitian ini menggunakan teori proses dari Merille S. Grindle yang menunjukkan implementasi program desa cinta statistik di kabupaten situbondo saat ini masih belum optimal dan mengalami kendala dalam pelaksanaannya baik dalam waktu pelaksanaan yang terbatas dan berbenturan dengan kegiatan statistik lainnya, serta keterbatasan dana untuk kegiatan program, namum manfaat sudah dirasakan oleh salah satu desa dalam pembinaan yang pada saat ini dimana pengambilan keputusan dalam pembangunan desanya lebih baik dengan menggunakan data dan adanya agen statistik pada level desa. Proses implementasi dari kebijakan yang dibuat oleh BPS Kabupaten Situbondo dalam melakukan pembinaan untuk mencapai tujuan desa cinta statistik belum terimplementasikan dengan baik.
References
Chen, Y. (2020). Statistical inference of categorical data in health management research. Chinese Journal of Health Management, 14(4), 400–406. https://doi.org/10.3760/cma.j.cn115624-20200607-00469
Cross, H. R. (2023). Under the Hood: The Scientific Leadership, Clinical Operations, Statistical and Data Management, and Laboratory Centers of the Antibacterial Resistance Leadership Group. Clinical Infectious Diseases, 77. https://doi.org/10.1093/cid/ciad529
Factors, C. S., & Islami, M. J. (2021). Implementasi Satu Data Indonesia: Tantangan dan Critical Success Factors (CSFs). 10, 13–23. https://doi.org/10.31504/komunika.v9i1.3750
Febrianti, V. S., Khuroydi, I., & Setiawan, A. (2020). Transformasi Pelayanan Publik Melalui Digital (Studi Pendayagunaan Website Rampak Pintar Di Desa Kesambi Rampak Situbondo). 464–492.
Gao, J. (2023). Practical Application of Big Data Statistical Analysis Method for Enterprise Economic Management in Digital Era. EAI Endorsed Transactions on Scalable Information Systems, 10(6). https://doi.org/10.4108/eetsis.3984
González-Serrano, L. (2019). Entropic statistical description of big data quality in hotel customer relationship management. Entropy, 21(4). https://doi.org/10.3390/e21040419
Herrmann, E. (2019). Motion data and model management for applied statistical motion synthesis. Italian Chapter Conference 2019 - Smart Tools and Apps in Computer Graphics, STAG 2019, 79–88. https://doi.org/10.2312/stag.20191366
Ihsan, H., Rahman, A., & Zahra, N. A. (2021). Sosialisasi Potensi Desa Mujur Sebagai Desa Cantik (Cinta Statistik) Dalam Bidang Pertanian. 943–948.
Ilmi, M. R., Maulana, A., & Wicaksono, I. (2022). Implementasi Layanan Harian Buat Administrasi Kependudukan Orang Jember (LAHBAKO) di Kantor Kecamatan Ambulu.
Li, M. (2023). Research on Public Management Statistical Data Quality Management Based on Fuzzy Clustering Algorithm. Proceedings - 2023 2nd International Conference on 3D Immersion, Interaction and Multi-Sensory Experiences, ICDIIME 2023, 514–518. https://doi.org/10.1109/ICDIIME59043.2023.00106
Lin, Z. (2020). Statistical inference of measurement data in health management research. Chinese Journal of Health Management, 14(5), 497–504. https://doi.org/10.3760/cma.j.cn115624-20200714-00553
Otamendi, U. (2021). GEO-IMAGERY MANAGEMENT AND STATISTICAL PROCESSING IN A REGIONAL CONTEXT USING OPEN DATA CUBE. International Geoscience and Remote Sensing Symposium (IGARSS), 5676–5679. https://doi.org/10.1109/IGARSS47720.2021.9553940
Padovano, M. (2022). Mapping complications in thyroid surgery: statistical data are useful for medico-legal management of a recurrent safety issue. Updates in Surgery, 74(5), 1725–1732. https://doi.org/10.1007/s13304-022-01357-8
Perazzini, S. (2023). Statistical indicators based on mobile phone and street maps data for risk management in small urban areas. Statistical Methods and Applications. https://doi.org/10.1007/s10260-023-00719-9
Rahbar, M. H. (2018). Harmonization, data management, and statistical issues related to prospective multicenter studies in Ankylosing spondylitis (AS): Experience from the Prospective Study Of Ankylosing Spondylitis (PSOAS) cohort. Contemporary Clinical Trials Communications, 11, 127–135. https://doi.org/10.1016/j.conctc.2018.07.004
Renggli, C. (2018). Ease.ml/ci and Ease.ml/meter in action: Towards data management for statistical generalization. Proceedings of the VLDB Endowment, 12(12), 1962–1965. https://doi.org/10.14778/3352063.3352110
Saha, E. (2019). Statistical analysis of medical data for inventory management in a healthcare system. Analytics, Operations, and Strategic Decision Making in the Public Sector, 166–186. https://doi.org/10.4018/978-1-5225-7591-7.ch008
Sanchez-Daza, A. (2022). COVID-19 Modeling Under Uncertainty: Statistical Data Analysis for Unveiling True Spreading Dynamics and Guiding Correct Epidemiological Management. Studies in Systems, Decision and Control, 366, 245–282. https://doi.org/10.1007/978-3-030-72834-2_9
Sanchez-Marquez, R. (2018). A statistical system management method to tackle data uncertainty when using key performance indicators of the balanced scorecard. Journal of Manufacturing Systems, 48, 166–179. https://doi.org/10.1016/j.jmsy.2018.07.010
Sekhar, M. S. (2018). A hybrid statistical data preprocessing and data forecasting model on ERP based supply chain management (SCM) databases. International Journal of Simulation: Systems, Science and Technology, 19(6), 25. https://doi.org/10.5013/IJSSST.a.19.06.25
Silva, I. (2019). Asset management of power transformers based on data analytics and statistical studies. WSEAS Transactions on Power Systems, 14, 202–208.
Stark, S. M. (2022). Statistical Data Analysis of Low-Level Nonconformances for Risk Assessment in Trackway Asset Management. Transportation Research Record, 2676(7), 542–553. https://doi.org/10.1177/03611981221079832
Takahashi, T. (2019). Impacts of 150 years of modernization policies on the management of common forests in japan: A statistical analysis of micro census data. International Journal of the Commons, 13(2), 1021–1034. https://doi.org/10.5334/ijc.936
Tegal, B. P. S. K. (2022). Ayo Kita Sukseskan Desa Cantik, Cinta Statistik. https://tegalkab.bps.go.id/news/2022/06/09/200/ayo-kita-sukseskan-desa-cantik–cinta-statistik.html
Ueyama, H. (2018). Development of statistical methods for estimating hourly direct and diffuse solar radiation using public data for precise cultivation management. Journal of Agricultural Meteorology, 74(1), 29–39. https://doi.org/10.2480/agrmet.D-17-00023
Wang, L. (2020). Research on the Application of Big Data Statistical Analysis in the Field of Economic Management. Journal of Physics: Conference Series, 1533(4). https://doi.org/10.1088/1742-6596/1533/4/042010
Wu, K. (2019). Special issue on scientific and statistical data management. Distributed and Parallel Databases, 37(1). https://doi.org/10.1007/s10619-019-07258-x
Yao, C. (2018). Clinical trial in China: The status and challenge of data management and statistical analysis. Journal of Evidence-Based Medicine, 11(1), 3–6. https://doi.org/10.1111/jebm.12295
Zoltán, V. J. (2021). Effect of various sampling methods on the statistical properties of financial data and their application in risk management. Statisztikai Szemle, 99(3), 233–252. https://doi.org/10.20311/stat2021.3.hu0233
Downloads
Published
How to Cite
License
Copyright (c) 2023 Delina Rohmatillah Mariani, Itok Wicaksono
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
