Membangun kepercayaan publik: visualisasi data interaktif capaian kinerja Kantor Regional IX BKN Jayapura
DOI:
https://doi.org/10.30997/jgs.v11i1.15091Kata Kunci:
Visualisasi Data, Kepegawaian, Power BI, Kanreg IX BKNAbstrak
Di era pengelolaan data yang semakin kompleks, visualisasi data menjadi kunci penting untuk memahami dan menganalisa informasi secara lebih efektif. Penelitian ini membahas tentang analisis visual dinamika kepegawaian di wilayah kerja Kanreg IX BKN Jayapura dengan menggunakan alat visualisasi Power BI. Memanfaatkan data jumlah PNS di wilayah kerja dan data kenaikan pangkat dan pensiun PNS selama tahun 2023, penelitian ini bertujuan untuk memberikan wawasan yang mendalam mengenai tren kepegawaian di wilayah kerja Kanreg IX BKN Jayapura. Melalui interpretasi temuan data, penelitian ini mengidentifikasi faktor-faktor yang mempengaruhi dinamika kepegawaian, seperti jumlah total PNS, usulan pensiun, dan usulan kenaikan pangkat. Implikasi dari temuan tersebut juga dibahas untuk memberikan rekomendasi yang relevan bagi para pemangku kepentingan yang terkait dengan pengambilan keputusan kepegawaian yang strategis. Dengan menggunakan Power BI sebagai alat visualisasi data yang canggih, penelitian ini memberikan kontribusi dalam pemahaman yang lebih baik tentang kepegawaian di wilayah Kanreg IX Jayapura dan memberikan dasar yang kuat untuk langkah-langkah kebijakan yang efektif dan berkelanjutan.
Referensi
Ali, S. M., Gupta, N., Nayak, G. K., & Lenka, R. K. (2016, December). Big data visualization: Tools and challenges. In 2016 2nd International conference on contemporary computing and informatics (IC3I) (pp. 656-660). IEEE.
Alsallakh, B., Micallef, L., Aigner, W., Hauser, H., Miksch, S., & Rodgers, P. (2014). Visualizing sets and set-typed data: State-of-the-art and future challenges.
Aspin, A. (2016). Pro Power BI Desktop. Apress.
Becker, L. T., & Gould, E. M. (2019). Microsoft power BI: extending excel to manipulate, analyze, and visualize diverse data. Serials Review, 45(3), 184-188.
Dilla, W. N., & Steinbart, P. J. (2005). The effects of alternative supplementary display formats on balanced scorecard judgments. International Journal of Accounting Information Systems, 6(3), 159-176.
Debiasi, A. (2016). Study of visual clutter in geographic node-link diagrams.
Husin, N. D. I., & Abdullah, N. A. S. (2019). Overlapping issues and solutions in data visualization techniques. Indonesian Journal of Electrical Engineering and Computer Science, 16(3), 1600-1608.
Keim, D. A., Mansmann, F., Schneidewind, J., & Ziegler, H. (2006, July). Challenges in visual data analysis. In Tenth International Conference on Information Visualisation (IV'06) (pp. 9-16). IEEE.
Keim, D. A., & Ward, M. O. (2002). Visual data mining techniques.
Knight, D., Knight, B., Pearson, M., Quintana, M., & Powell, B. (2018). Microsoft Power BI Complete Reference: Bring your data to life with the powerful features of Microsoft Power BI. Packt Publishing Ltd.
Knaflic, C. N. (2015). Storytelling with data: A data visualization guide for business professionals. John Wiley & Sons.
Lipe, M. G., & Salterio, S. (2002). A note on the judgmental effects of the balanced scorecard's information organization. Accounting, organizations and society, 27(6), 531-540.
Liu, J., Tang, T., Wang, W., Xu, B., Kong, X., & Xia, F. (2018). A survey of scholarly data visualization. Ieee Access, 6, 19205-19221.
Provost, F., & Fawcett, T. (2013). Data Science for Business: What you need to know about data mining and data-analytic thinking. " O'Reilly Media, Inc.".
Maccarthaigh, M., & Boyle, R. (2014). Civil service accountability: Challenge and change. Research Paper, (12).
Powell, B. (2018). Mastering Microsoft Power BI: Expert techniques for effective data analytics and business intelligence. Packt Publishing Ltd.
Provost, F., & Fawcett, T. (2013). Data science and its relationship to big data and data-driven decision making. Big data, 1(1), 51-59.
Singh, G., Kumar, A., Singh, J., & Kaur, J. (2023, March). Data visualization for developing effective performance dashboard with Power BI. In 2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA) (pp. 968-973). IEEE.
Stefanovic, N. (2015). Collaborative predictive business intelligence model for spare parts inventory replenishment. Computer Science and Information Systems, 12(3), 911-930.
Susanto, A., Wahid, O., Hazriani, Y., & Yuyun, Y. (2021). Decision support system on quality assessment of the prospective civil servant’s education and training using fuzzy method. Indonesian Journal of Electrical Engineering and Computer Science, 24(1), 519-529.
Swires-Hennessy, E. (2014). Presenting data: How to communicate your message effectively. John Wiley & Sons.
Uskov, V. L., Bakken, J. P., Ganapathi, K. S., Gayke, K., Galloway, B., & Fatima, J. (2020). Data cleaning and data visualization systems for learning analytics. In Smart Education and e-Learning 2020 (pp. 183-197). Springer Singapore.
Van den Elzen, S., & Van Wijk, J. J. (2014). Multivariate network exploration and presentation: From detail to overview via selections and aggregations. IEEE Transactions on Visualization and Computer Graphics, 20(12), 2310-2319.
Wahyudin, C. E. C. E. P., Apriliani, A. F. M. I., Ramdani, F. T., Pratidina, G. I. N. U. N. G., & Seran, G. G. (2023). a Bibliometric Analysis Collaborative Governance of Plastic Reduction Through the Transformation Industry. Journal of Engineering Science and Technology, 18(4), 85-93.
Widjaja, S., & Mauritsius, T. (2019). The development of performance dashboard visualization with power BI as platform. International Journal of Mechanical Engineering and Technology (IJMET), 10(5), 235-249.
Wijaya, A., Subagyo, A., Pramono, P., & Pujiatun, P. (2022). Penerapan Prinsip-Prinsip Service Excellence dalam Pelayanan Publik. JIIP-Jurnal Ilmiah Ilmu Pendidikan, 5(12), 5485-5492.
Xia, F., Su, X., Wang, W., Zhang, C., Ning, Z., & Lee, I. (2016). Bibliographic analysis of nature based on Twitter and Facebook altmetrics data. PloS one, 11(12), e0165997.
Yigitbasioglu, O. M., & Velcu, O. (2012). A review of dashboards in performance management: Implications for design and research. International journal of accounting information systems, 13(1), 41-59.
Unduhan
Diterbitkan
Cara Mengutip
Terbitan
Bagian
Lisensi
Hak Cipta (c) 2025 Yusuf Setiadi, Hendro Margono, Imam Yuadi
Artikel ini berlisensiCreative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with Jurnal Governansi agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in Jurnal Governansi.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in Jurnal Governansi.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
