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Modifikasi skyline query untuk mengukur daerah prioritas penerima bantuan alat pelindung diri bagi tenaga kesehatan COVID-19

Modified skyline query to measure priority region for personal protective equipment recipient of COVID-19 health workers

Department of Informatics, Universitas Muhammadiyah Cirebon. Jl. Fatahillah, Watubelah, Kec. Sumber, Cirebon, Jawa Barat 45611, Indonesia

Received: 7 Dec 2020; Revised: 28 Jun 2021; Accepted: 5 Jul 2021; Available online: 18 Jul 2021; Published: 31 Jul 2021.
Open Access Copyright (c) 2021 The Authors. Published by Department of Computer Engineering, Universitas Diponegoro
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Citation Format:
The distribution of personal protective equipment (PPE) plays a vital role in meeting the needs of PPE in an area. This study aims to measure the priority of PPE recipient regions in West Java Province using a skyline query algorithm, namely Sort Filter Skyline (SFS). In this study, the SFS algorithm is modified to optimize the dominance measurement section. Regions that do not have hospitals will not be prioritized for PPE recipients. The preferences used in this study are maximum and minimum. The maximum preference rule is used for the number of ODP, PDP, positive and dead cases, while the minimum preference rule is used for the cured and distance attributes. The application of SFS for calculating priority regions has been successfully carried out by developing two models, namely MS1 using unmodified SFS and MS2 using modified SFS by adding a selection process for regions with no hospitals. The MS1 produces 21 skyline objects (55.55 %), while MS2 15 (66.66 %) skyline objects. The MS2 is faster than that of MS1 because fewer objects are being tested. The MS1 takes 0.0222 seconds, while MS2 only 0.0193 seconds.

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Data analysis: Modified skyline query to measure priority region for personal protective equipment recipient of COVID-19 health workers
Subject This material contains the raw data, normalization result, and entropy calculation.
Type Data Analysis
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Keywords: COVID-19; skyline query; health worker; personal protective euqipment (PPE)
Funding: Universitas Muhammadiyah Cirebon

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  1. S. S. Unhale, Q. B. Ansar, S. Sanap, S. Thakhre, and S. Wadatkar, “A review on corona virus (Covid-19),” World Journal of Pharmceutical Life Sciences, vol. 6, no. 4, pp. 109–115, 2020
  2. M. A. Shereen, S. Khan, A. Kazmi, N. Bashir, and R. Siddique, “COVID-19 infection: Origin, transmission, and characteristics of human coronaviruses,” Journal of Advanced Research, vol. 24, pp. 91–98, 2020. doi: 10.1016/j.jare.2020.03.005
  3. C. R. Telles, “Covid-19, an overview of virus reproductive emergent social transmission behavior,” Engineering and Applied Science Letters, vol. 3, no. 3, pp. 15-19, 2020. doi: 10.33767/
  4. Y. Liu et al., “Aerodynamic analysis of SARS-CoV-2 in two Wuhan hospitals,” Nature, vol. 582, no. 1, pp. 557–560, 2020. doi: 10.1038/s41586-020-2271-3
  5. J. Howard et al., “Face mask against Covid-19: an evidence review,” British Medical Journal, vol. 30, no. 20, pp. 1–8, 2020. doi: 10.20944/preprints202004.0203.v1
  6. D. Ramakrishnan, “Covid-19 and face masks – to use or not to use!,” Indian Journal Community Heath., vol. 32, no. 2 (Supp), pp. 240–243, 2020. doi: 10.47203/IJCH.2020.v32i02SUPP.012
  7. I. Tubert-Brohman, W. Sherman, M. Repasky, and T. Beurning, “Improved docking of polypeptides with glide,” Journal of Chemical Information and Modeling, vol. 53, no. 7, pp. 1689–1699, 2013. doi: 10.1021/ci400128m
  8. T. M. Cook, “Personal protective equipment during the coronavirus disease (COVID) 2019 pandemic – a narrative review,” Anaesthesia, vol. 75, no. 7, pp. 920–927, 2020. doi: 10.1111/anae.15071
  9. S. Prastyowati, “Sistem penyaluran bantuan bencana alam dan keterpenuhan kebutuhan korban kasus di kabupaten Padang Pariaman,” Jurnal Penelitian Kesejahteraan Sosial, vol. 12, no. 1, pp. 80-92, 2013
  10. N. L. Damanik, M. Dirhamsyah, and E. Fatimah “Model distribusi bantuan logistik kemanusiaan pada saat bencana banjir dengan memperhitungkan data iklim,” Jurnal Ilmu Kebencanaan, vol. 2, no. 1, pp. 35–43, 2015
  11. A. Annisa, A. Zaman, and Y. Morimoto, “Area skyline query for selecting good locations in a map,” Journal of Information Processing, vol. 24, no. 6, pp. 946–955, 2016. doi: 10.2197/ipsjjip.24.946
  12. H. Herawati, "Penentuan lokasi gudang darurat bencana dengan AHP¸ cluster analysis dan TOPSIS" Jurnal Ilmiah Manajemen, vol. 6, no. 3, pp. 434–448, 2016
  13. R. Steffi, “Survey on skyline queries with its algorithms and operators,” International Journal of Engineering Research & Technology, vol. 2, no. 11, pp. 1094–1098, 2013
  14. N. T. Lapatta, “Skyline query untuk rekomendasi ekowisata berdasarkan sentimen menggunakan apache spark nouval trezandy lapatta,” thesis, IPB University, Indonesia, 2019
  15. R. D. Kulkarni and B. F. Momin, “Skyline computation for frequent queries in update intensive environment,” Journal King Saud University- Computer Information Sciences, vol. 28, no. 4, pp. 447–456, 2016. doi: 10.1016/j.jksuci.2015.04.003
  16. V. Purwayoga and I. S. Sitanggang, “Clustering potential area of fusarium oxysporum as a disease of garlic,” IOP Conference Series: Earth and Environmental Science, vol. 528, 012040, 2020. doi: 10.1088/1755-1315/528/1/012040
  17. S. A. Alasadi and W. S. Bhaya, “Review of data preprocessing techniques in data mining,” Journal of Engineering and Applied Sciences, vol. 12, no. 16, pp. 4102–4107, 2017
  18. J. Gerretzen et al., “Simple and effective way for data preprocessing selection based on design of experiments,” Analytical Chemistry, vol. 87, no. 24, pp. 12096–12103, 2015. doi: 10.1021/acs.analchem.5b02832
  19. P. Dauni, M. D. Firdaus, R. Asfariani, M. I. N. Saputra, A. A. Hidayat, and W. B. Zulfikar, “Implementation of Haversine formula for school location tracking,” Journal of Physics: Conference Series, vol. 1402, 077028, 2019. doi: 10.1088/1742-6596/1402/7/077028
  20. Y. Miftahuddin, S. Umaroh, and F. R. Karim, “Perbandingan metode perhitungan jarak Euclidean, Haversine, dan Manhattan dalam penentuan posis karyawan (studi kasus : Institut Teknologi Nasional Bandung),” Jurnal Tekno Insentif, vol. 14, no. 2, pp. 69–77, 2020. doi: 10.36787/jti.v14i2.270
  21. D. A. Prasetya, P. T. Nguyen, R. Faizullin, I. Iswanto, and E. F. Armay, “Resolving the shortest path problem using the haversine algorithm,” Journal of Critical Reviews, vol. 7, no. 1, pp. 62–64, 2020

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