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All Journal BIMASTER Jurnal Matematika Sains dan Teknologi ComTech: Computer, Mathematics and Engineering Applications JUDIKA (JURNAL PENDIDIKAN UNSIKA) Jurnal Matematika UNAND Jurnal Pengabdian kepada Masyarakat Nusantara JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Jurnal Forum Analisis Statistik Jurnal Siger Matematika Fraction: Jurnal Teori dan Terapan Matematika
Nurfitri Imro’ah
Universitas Tanjungpura
Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Mathematics Social Sciences Other

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Journal : ComTech: Computer, Mathematics and Engineering Applications

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The Implementation of Control Charts as a Verification Tool in a Time Series Model for COVID-19 Vaccine Participants in Pontianak Nurfitri Imro'ah; Nur'ainul Miftahul Huda; Abang Yogi Pratama
ComTech: Computer, Mathematics and Engineering Applications Vol. 14 No. 1 (2023): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v14i1.8462

Abstract

Vaccines are the primary weapon used to stop the outbreak, especially amid the COVID-19 pandemic. Thus, supplying vaccines to control the COVID-19 pandemic is essential, especially in minimizing the incidence and achieving herd immunity to break the chain of COVID-19. West Kalimantan has taken firm anticipatory steps to prevent COVID-19 in the form of a vaccination program in Indonesia. The highest vaccination achievement occurs in Pontianak City, the province’s capital. The research analyzed data on vaccine participants in Pontianak using time series analysis. In addition, the residuals from the time series model were used as observations in constructing the control chart. The research also analyzes the accuracy of the time series model using the Individual Moving Range (IMR) control chart. The results show that the ARIMA model (5,0,2) is the best because it fulfills the assumption of white noise. However, the ARIMA (5,0,2) model is inaccurate in making predictions because the residuals from the ARIMA (5,0,2) model are out of control (based on the IMR control chart). Hence, it is necessary to evaluate in determining the time series model. It can be analyzed using a control chart. Therefore, measuring the model’s accuracy on the best model is essential in predicting several subsequent periods.
Co-Authors Abang Yogi Pratama Alvin Octavianus Halim Anjeli Dwi Laksmi Astri Maulini Bagus Setiadi Canseria Yuli Ismayanti Deva Kurnia Aristi Devi Eka Putri Eka Lestari Elisabet Wulan Ervin Ervin Ervina Ervina Eva Selvia Evy Sulistianingsih Ezra Amarya Aipassa Giovani Parasta Riswanda Helmi Helmi Hendra Perdana Ika Novira Zulianti Imi Sartika Indah Noviyanti Julianti Kastari Laksono Trisnantoro Luh Putu Ratna Sundari Maria Regina Vindasari Marsela Dian Bertiani Marwalida Rachmadiar Maya Rosalina Naomi Nessyana Debataraja Naomi Nessyana Debataraja Neva Satyahadewi NUR’AINUL MIFTAHUL HUDA Riani Mahalalita Robiansyah Robiansyah Sani Sani Setyo Wir Rizki Setyo Wira Rizki Shantika Martha Siska Yulianti Siti Aprizkiyandari, Nurul Qomariyah, Shantika Martha, Siti Hardianti Sri Jumiati Stepanus Reho Syafitri Wulandari Tamtama, Ray Tan Ade Indra Satria Trinita Ariningsih Vina Annisa Nurdiani Aji Vita Virgianti Wirda Andani Yogi Pratama Yosi Yosi