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Ika Yuni Wulansari
Politeknik Statistika STIS
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THE IMPACT OF COVID-19 OUTBREAK ON AIR POLLUTION LEVELS USING ARIMA INTERVENTION MODELLING: A CASE STUDY OF JAKARTA, INDONESIA Dyah Makutaning Dewi; Ariful Romadhon; Istu Indah Setyaningsih; Ika Yuni Wulansari
Jurnal Meteorologi dan Geofisika Vol 23, No 3 (2022): Special Issue
Publisher : Pusat Penelitian dan Pengembangan BMKG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31172/jmg.v23i3.791

Abstract

Jakarta is a region with a high number of COVID-19 cases in Indonesia. This study investigates the impact of the COVID-19 pandemic and the resulting large scale social restriction on air pollution levels in Jakarta, Indonesia, by studying particulate matter (PM10) levels. This study employs ARIMA intervention using daily COVID-19 case data from January 1, 2020 to September 30, 2020 (the period before and after the first case of COVID-19 in Indonesia on March 2, 2020). The analysis shows COVID-19 started to impact PM10 in Jakarta on the 11th day after confirming the first case in Indonesia, which is indicated by an unordinary increase in PM10 level. However, on the 12th day after intervention, the PM10 level decreases. This occurred at the beginning of the period when large-scale social restrictions are imposed. However, one month after intervention, PM10 increases again and continues to increase until the end of the study. This is allegedly because people are accustomed to being ignorant and bored with the pandemic situation. Social restrictions and movements are no longer effective, which results in the rise of PM10 levels again. Hence, it can be concluded that COVID-19 impacts air quality in Jakarta even though the impact is minimal and in the short term.
Estimating Customer Lifetime Value in the E-Commerce Industry Using Multivariate Analysis Bagaskoro Cahyo Laksono; Ika Yuni Wulansari
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2021 No. 1 (2021): Proceedings of 2021 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2021i1.161

Abstract

Companies can develop their business using big data to support decision-making. Big data in the e-commerce industry that includes size and speed of high transactions can be used to analyze customer behaviour and predict customer value. Nowadays, companies are starting to develop customer-oriented rather than product-oriented business interests. One way that can be used to determine customer value is by calculating Customer Lifetime Value (CLV). By knowing CLV at the individual level, it will be useful to help decision-makers to develop customer segmentation and resource allocation. It is important to do segmentation or customer grouping that describes customer loyalty groups. Therefore, this research aims to calculate CLV and customer segmentation using the RFM analysis method. The dimensions of forming CLV include the values of Recency, Frequency, and Monetary. In this study, concept of multivariate statistical analysis will be applied, namely K-Means Clustering and factor analysis. Segmentation is done to determine the level of customers. The higher the CLV value, more valuable customer is to maintain. In the end, the customer segmentation method built by author can be used to optimize company's strategy to get maximum profit. This method can be applied to various cases and other companies.
THE IMPACT OF COVID-19 OUTBREAK ON AIR POLLUTION LEVELS USING ARIMA INTERVENTION MODELLING: A CASE STUDY OF JAKARTA, INDONESIA Dyah Makutaning Dewi; Ariful Romadhon; Istu Indah Setyaningsih; Ika Yuni Wulansari
Jurnal Meteorologi dan Geofisika Vol. 23 No. 3 (2022): Special Issue
Publisher : Pusat Penelitian dan Pengembangan BMKG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31172/jmg.v23i3.791

Abstract

Jakarta is a region with a high number of COVID-19 cases in Indonesia. This study investigates the impact of the COVID-19 pandemic and the resulting large scale social restriction on air pollution levels in Jakarta, Indonesia, by studying particulate matter (PM10) levels. This study employs ARIMA intervention using daily COVID-19 case data from January 1, 2020 to September 30, 2020 (the period before and after the first case of COVID-19 in Indonesia on March 2, 2020). The analysis shows COVID-19 started to impact PM10 in Jakarta on the 11th day after confirming the first case in Indonesia, which is indicated by an unordinary increase in PM10 level. However, on the 12th day after intervention, the PM10 level decreases. This occurred at the beginning of the period when large-scale social restrictions are imposed. However, one month after intervention, PM10 increases again and continues to increase until the end of the study. This is allegedly because people are accustomed to being ignorant and bored with the pandemic situation. Social restrictions and movements are no longer effective, which results in the rise of PM10 levels again. Hence, it can be concluded that COVID-19 impacts air quality in Jakarta even though the impact is minimal and in the short term.
Co-Authors Ariful Romadhon Bagaskoro Cahyo Laksono Dyah Makutaning Dewi Geri Yesa Ermawan Istu Indah Setyaningsih Siskarossa Ika Oktora