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All Journal Prosiding Seminar Nasional Official Statistics PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS
Amanda Pratama Putra
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Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences

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Mobile Positioning Data: Prediktor Produk Domestik Regional Bruto (PDRB) Pada Masa Pandemi Amanda Pratama Putra; Heny Wulandari
Seminar Nasional Official Statistics Vol 2021 No 1 (2021): Seminar Nasional Official Statistics 2021
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (358.198 KB) | DOI: 10.34123/semnasoffstat.v2021i1.1033

Abstract

The Coronavirus Disease 2019 (COVID-19) pandemic has devastated economic activity in many countries, including Indonesia. Big data as an alternative data source to measure economic activity, especially in a pandemic situation, can be a valuable mine of information. In the present research, a new approach for measuring economic activities based on mobile positioning data (MPD) has been developed. The sample dataset of mobile network subscribers’ activity was aggregated at the area municipality level by the daily interval, where the activity itself is defined as the number of mobile transactions and detected locations, and the number of unique users. This paper shows that mobile positioning data (MPD) can be a proxy to estimate economic activity in Indonesia, especially during pandemic conditions.
AMDA: Anchor Mobility Data Analytic for Determining Home-Work Location from Mobile Positioning Data Amanda Pratama Putra; Wa Ode Zuhayeni Madjida; Ignatius Aditya Setyadi; Amin Rois Sinung Nugroho; Alfatihah Reno MNSP Munaf
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.v2021i1.239

Abstract

In conducting a mobility analysis using Mobile Positioning Data, the most critical step is to define each customer's usual environment. The initial concept of mobility used is the movement that occurs from and to every usual environment, so errors in determining the usual environment will cause incorrect mobility statistics. Therefore, Anchor Mobility Data Analytic (AMDA) is proposed for Home-Work Location Determination from Mobile Positioning Data. This algorithm uses clockwise reversal to make it easier to classify someone in their usual environment. Unfortunately, only about 80% of the raw data can be used to establish usual environments. The remaining 20% do not have sufficient data history. This study found that the accuracy of AMDA in determining monthly home location was 98.8% at the provincial level and 88.7% at the regency level. As for the determination of monthly work locations, 98.9% at the provincial level and 70.4% at the regency level.
Co-Authors Alfatihah Reno MNSP Munaf Amin Rois Sinung Nugroho Heny Wulandari Ignatius Aditya Setyadi Wa Ode Zuhayeni Madjida