Open AccessAMDA: Anchor Mobility Data Analytic for Determining Home-Work Location from Mobile Positioning Data
Author(s) -
Amanda Pratama Putra,
Wa Ode Zuhayeni Madjida,
Ignatius Aditya Setyadi,
Amin Rois Sinung Nugroho,
Alfatihah Reno MNSP Munaf
Publication year - 2022
Publication title -
proceedings of international conference on data science and official statistics
Language(s) - English
Resource type - Journals
ISSN - 2809-9842
DOI - 10.34123/icdsos.v2021i1.239
Subject(s) - work (physics) , raw data , computer science , mobile device , statistics , mathematics , engineering , mechanical engineering , programming language , operating system
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.