International Journal on Electrical Engineering and Informatics 11(3), pp. 474-484.
ISSN/ISBN: Not available at this time. DOI: Not available at this time.
Abstract: Interviewer falsification is an important issue faced by institutions conducting censuses and surveys around the world, including Statistics Indonesia. This study discusses several methods to systematically detect interviewer falsification and validation using data mining techniques so that human supervisors can take further actions. After analyzing relevant features and conducting experiments, the results showed that unsupervised classification algorithm using simple 2-means clustering achieved 70.5% accuracy, while the supervised classification using logistic regression improved the accuracy to 88.5%. A greater level of accuracy is still needed to be pursued in further research, but the current results are certainly better than the traditional method which has almost no falsification detection method at all.
Bibtex:
@article{,
author = {Yusep Rosmansyah and Ibnu Santoso and Ariq Bani Hardi and Atina Putri and Sarwono Sutikno},
title = {Detection of Interviewer Falsification in Statistics Indonesia’s Mobile Survey},
journal = {International Journal on Electrical Engineering and Informatics},
volume = {11},
number = {3},
pages = {474--484},
year = {2019},
url = {http://ijeei.org/docs-2602241995dc8d94d44109.pdf},
doi = {},
}
Reference Type: Journal Article
Subject Area(s): Accounting, Statistics