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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi
Anang Kurnia
2Institute of Engineering Mathematics, Universiti Malaysia Perlis
Mathematics

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Comparing Outlier Detection Methods: An Application on Indonesian Air Quality Data Anwar Fitrianto; Amalia Kholifatunnisa; Anang Kurnia
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 9, No 2 (2024): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v9i2.29434

Abstract

There are many methods for detecting outliers, but only a few methods consider data distribution. This research compares outlier detection method on univariate data with a skewed distribution. Outlier detection methods used in this research are Tukey's boxplot, adjusted boxplot, sequential fences, and adjusted sequential fences. It identifies areas of concern due to poor air quality during the Implementation of Micro-Community Activity Restrictions. The study used Indonesian air quality index data.The adjusted boxplot method performs best based on the number of outliers detected, error rate, accuracy, precision, specificity, sensitivity, and robustness. Adjusted boxplot and adjusted sequential fences can detect tails that contain outliers accurately because the skewness coefficient makes them more robust. Meanwhile, Tukey's boxplot and sequential fences are poor methods since they couldn’t detect correctly true outliers. Based on the results, adjusted boxplot is the best method. Then, areas that need attention due to poor air quality include South Sumatera, South Sulawesi, West Java, Riau, North Sumatera, Jambi, Jakarta, and East Java.
Co-Authors Amalia Kholifatunnisa Fitrianto, Anwar