Open AccessOptimum partition in flight route anomaly detection
Author(s) -
Mohammad Yazdi Pusadan,
Joko Lianto Buliali,
Raden Venantius Hari Ginardi
Publication year - 2019
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v14.i3.pp1315-1329
Subject(s) - partition (number theory) , anomaly detection , cluster analysis , mathematics , combinatorics , data set , cluster (spacecraft) , algorithm , computer science , statistics , data mining , programming language
Anomaly detection of flight route can be analyzed with the availability of flight data set. Automatic Dependent Surveillance (ADS-B) is the data set used. The parameters used are timestamp, latitude, longitude, and speed. The purpose of the research is to determine the optimum area for anomaly detection through real time approach. The methods used are: a) clustering and cluster validity analysis; and b) False Identification Rate (FIR). The results archieved are four steps, i.e: a) Build segments based on waypoints; b) Partition area based on 3-Dimension features P 1 and P 2 ; c) grouping; and d) Measurement of cluster validity. The optimum partition is generated by calculating the minimum percentage of FIR. The results achieved are: i) there are five partitions, i.e: (n/2, n/3, n/4, n/5) and ii) optimal partition of each 3D, that is: for P 1 was five partitions and the P 2 feature was four partitions