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All Journal Prosiding Seminar Nasional Official Statistics
Susanto, Hardi Dwi
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Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences

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Analisis Pola Kecelakaan Lalu Lintas Menggunakan Algoritma Decision Tree Berdasarkan Ekstraksi Informasi dari Berita Online Menggunakan Named Entity Recognition (NER) Susanto, Hardi Dwi; Yuniarto, Budi
Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2023i1.1751

Abstract

Toll roads as freeways do not make toll roads free from traffic accidents. In 2020, West Java Province had a total of 20 toll roads spanning a length of 521,15 km. The Cipali Toll Road is one of the sections with the highest fatalities in the world. Prevention of traffic accidents is important as an effort to reduce the incidence of traffic accidents. However, official data regarding traffic accidents on toll roads by official agencies is not available in detail, so alternative data sources such as online news are used. NER with Bi-LSTM-CNN is used to extract accident data. The results of news extraction are analyzed by making decision rules to determine the pattern of accidents that occur. This decision rule is in the form of a decision tree with a dataset that uses data from three toll roads with the highest fatality with the mode by concept imputation feature as a missing value handling method and toll roads as attributes, resulting in an f1-score value of 67,76% and an accuracy value of 75,49 %.
Co-Authors Yuniarto, Budi