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All Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURTEKSI Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal JOURNAL OF SCIENCE AND SOCIAL RESEARCH EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Teknik Informatika (JUTIF) Jutsi: Jurnal Teknologi dan Sistem Informasi J-Com (Journal of Computer) Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat
Rahayu, Elly
Sekolah Tinggi Manajemen Informatika Dan Komputer Royal
Humanities Computer Science & IT Economics, Econometrics & Finance Education Health Professions Languange, Linguistic, Communication & Media Public Health Social Sciences

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Journal : JITK (Jurnal Ilmu Pengetahuan dan Komputer)

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K-MEANS CLUSTERING AREAS PRONE TO TRAFFIC ACCIDENTS IN ASAHAN REGENCY Nurul Rahmadani; Elly Rahayu; Ayu Lestari
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 2 (2021): JITK Issue February 2021
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1382.878 KB) | DOI: 10.33480/jitk.v6i2.1519

Abstract

Traffic accidents on the highway still contribute to the high mortality rate in Indonesia, so it is of particular concern to the police in this country. Accidents occur in various places with different time events, this makes it difficult to determine which areas have a high level of traffic accident vulnerability. Information about traffic accident-prone areas is needed by the community and law enforcement. This information can be taken into consideration for supervision and anticipatory action, especially for the police. The initial stage of traffic accident prevention is to know the factors that cause traffic accidents obtained through traffic accident data analysis. The information system in this study analyzed traffic accident-prone areas in Asahan Regency. The analysis can be done with data mining, namely K-Means Clustering which can group data into several groups according to the characteristics of the data. The results of this study are the Asahan District Police Satlantas can find out the accident-prone areas in the most vulnerable categories, quite vulnerable and not vulnerable.
Co-Authors Aandanu Aandanu Adi Prijuna Lubis Aidil Adi Suhendra Apriaji Kurniawan Ayu Lestari Cindy Ross Dewi Maharani Donni Nasution Fauzy Maulana Sinaga Helmiah, Fauriatun Herman Saputra Herman Saputra Iqbal Kamil Siregar Jeperson Hutahaean Kifti, Wan Mariatul Kiki Andriani Masitah Handayani Nadya Viranika Nency Widya Monalisa Nofriadi Nofriadi Novi Silvana Kawila Nuriadi Manurung Nurul Rahmadani Nurwati Nurwati Nurwati Nurwati Oni Dewi Lestari Putri Sundari Renanda Eka Putri Risnawati Risnawati Rita Ratna sari Rohminatin Rohminatin Rohminatin Rohminatin Roni Dalimunthe Santoso Santoso SANTOSO SANTOSO Sri Puspita Dewi Sri Wahyuni Nasution Suriana Suriana Syafaat Sufi Lubis Syahira Syahira Tri Anjar Ningsih USWATUN HASANAH Wan Mariatul Kifti William Ramdhan