Parapat, Ave Gomos and Panggabean, Jeremia (2024) Analisis Jam Rawan Kecelakaan Berdasarkan Hari dengan Menggunakan Metode Agglomerative Hierarchical Clustering. Project Report. [s.n.], [s.l.]. (Unpublished)
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Abstract
Laporan kerja praktik ini disusun berdasarkan kegiatan yang dilaksanakan di PT Jasa Raharja Cabang Utama Jawa Timur selama dua bulan. Fokus utama dari kegiatan ini adalah analisis jam rawan kecelakaan berdasarkan hari dengan menggunakan metode Agglomerative Hierarchical Clustering. Data yang digunakan merupakan data sekunder kecelakaan lalu lintas di Provinsi Jawa Timur selama tahun 2023. Penelitian dimulai dengan analisis deskriptif terhadap jumlah kecelakaan per jam, yang menunjukkan bahwa pukul 07.00 memiliki rata-rata kecelakaan tertinggi, sedangkan pukul 00.00 terendah. Selanjutnya, metode clustering dengan pendekatan Ward digunakan untuk mengelompokkan jam ke dalam empat cluster berdasarkan tingkat kerawanan. Hasilnya menunjukkan bahwa cluster 4 (pukul 06.00–07.00) adalah waktu paling rawan kecelakaan, terutama pada hari kerja seperti Senin dan Jumat. Sebaliknya, cluster 1 (malam hingga dini hari) merupakan waktu dengan tingkat kerawanan paling rendah. Visualisasi boxplot per hari memperkuat hasil analisis tersebut. Temuan ini diharapkan dapat membantu PT Jasa Raharja dalam memetakan pola waktu kecelakaan serta merancang strategi pencegahan yang lebih efektif, terutama pada jam dan hari dengan tingkat risiko tinggi.
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This internship report is based on a two-month program conducted at PT Jasa Raharja, East Java Main Branch. The primary focus of the project was to analyze accident-prone hours by day using the Agglomerative Hierarchical Clustering method. The study utilized secondary data of traffic accidents in East Java throughout 2023. The analysis began with descriptive statistics, revealing that 07:00 AM had the highest average number of accidents, while 00:00 AM had the lowest. The clustering process applied Ward’s method to group the hours into four clusters based on accident risk levels. The results showed that Cluster 4 (06:00–07:00 AM) represented the most accident-prone period, especially on weekdays such as Monday and Friday. Conversely, Cluster 1 (late night to early morning) represented the least risky hours. Daily boxplot visualizations supported these findings by highlighting differences in accident patterns across days. The outcomes of this analysis are expected to assist PT Jasa Raharja in mapping accident time patterns and formulating more effective prevention strategies, particularly during high-risk hours and days.
| Item Type: | Monograph (Project Report) |
|---|---|
| Uncontrolled Keywords: | Kecelakaan lalu lintas, Jam Rawan, Klasterisasi, Metode Ward, Jasa Raharja |
| Subjects: | Q Science > QA Mathematics > QA278 Cluster Analysis. Multivariate analysis. Correspondence analysis (Statistics) |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Actuaria > 94203-(S1) Undergraduate Thesis |
| Depositing User: | Ave Gomos Parapat |
| Date Deposited: | 23 Jul 2025 04:25 |
| Last Modified: | 23 Jul 2025 04:25 |
| URI: | http://repository.its.ac.id/id/eprint/120331 |
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