Daffa Malaeka Adyori, . (2025) ANALISIS CLUSTER UNTUK MENENTUKAN WILAYAH BERPOTENSI RESIKO KECELAKAAN PADA 13 RUAS TOL DI JABODETABEK DAN JABAR. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
![[img]](http://repository.upnvj.ac.id/style/images/fileicons/text.png) |
Text
ABSTRAK.pdf Download (14kB) |
|
Text
AWAL.pdf Download (398kB) |
|
Text
BAB 1.pdf Restricted to Repository UPNVJ Only Download (142kB) |
|
Text
BAB 2.pdf Restricted to Repository UPNVJ Only Download (443kB) |
|
Text
BAB 3.pdf Restricted to Repository UPNVJ Only Download (183kB) |
|
Text
BAB 4.pdf Restricted to Repository UPNVJ Only Download (874kB) |
|
Text
BAB 5.pdf Download (118kB) |
|
Text
DAFTAR PUSTAKA.pdf Download (152kB) |
|
Text
LAMPIRAN.pdf Restricted to Repository UPNVJ Only Download (2MB) |
|
Text
RIWAYAT HIDUP.pdf Restricted to Repository UPNVJ Only Download (87kB) |
|
Text
HASIL PLAGIARISME.pdf Restricted to Repository staff only Download (1MB) |
|
Text
ARTIKEL KI.pdf Restricted to Repository staff only Download (649kB) |
Abstract
Traffic accidents on toll roads are one of the significant problems in Indonesia, especially in the Jabodetabek and West Java regions. With the background of the increasing level of potential risk of accidents that affect things such as casualties, and heavily damaged vehicles, this study implements the K-Means Clustering method to group areas with accident risk levels in 13 toll roads in Jabodetabek and West Java. The data utilized covers the period 2020 to 2023 and includes the number of accidents, the number of fatalities, and the number of heavily damaged vehicles obtained from PT Jasa Marga. The analysis results show the optimal K value of 3, as supported by the Elbow Method, which shows a significant decrease in the Sum of Squared Errors (SSE) value until the number of clusters reaches 3. This study completed the grouping of toll road sections into three clusters: High Risk Potential Areas with moderate number of crashes and fatalities, Medium Risk Potential Areas with moderate number of crashes and high fatalities, and Low Risk Potential Areas with low number of crashes and low fatalities. Model evaluation using the Davies-Bouldin Index resulted in a score of 0.962, indicating good clustering quality. The results of data visualization were carried out using the Streamlit framework, which displays an interactive display for exploration and understanding of clustering results in various regions in 2020.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | No. Panggil: 2110512129 Pembimbing 1: Nur Hafifah Matondang Pembimbing 2: Nindy Irzavika Penguji 1: Ika Nurlaili Isnainiyah Penguji 2: Ati Zaidiah |
| Uncontrolled Keywords: | Traffic accident, K-Means Clustering, accident risk, data visualisation |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Sistem Informasi (S1) |
| Depositing User: | DAFFA MALAEKA ADYORI |
| Date Deposited: | 31 Jan 2025 04:29 |
| Last Modified: | 13 Mar 2025 03:38 |
| URI: | http://repository.upnvj.ac.id/id/eprint/35726 |
Actions (login required)
 |
View Item |