Peramalan Kejadian Kecelakaan di Surabaya dengan Metode Sarima: Studi Kasus Data Call Center

Zavira, Hanif Ziva and Luthfiya, Imara Peramalan Kejadian Kecelakaan di Surabaya dengan Metode Sarima: Studi Kasus Data Call Center. Project Report (Praktek Kerja Lapang dan Magang). UPN Veteran Jawa Timur. (Unpublished)

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Abstract

This internship program was carried out at the Surabaya Regional Disaster Management Agency (BPBD), a local government institution responsible for handling various types of emergency incidents, including natural disasters, fires, medical emergencies, and traffic accidents. The main focus of the internship, which lasted for more than four months, was to utilize historical data from the Call Center 112—particularly records of traffic accidents—for predictive analysis. The objective was to develop a monthly forecasting model for the number of traffic accidents in Surabaya to support better risk mitigation and emergency planning. The forecasting method applied was SARIMA, a time series approach suitable for modeling seasonal patterns in historical data. Accident records from 2022 to 2024 were used to train the model and generate forecasts for the year 2025. The results show that SARIMA is capable of producing reliable forecasts with relatively low error rates, and the projected trends suggest a stable seasonal pattern in accident occurrences. All findings were visualized through interactive dashboards and time series plots to facilitate interpretation. Through thisinternship, the student gained hands-on experience in applying statistical methods to real-world data while contributing to data-driven policy development in a government setting.

Item Type:

Monograph (Project Report (Praktek Kerja Lapang dan Magang))

Contributors:

Contribution	Contributors	NIDN/NIDK	Email
Thesis advisor	Adziima, Andri Fauzan	NUPTK9844773674130292	andri.fauzan.fasilkom@upnjatim.ac.id
UNSPECIFIED	Trimono, Trimono	NIDN0008099501	trimono.stat@upnjatim.ac.id

Subjects:

Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science

Divisions:

Faculty of Computer Science > Departemen of Data Science

Depositing User:

Hanif Ziva Zavira

Date Deposited:

20 Jul 2026 06:47

Last Modified:

20 Jul 2026 06:47

URI:

https://repository.upnjatim.ac.id/id/eprint/56212