Puspita, Adinda Puja (2024) Penerapan Metode Autoregressive Integrated Moving Average (ARIMA) dalam Peramalan Sumbangan Wajib Dana Kecelakaan Lalu Lintas Jalan Kabupaten Bojonegoro. Project Report. [s.n.], [s.l.]. (Unpublished)
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Abstract
Kerja praktik ini dilaksanakan di PT Jasa Raharja Perwakilan Bojonegoro dengan tujuan menerapkan ilmu aktuaria dalam dunia kerja, khususnya dalam kegiatan analisis dan peramalan data. Fokus utama dari kegiatan ini adalah melakukan peramalan terhadap pendapatan Sumbangan Wajib Dana Kecelakaan Lalu Lintas Jalan (SWDKLLJ) di Kabupaten Bojonegoro menggunakan metode Autoregressive Integrated Moving Average (ARIMA). Data yang digunakan merupakan data time series bulanan dari Januari 2014 hingga Juni 2024. Proses analisis dimulai dari visualisasi dan analisis statistik deskriptif, pengujian stasioneritas dalam rata-rata dan varians, identifikasi model ARIMA dengan ACF dan PACF, estimasi dan uji signifikansi parameter, serta pemeriksaan diagnostik terhadap residual. Model terbaik ditentukan berdasarkan nilai AIC terkecil serta hasil evaluasi dengan Mean Absolute Percentage Error (MAPE). Hasil peramalan menunjukkan bahwa model ARIMA dapat digunakan secara efektif untuk memproyeksikan pendapatan SWDKLLJ di periode mendatang, dengan tingkat akurasi yang tergolong baik. Penelitian ini diharapkan dapat memberikan kontribusi dalam mendukung proses perencanaan dan pengambilan keputusan di PT Jasa Raharja.
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This internship was conducted at PT Jasa Raharja Bojonegoro Representative Office with the aim of applying actuarial science in the workplace, particularly in data analysis and forecasting activities. The main focus of this activity was to forecast the revenue of the Mandatory Road Traffic Accident Fund (SWDKLLJ) in Bojonegoro Regency using the Autoregressive Integrated Moving Average (ARIMA) method. The data used was monthly time series data from January 2014 to June 2024. The analysis process began with visualization and descriptive statistical analysis, stationarity testing in the mean and variance, identification of the ARIMA model with ACF and PACF, parameter estimation and significance testing, and diagnostic examination of the residuals. The best model was determined based on the smallest AIC value and the results of the evaluation using the Mean Absolute Percentage Error (MAPE). The forecasting results showed that the ARIMA model can be used effectively to project SWDKLLJ revenue in the future period, with a relatively good level of accuracy. This research is expected to contribute to supporting the planning and decision-making process at PT Jasa Raharja.
| Item Type: | Monograph (Project Report) |
|---|---|
| Uncontrolled Keywords: | ARIMA,Jasa Raharja,Kerja Praktik,Peramalan,Time Series ARIMA, Jasa Raharja, Forecasting, Practical Work, Time Series |
| Subjects: | Q Science > QA Mathematics > QA276 Mathematical statistics. Time-series analysis. Failure time data analysis. Survival analysis (Biometry) |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Actuaria > 94203-(S1) Undergraduate Thesis |
| Depositing User: | Adinda Puja Puspita |
| Date Deposited: | 31 Jul 2025 03:04 |
| Last Modified: | 31 Jul 2025 03:04 |
| URI: | http://repository.its.ac.id/id/eprint/124777 |
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