Erlangga, Bhimo (2024) Analisis Peramalan Jumlah Klaim Program Jaminan Hari Tua (JHT) BPJS Ketenagakerjaan Surabaya Karimunjawa Menggunakan Metode Autoregressive Integrated Moving Average (ARIMA). Project Report. [s.n.], [s.l.]. (Unpublished)
![[thumbnail of 5006211051-Project_Report.pdf]](http://repository.its.ac.id/style/images/fileicons/text.png) |
Text
5006211051-Project_Report.pdf - Accepted Version Restricted to Repository staff only Download (2MB) | Request a copy |
Abstract
BPJS Ketenagakerjaan merupakan badan penyelenggara jaminan sosial yang memiliki tanggung jawab dalam memberikan perlindungan sosial ekonomi kepada pekerja di Indonesia, salah satunya melalui program Jaminan Hari Tua (JHT). Untuk mendukung pengambilan keputusan yang lebih baik dalam pengelolaan dana JHT, diperlukan suatu metode peramalan yang mampu memprediksi jumlah klaim di masa mendatang secara akurat. Penelitian ini bertujuan untuk meramalkan jumlah klaim JHT BPJS Ketenagakerjaan Cabang Surabaya Karimunjawa menggunakan metode Autoregressive Integrated Moving Average (ARIMA). Data yang digunakan adalah jumlah klaim bulanan dari Januari 2020 hingga Desember 2023. Tahapan analisis dimulai dari transformasi data, uji stasioneritas varians dengan Box-Cox, uji stasioneritas mean melalui differencing, identifikasi model menggunakan plot ACF dan PACF, estimasi parameter, serta uji diagnostik residual melalui uji white noise dan normalitas. Dari beberapa model yang dicoba, diperoleh bahwa model ARIMA(1,1,1) merupakan model terbaik berdasarkan nilai Akaike Information Criterion (AIC) terkecil dan kelulusan terhadap uji diagnostik residual. Model ini kemudian digunakan untuk melakukan peramalan jumlah klaim lima bulan ke depan, yaitu dari Januari hingga Mei 2024. Hasil peramalan menunjukkan jumlah klaim berada pada rentang 2397 hingga 2624 klaim per bulan, dengan batas bawah dan atas yang menggambarkan ketidakpastian estimasi. Hasil ini diharapkan dapat menjadi bahan pertimbangan bagi BPJS Ketenagakerjaan dalam merancang strategi operasional dan pengelolaan keuangan program JHT secara lebih efisien dan terarah. Selain itu, penggunaan metode ARIMA dalam konteks ini menunjukkan bahwa pendekatan statistik time series mampu memberikan hasil yang andal dalam mendukung pengambilan keputusan di sektor jaminan sosial.
==================================================================================================================================
BPJS Ketenagakerjaan is a social security agency responsible for providing economic protection to workers in Indonesia, one of which is through the Old Age Security (JHT) program. To support better decision-making in managing JHT funds, an accurate forecasting method is required to predict future claim volumes. This study aims to forecast the number of JHT claims at the Surabaya Karimunjawa Branch Office using the Autoregressive Integrated Moving Average (ARIMA) method. The data used consists of monthly claim figures from January 2020 to December 2023. The analysis process includes data transformation, variance stationarity testing using Box-Cox, mean stationarity testing through differencing, model identification using ACF and PACF plots, parameter estimation, and residual diagnostics through white noise and normality tests. Among several candidate models, ARIMA(1,1,1) was selected as the best model based on the lowest Akaike Information Criterion (AIC) value and its compliance with residual diagnostic tests. This model was then applied to forecast the number of JHT claims for the next five months, from January to May 2024. The forecast results showed monthly claims ranging between 2,397 and 2,624, with lower and upper bounds indicating the confidence intervals of the estimates. These results are expected to serve as a useful reference for BPJS Ketenagakerjaan in planning operational strategies and financial management of the JHT program more effectively. Furthermore, the application of the ARIMA method in this context demonstrates that statistical time series models can provide reliable insights to support policy and operational decisions in the field of social security.
| Item Type: | Monograph (Project Report) |
|---|---|
| Uncontrolled Keywords: | Forecasting, ARIMA, Time Series, Old Age Security, BPJS Ketenagakerjaan, Peramalan, ARIMA, Time Series, JHT, BPJS Ketenagakerjaan |
| Subjects: | H Social Sciences > HA Statistics H Social Sciences > HA Statistics > HA30.3 Time-series analysis |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Actuaria > 94203-(S1) Undergraduate Thesis |
| Depositing User: | Bhimo Erlangga |
| Date Deposited: | 28 Jul 2025 02:46 |
| Last Modified: | 28 Jul 2025 02:46 |
| URI: | http://repository.its.ac.id/id/eprint/122374 |
Actions (login required)
 |
View Item |