Penerapan Metode Autoregressive Integrated Moving Average (ARIMA) dalam Peramalan Laju Inflasi di Kabupaten Tuban

Eraswati, Kadek Imelda Anindra (2024) Penerapan Metode Autoregressive Integrated Moving Average (ARIMA) dalam Peramalan Laju Inflasi di Kabupaten Tuban. Project Report. [s.n.], [s.l.]. (Unpublished)

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Abstract

Inflasi merupakan fenomena ekonomi yang ditandai dengan meningkatnya harga barang dan jasa secara umum dan terus-menerus dalam suatu periode, yang dapat memengaruhi daya beli masyarakat dan kestabilan ekonomi daerah. Di Kabupaten Tuban, laju inflasi juga mengalami fluktuasi dari tahun ke tahun, sehingga diperlukan upaya untuk memantau dan meramalkannya secara akurat. Penelitian ini bertujuan untuk menganalisis dan memprediksi laju inflasi bulanan di Kabupaten Tuban berdasarkan data periode 2014 hingga 2023 yang diperoleh dari publikasi Statistik Daerah dan Berita Resmi Statistik BPS Kabupaten Tuban. Metode yang digunakan meliputi statistika deskriptif, model Autoregressive Integrated Moving Average (ARIMA), serta evaluasi akurasi menggunakan Mean Absolute Percentage Error (MAPE). Hasil analisis menunjukkan bahwa data inflasi telah bersifat stasioner, sehingga tidak memerlukan proses differencing. Dari delapan model awal yang dibentuk, tiga model signifikan berhasil diidentifikasi, yaitu AR(1), AR(2), dan MA(1), dengan model AR(2) sebagai model terbaik berdasarkan nilai P-Value dan evaluasi lanjutan. Model ini menghasilkan nilai MAPE sebesar 30,74%, yang tergolong layak untuk keperluan peramalan. Peramalan dilakukan untuk 12 bulan ke depan (Januari–Desember 2024), dan menunjukkan pola fluktuatif di awal serta kecenderungan stabil di akhir periode. Hasil peramalan ini diharapkan dapat menjadi dasar pertimbangan dalam penyusunan strategi pengendalian inflasi daerah. Penelitian ini juga menyarankan pengembangan lebih lanjut dengan menggunakan model musiman seperti SARIMA dan ARIMA Subset untuk meningkatkan akurasi hasil peramalan.
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Inflation is an economic phenomenon characterized by a general and continuous increase in the prices of goods and services over a certain period, which can affect people's purchasing power and regional economic stability. In Tuban Regency, the inflation rate has also fluctuated from year to year, requiring efforts to monitor and forecast it accurately. This study aims to analyze and predict the monthly inflation rate in Tuban Regency using data from 2014 to 2023 obtained from the Regional Statistics publication and the Official Statistics Report published by BPS Tuban Regency. The methods used include descriptive statistics, the Autoregressive Integrated Moving Average (ARIMA) model, and accuracy evaluation using the Mean Absolute Percentage Error (MAPE). The analysis results show that the inflation data is stationary, so no differencing process is required. From the eight initial models formed, three significant models were identified, namely AR(1), AR(2), and MA(1), with AR(2) selected as the best model based on P-Value and further evaluations. This model produced a MAPE value of 30.74%, which is considered acceptable for forecasting purposes. Forecasting was conducted for the next 12 months (January–December 2024), showing fluctuations in the early period and a stable trend in the later period. The forecasting results are expected to serve as a basis for consideration in formulating regional inflation control strategies. This study also recommends further development using seasonal models such as SARIMA and ARIMA Subset to improve forecasting accuracy.

Item Type:	Monograph (Project Report)
Uncontrolled Keywords:	ARIMA, Forecasting, Inflation, MAPE, Tuban Regency, ARIMA, Inflasi, Kabupaten Tuban, MAPE, Peramalan
Subjects:	H Social Sciences > HB Economic Theory > Economic forecasting--Mathematical models.
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Actuaria > 94203-(S1) Undergraduate Thesis
Depositing User:	Kadek Imelda Anindra Eraswati
Date Deposited:	11 Jul 2025 00:42
Last Modified:	11 Jul 2025 00:42
URI:	http://repository.its.ac.id/id/eprint/119573

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