Nayla, Aisyah (2025) Peramalan Indeks Harga Konsumen (IHK) Provinsi Jawa Timur Menggunakan Model Vector Autoregressive (VAR). Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Indeks Harga Konsumen (IHK) adalah indikator utama dalam mengukur inflasi dan kestabilan harga di suatu wilayah, yang dipengaruhi oleh beberapa sektor utama seperti Makanan, Perumahan, dan Kesehatan. IHK diramalkan karena fluktuasi harga yang dapat mempengaruhi daya beli masyarakat dan stabilitas ekonomi, terutama di Jawa Timur yang memiliki peran ekonomi besar. Peninjauan terhadap IHK penting untuk menjaga daya beli masyarakat dan mendukung pertumbuhan ekonomi yang berkelanjutan di provinsi ini. Penelitian ini bertujuan untuk memperoleh model VAR, menganalisis hubungan antar variabel dalam peramalan IHK, serta sektor-sektor terkait, dan mengevaluasi akurasi hasil peramalan menggunakan MAPE. Metode yang digunakan adalah Vector Autoregression (VAR) dengan data deret waktu bulanan dari Januari 2015 hingga Desember 2024. Model VAR dipilih karena kemampuannya untuk memodelkan hubungan simultan antar variabel multivariat. Model yang digunakan dalam penelitian ini adalah VAR(1), dengan semua parameter. Hasil penelitian menunjukkan bahwa model VAR(1) menghasilkan peramalan yang konsisten dengan pola historis data, dengan kelanjutan tren yang sejalan. Evaluasi menggunakan nilai MAPE menunjukkan bahwa model ini memiliki akurasi yang baik, dengan nilai keseluruhan sebesar 1.033%, oleh karena itu, model VAR(1) dinilai layak digunakan untuk meramalkan IHK dan variabel sektoral terkait.
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The Consumer Price Index (CPI) is a key indicator in measuring inflation and price stability in a region, which is influenced by several key sectors such as Food, Housing, and Health. The CPI is forecasted due to price fluctuations that can affect people's purchasing power and economic stability, especially in East Java which has a large economic role. A review of the CPI is important to maintain people's purchasing power and support sustainable economic growth in the province. This study aims to obtain a VAR model, analyze the relationship between variables in CPI forecasting, as well as related sectors, and evaluate the accuracy of forecasting results using MAPE. The method used is Vector Autoregression (VAR) with monthly time series data from January 2015 to December 2024. The VAR model was chosen because of its ability to model simultaneous relationships between multivariate variables. The model used in this study is VAR(1), with all relevant parameters. The results showed that the VAR(1) model produced forecasts that were consistent with the historical pattern of the data, with relatively appropriate trend continuation. Evaluation using the MAPE value shows that the model has good accuracy, with an overall value of 1.033%, therefore, the VAR(1) model is considered feasible to use for forecasting CPI and related sectoral variables.
Item Type: | Thesis (Other) |
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Uncontrolled Keywords: | IHK, VAR, Peramalan, CPI, VAR, Forecasting |
Subjects: | Q Science > QA Mathematics > QA276 Mathematical statistics. Time-series analysis. Failure time data analysis. Survival analysis (Biometry) Q Science > QA Mathematics > QA401 Mathematical models. |
Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44201-(S1) Undergraduate Thesis |
Depositing User: | Aisyah Nayla |
Date Deposited: | 01 Aug 2025 02:41 |
Last Modified: | 01 Aug 2025 02:41 |
URI: | http://repository.its.ac.id/id/eprint/124759 |
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