Peramalan Volume Transaksi dengan Alat Pembayaran Non Tunai (APNT) Menggunakan Vector Autoregressive (VAR)

Abu Sifa, Muhammad Hasan Alwi (2026) Peramalan Volume Transaksi dengan Alat Pembayaran Non Tunai (APNT) Menggunakan Vector Autoregressive (VAR). Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Perkembangan sistem pembayaran digital di Indonesia menunjukkan pertumbuhan yang pesat, terutama dengan meningkatnya penggunaan alat pembayaran non tunai (APNT) seperti Kartu Kredit, Kartu Debit, e-money, dan QRIS. Dinamika penggunaan berbagai instrumen tersebut mencerminkan pergeseran perilaku masyarakat dalam melakukan transaksi keuangan. Penelitian ini bertujuan untuk meramalkan Volume Transaksi Belanja APNT dengan menggunakan pendekatan ekonometrika melalui model Vector Auto Regressive (VAR). Penelitian ini menggunakan data bulanan dari Januari 2020 hingga Februari 2025 yang diperoleh dari Bank Indonesia. Tahapan analisis meliputi uji stasioneritas, identifikasi model menggunakan nilai AIC, MACF, dan MPACF, estimasi parameter, Diagnostic Checking, serta evaluasi model menggunakan nilai MAE, MAPE, RMSE. Hasil penelitian menunjukkan bahwa model VAR hanya menggambarkan hubungan pada Kartu Debit dan e-money sementara pada Kartu Kredit dan QRIS menunjukkan hubungan dengan dirinya sendiri sehingga dilakukan pemodelan VAR pada Kartu Debit dan e-money kemudian pemodelan ARIMA untuk Kartu Kredit dan QRIS. Peramalan pada Kartu Kredit, Kartu Debit, dan e-money menunjukkan kenaikan sedangkan pada QRIS menunjukkan penurunan.
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The development of digital payment systems in Indonesia shows rapid growth, especially with the increasing use of non-cash payment instruments (APNT) such as credit cards, debit cards, e-money, and QRIS. The dynamics of the use of these various instruments reflect shifts in people's behavior in conducting financial transactions. This study aims to forecast the volume of APNT shopping transactions using an econometric approach through the Vector Auto Regressive (VAR) model. This study uses monthly data from January 2020 to February 2025 obtained from Bank Indonesia. The analysis stages include stationarity testing, model identification using AIC, MACF, and MPACF values, parameter estimation, Diagnostic Checking, and model evaluation using MAE, MAPE, and RMSE values. The results show that the VAR model only describes the relationship between debit cards and e-money, while credit cards and QRIS show a relationship with themselves. Therefore, VAR modeling is carried out on debit cards and e-money, then ARIMA modeling for credit cards and QRIS. Forecasts for credit cards, debit cards, and e-money show an increase, while for QRIS shows a decrease.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Alat Pembayaran Non Tunai, Volume Transaksi, Vector Auto Regressive, QRIS, Kartu Kredit, E-money. Non-Cash Payment Instruments, Transaction Volume, Vector Auto Regressive, QRIS, Credit Card, Electronic Money.
Subjects:	H Social Sciences > HA Statistics H Social Sciences > HA Statistics > HA30.3 Time-series analysis H Social Sciences > HB Economic Theory > Economic forecasting--Mathematical models. H Social Sciences > HC Economic History and Conditions > HC441 Macroeconomics. L Education > L Education (General)
Divisions:	Faculty of Vocational > 49501-Business Statistics
Depositing User:	Muhammad Hasan Alwi Abu Sifa
Date Deposited:	15 Jun 2026 01:18
Last Modified:	15 Jun 2026 01:18
URI:	http://repository.its.ac.id/id/eprint/133781

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