Abstract
As the most Moslem country, economic activity in Indonesia is often parallel with the movement of Qamariah (lunar) calendar which is different with Gregorian calendar. Using calender variation, this research attempts to look for modified time series model for non-cash payment projection (forecast) aim. The result shows that calendar variation plays statistically significant role on non-cash payment, evidenced by significant payment in the month in which Eid Fitr occurs. The occurrence of Eid Fitr in the first and second week of the month is evidently characterized by increasing non-cash payment in one month earlier. The best model with highest accuracy for non-cash payment projection is ARIMAX(2,1,1) as it is able to capture the pattern, trend and fluctuation. It also suggests the peak of non-cash payment will be in December.
Highlights
economic activity in Indonesia is often parallel with the movement of Qamariah
calendar which is different with Gregorian calendar
this research attempts to look for modified time series model for non-cash payment projection
Summary
Teknologi kian berkembang pesat, yang ditandai dengan aksesibilitas Internet yang makin luas. Berdasarkan data Statistik Sistem Keuangan Indonesia, segmen penggunaan instrumen pembayaran non-tunai dapat dibagi ke dalam dua jenis dimana jenis pertama adalah transaksi dengan nominal minimal Rp 1.000.000 yang didominasi oleh kartu debet/ATM dan kartu kredit. Hal ini untuk memudahkan peramalan (proyeksi) atas total pembayaran non-tunai sehingga pemerintah dapat merancang regulasi dan tindakan yang berkaitan dengan infrastruktur sistem keuangan, peredaran uang tunai dan sebagainya. Mengingat pentingnya peran sistem pembayaran non-tunai dalam menjaga stabilitas sistem keuangan, maka penelitian ini diangkat untuk melakukan identifikasi dan proyeksi terhadap total pembayaran non-tunai yang menggunakan APMK dan UE dengan konfigurasi variasi kalender. Beberapa model peramalan yang digunakan untuk proyeksi (forecasting) total pembayaran non-tunai via APMK dan UE, seperti regresi deret waktu, ARIMA dan ARIMAX, akan dibandingkan akurasinya
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