Analisis Peramalan Transaksi Harian Nasabah PT Indo Captital Sekuritas Menggunakan Metode Autoregressive Integrated Moving Average.

Pratama, Aditya Rizky (2024) Analisis Peramalan Transaksi Harian Nasabah PT Indo Captital Sekuritas Menggunakan Metode Autoregressive Integrated Moving Average. Project Report. [s.n], [s.l.]. (Unpublished)

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Abstract

Laporan ini membahas pelaksanaan kerja praktik di PT Indo Capital Sekuritas, khususnya di divisi settlement, dengan fokus pada analisis peramalan transaksi harian nasabah menggunakan metode Autoregressive Integrated Moving Average (ARIMA). Penelitian ini melibatkan pengumpulan dan analisis data transaksi harian nasabah selama periode Januari–Desember 2023. Hasilnya menunjukkan model ARIMA (1,1,2) sebagai model terbaik untuk peramalan, dengan estimasi transaksi yang stabil di masa mendatang. Melalui kerja praktik ini, penulis memperoleh pemahaman tentang proses penyelesaian transaksi saham, akurasi data, dan analisis kuantitatif berbasis statistik, yang relevan dalam mendukung efisiensi operasional perusahaan.
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This report discusses the implementation of an internship program at PT Indo Capital Sekuritas, specifically in the settlement division, focusing on forecasting daily customer transactions using the Autoregressive Integrated Moving Average (ARIMA) method. The research involved collecting and analyzing daily customer transaction data for the period of January–December 2023. The results identified the ARIMA (1,1,2) model as the best-fit model for forecasting, with stable transaction estimates for the future. Through this internship, the author gained insights into the process of stock transaction settlement, data accuracy, and statistical-based quantitative analysis, which are relevant to supporting the company's operational efficiency.

Item Type:	Monograph (Project Report)
Uncontrolled Keywords:	Kerja Praktik, PT Indo Capital Sekuritas, ARIMA, Peramalan, Internship, Forecasting
Subjects:	Q Science > QA Mathematics > QA276 Mathematical statistics. Time-series analysis. Failure time data analysis. Survival analysis (Biometry) Q Science > QA Mathematics > QA280 Box-Jenkins forecasting Q Science > QA Mathematics > QA401 Mathematical models.
Divisions:	Faculty of Mathematics, Computation, and Data Science > Actuaria > 94203-(S1) Undergraduate Thesis
Depositing User:	Aditya Rizky Pratama
Date Deposited:	20 Jan 2025 01:23
Last Modified:	20 Jan 2025 01:23
URI:	http://repository.its.ac.id/id/eprint/116322

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