Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal VARIANSI: Journal of Statistics and Its Application on Teaching and Research Mikailalsys Journal of Mathematics and Statistics
Avrilia, Khairunnisa
Unknown Affiliation
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics Mechanical Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Comparison of Value at Risk (VaR) in Risk Analysis: Historical, Variance Covariance and Monte Carlo Methods Fauziyah, Meirinda; Dani, Andrea Tri Rian; Koirudin, Hadi; Budi, Ennesya Estya; Avrilia, Khairunnisa; Watika, Noor Hikmah
Mikailalsys Journal of Mathematics and Statistics Vol 2 No 3 (2024): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v2i3.3778

Abstract

Value at Risk (VaR) is a method used to measure financial risk in a company. VaR calculations are often used to calculate the level of loss from shares in a company, such as bank shares. The aim of this research is to determine the level of losses in Bank Central Asia shares using the historical method, the Variance-covariance method, and the Monte Carlo method. the results showed that with an initial investment of $50 and using the Historical method at a significant level of 95%, the VaR value was obtained at $16.42 or IDR. 267.301 and at the 90% significant level, the VaR value was obtained at $12.41 or IDR. 202.022. Based on the Variance-covariance method with an initial investment of 50$ at the 95% significant level, the VaR value is obtained at $16.42 or IDR. 267,301 and at the 90% significant level, the VaR value is obtained at $12.79 or IDR. 208.208. Meanwhile, based on the Monte Carlo method with an initial investment of $50, at a significant level of 95%, the VaR value is obtained at $16.46 or IDR. 267,952 and at the 90% significance level, the VaR value is obtained at $12.84 or IDR. 209.022. Based on the three methods used, it was concluded that the Monte Carlo method gave greater results compared to the other two methods.
Implementasi Model Hybrid Autoregressive Fractionally Integrated Moving Average-Neural Network (ARFIMA-NN) pada Peramalan Indeks Harga Saham Gabungan Avrilia, Khairunnisa; Yuniarti, Desi; Nurmayanti, Wiwit Pura; Fathurahman, M.; Wahyuningsih, Sri
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 8 No. 1 (2026)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm487

Abstract

Fenomena fluktuasi ekstrem pada harga penutupan Indeks Harga Saham Gabungan (IHSG) di Bursa Efek Indonesia (BEI) menciptakan ketidakpastian yang sulit diprediksi, sehingga peramalan pada data harga penutupan IHSG dapat membantu investor untuk mengantisipasi risiko investasi dan mempermudah investor untuk menentukan strategi investasi pada periode mendatang. Model hybrid Autoregressive Fractionally Integrated Moving Average-Neural Network (ARFIMA-NN) diimplementasikan karena model ini mampu menangani karakteristik long memory dan memiliki kemampuan menangkap pola non-linier, yang diharapkan dapat meningkatkan akurasi pada peramalan. Berdasarkan hasil analisis, diperoleh hasil peramalan menggunakan model hybrid ARFIMA-NN dengan 1 hingga 3 neuron yang menunjukkan bahwa nilai MAPE berada di bawah 10% atau peramalan sangat baik. Selanjutnya berdasarkan model hybrid ARFIMA(1;0,51;4)-NN 2 menggunakan data IHSG periode Januari 2005 hingga dengan Desember 2024 diperoleh IHSG periode Januari hingga Desember 2025 yang meningkat setiap bulannya.
Co-Authors Budi, Ennesya Estya Dani, Andrea Tri Rian Fauziyah, Meirinda Koirudin, Hadi M. Fathurahman Nurmayanti, Wiwit Pura Nurwijayanti Watika, Noor Hikmah Yuniarti, Desi