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All Journal JURNAL ILMIAH MATEMATIKA DAN TERAPAN ESTIMASI: Journal of Statistics and Its Application
Alimatun Najiha
Universitas Tadulako
Mathematics

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Nilai Risiko Terkondisi pada Return Finansial Menggunakan Metode Copula Gumbel Najiha Alimatun; Anisa Anisa; Andi Kresna Jaya
ESTIMASI: Journal of Statistics and Its Application Vol. 3, No. 1, Januari, 2022 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.vi.12246

Abstract

The calculation of VaR is assumed normal distribution while the conditions in the real world distribution conditions of the return value depends on the market conditions that occurred at the time. Thus, this makes VaR estimates invalid which results in portfolio risk occurring greater than the predetermined risk. Therefore, In this study, the estimated risk value uses the Conditional Value at Risk (CVaR), which measures the expected value depending on what is the worst percentage of the risk loss, and using Copula Gumbel to model financial return in the investment data of PT. Telkomunikasi Indonesia tbk and PT. XL Axiata tbk. for the period March 11, 2019 to March 10, 2020. In this study, the CVaR estimation results for the 99% confidence level is 0.231, while for the VaR estimate it is 0.192. This indicates that risk value with CVaR estimate is better able to show higher risk than VaR.
Comparison of Random Survival Forest and Fuzzy Random Survival Forest Models in Telecommunications Industry Customer Data Nurhaliza, Sitti; Harismahyanti, Andi; Najiha, Alimatun
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 21 No. 2 (2024)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/2540766X.2024.v21.i2.17498

Abstract

The telecommunications sector is facing increasing competition, and customer churn is still a majorchallenge despite the implementation of advanced promotions and high-quality services. Churn refers tothe discontinuation of services by customers, influenced by several factors that can be found through datamodeling. This study compares two predictive models, Random Survival Forest (RSF) and Fuzzy RandomSurvival Forest (FRSF), for predicting customer churn time in the telecommunications industry. Bothmodels are evaluated using the median C-index value obtained from 20 repetitions, ensuring moreconsistent and reliable results. RSF, a widely used survival analysis method, has shown strong predictivepower, with studies reporting up to 99% accuracy in churn prediction. However, FRSF, a modified versionthat incorporates fuzzy logic, has proved superior performance, particularly in handling imprecise oruncertain data. The results show that FRSF achieves a lower error rate of 0.1739, compared to RSF's errorrate of 0.1906. These findings suggest that FRSF outperforms RSF in churn prediction, making it a morereliable and righter model for finding at-risk customers. The study concludes that the FRSF model is thepreferred choice for predicting churn in the telecommunications industry, offering better predictive qualityand consistency in handling uncertain data.
Co-Authors Andi Kresna Jaya Anisa Anisa Harismahyanti A., Andi Sitti Nurhaliza