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This Author published in this journals
All Journal International Journal of Quantitative Research and Modeling International Journal of Ethno-Sciences and Education Research
Riza Andrian Ibrahim
Doctoral of Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Sumedang 45363, Indonesia
Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Physics Transportation Other

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The Impact of Smartphone Use on the Psychology of Young Children in Parungponteng District Riza Andrian Ibrahim; Astrid Sulistya Azahra; Nurnisaa binti Abdullah Suhaimi
International Journal of Ethno-Sciences and Education Research Vol 4, No 1 (2024)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijeer.v4i1.566

Abstract

This research aims to analyze the impact of gadget use on the psychological development of elementary school-aged children at Cibuntu Elementary School, Cibungur Village, Parungponteng District. The research method used is a qualitative approach using observation, questionnaires and interviews as data collection techniques. The research results show that the use of gadgets has both positive and negative impacts on children's psychological development. Positive impacts include improved cognitive skills and access to information, while negative impacts include the risk of addiction and behavioral disorders. The role of parents and schools in supervising and directing gadget use is very important to minimize negative impacts. This research provides a comprehensive picture of the complexity of the interaction between technology and child development.
Determining the Pure Premium at Jasa Raharja Insurance Company Purwakarta Branch using Fast Fourir Transform (FFT) through Estimated Aggregate Loss Distribution Rifki Saefullah; Riza Andrian Ibrahim
International Journal of Quantitative Research and Modeling Vol. 5 No. 4 (2024): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i4.815

Abstract

Insurance is a contractual agreement between two parties, namely the insured party (customer) and the insurer (insurance company), in which the insured party pays a premium to the insurer, then in return, the insurer will provide compensation (claim) to the insured party if an insured event occurs. Each customer is required to pay a premium as an obligation stated in the insurance agreement by paying a premium, the customer fulfills his obligations and is entitled to the benefits stated in the policy. Therefore, the Insurance Company needs to carry out a scheme in the process of paying pure premiums for the sustainability of the insurance company. When determining the premium, it is done by estimating the aggregate loss distribution. This research will calculate thepure premium at the Purwakarta Branch of Jasa Raharja Insurance Company. The model used in this study is the distribution of aggregate loss with a compound distribution of claim frequency and claim size. Many claims follow the Poisson distribution and large claims follow the Lognormal distribution. In the process of estimating the probability of aggregate loss with the compound distribution model, the Inverse method with the Fast Fourier Transform (FFT) algorithm is used. This research will provide understanding and insight to insurance companies in determining the amount of premium that must be charged to customers.
Mean-VaR Portfolio Diversification Based on K-Medoids Clustering Deva Putra Setyawan; Alim Jaizul Wahid; Riza Andrian Ibrahim
International Journal of Quantitative Research and Modeling Vol. 7 No. 2 (2026): International Journal of Quantitative Research and Modeling (IJQRM)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v7i2.1330

Abstract

This study develops a diversified stock portfolio by integrating the Mean-Value at Risk (Mean-VaR) model with K-Medoids clustering. The approach groups stocks according to similar risk-return characteristics before the portfolio optimization stage. The data consist of daily closing prices of LQ45 index constituents from 3 February to 31 July 2025, obtained from the Indonesia Stock Exchange and Yahoo Finance. Of the 45 LQ45 stocks, 18 stocks satisfied the criteria of data completeness, liquidity, market capitalization stability, and sector representation. Clustering was performed using expected return and 95% Value at Risk (VaR) as input variables. The best clustering structure was obtained for two clusters, with a Silhouette Index of 0.6882. The first cluster represents aggressive stocks with relatively high expected returns and higher downside risk, including ANTM, BRPT, AMMN, and MDKA. The second cluster represents defensive stocks with lower risk and more stable returns, including INDF, ASII, ICBP, BBCA, and TLKM. The optimal Mean-VaR portfolio was constructed with minimum inter-cluster allocation constraints of 30% for the aggressive cluster and 70% for the defensive cluster. The resulting portfolio produced a daily expected return of 0.003272 and a 95% VaR of -0.029053. These results indicate that K-Medoids clustering can support portfolio diversification by identifying distinct risk-return groups and improving risk control in investment allocation.
Co-Authors Alim Jaizul Wahid Astrid Sulistya Azahra Deva Putra Setyawan Nurnisaa binti Abdullah Suhaimi Rifki Saefullah