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Classification of types A and A_+ from low dimensional standard and non-standard filiform Lie Algebras Kurniadi, Edi; Parmikanti, Kankan; Badrulfalah, Badrulfalah
Journal of Natural Sciences and Mathematics Research Vol. 9 No. 2 (2023): December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In this paper, we study low-dimensional Filiform Lie algebras. Specifically, three-dimensional standard Filiform Lie algebras and five-dimensional non-standard Filiform Lie algebras. The classification method was given in the following stage. For given a low-dimensional Filiform Lie algebra, we compute its second centre. We showed that three-dimensional Filiform Lie algebra-called Heisenberg Lie algebra-is type ???? and ????+ as well. On the other hand, for ????≥3, the standard Filiform Lie algebras are type ???? but not type ????+. In this case, we give a concrete example of case five-dimensional Heisenberg Lie algebra. Moreover, we proved that five-dimensional non-standard Filiform Lie algebra is type ???? but not type ????+. It is still an open problem to classify types ???? and ????+ for the general case of non-standard Filiform Lie algebra of dimension ≥6.
Application of Single Index Model to Determine Optimal Stock Portfolio (A Case Study on IDX30 in 2022) Emmanuel Parulian Sirait; Kankan Parmikanti; Riaman Riaman
International Journal of Quantitative Research and Modeling Vol. 4 No. 3 (2023): 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.v4i3.493

Abstract

Stock represent proof of ownership or participation of an individual or entity in a company. Investors gain profits from shares through capital gains and dividends. The difficulty in selecting an optimal composition of a stock portfolio is a major concern for investors. This study aims to determine the optimal composition of a stock portfolio, calculate the expected returns in the future, and assess the potential risks that investors may encounter later on. The data for this research consists of stocks listed on the IDX30 Index throughout the year 2022, which consistently appear in every six-month evaluation. The analysis is conducted using a single-index model. Based on the findings of this study, the following ten stocks are identified as the optimal portfolio constituents: KLBF with a weight of 17.20%, BBRI with a weight of 17.18%, BBCA with a weight of 17.08%, PTBA with a weight of 12.46%, BBNI with a weight of 9.89%, UNVR with a weight of 8.33%, INKP with a weight of 8.66%, ICBP with a weight of 5.56%, BMRI with a weight of 3.25%, and UNTR with a weight of 0,39%. The expected return from the formed portfolio is 0,1% per day, with a corresponding risk of 0,004%.
Comparative Analysis of Normal Pension Benefits Using the Attained Age Normal Method and the Individual Level Premium Method Atha Hukama; Kankan Parmikanti; Riaman Riaman
International Journal of Quantitative Research and Modeling Vol. 6 No. 2 (2025): 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.v6i2.946

Abstract

Pension programs are among the most important forms of employee compensation, offering financial security after retirement. This study aims to calculate the company’s initial payroll contributions to determine regular contributions, actuarial liabilities, and pension benefits using two actuarial projection methods: the Attained Age Normal (AAN) and Individual Level Premium (ILP) methods. The analysis is based on employee data from Puskesmas Binjai Estate, including age, salary, and years of service. It includes computations of pension benefits, normal costs, actuarial liabilities, and net benefits received by employees under each method. The results reveal that the length of service significantly affects both the value of contributions and the actuarial liabilities. Employees with longer service periods result in higher contribution requirements and greater liabilities. Moreover, the Attained Age Normal method produces higher pension benefits compared to the Individual Level Premium method for long-serving employees. However, both methods present financial challenges for employers, as they require higher contributions relative to the benefits promised. Consequently, companies must allocate substantial funding to meet their pension obligations. This study provides a comparative perspective that can assist decision-makers in selecting an actuarial method that balances benefit adequacy and financial sustainability.
BI Rate Forecasting Using the Fuzzy Time Series Method with Percentage Change as the Universe of Discourse Nadhira Shafa Felisya; Kankan Parmikanti; Sukono
International Journal of Business, Economics, and Social Development Vol. 7 No. 2 (2026): International Journal of Business, Economics, and Social Development (IJBESD)
Publisher : Rescollacom (Research Collaborations Community)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijbesd.v7i2.1169

Abstract

BI Rate is a policy interest rate that reflects the direction of Bank Indonesia’s monetary policy and has a significant impact on financial sector stability and overall economic conditions. The fluctuating movement of BI Rate necessitates the use of forecasting methods capable of accurately capturing data patterns. This study aims to forecast BI Rate using the Fuzzy Time Series method with percentage change as the universe of discourse. BI Rate data from January 2009 to September 2025 are used as historical data in the forecasting process. The research stages include transforming the data into percentage change form, constructing the universe of discourse, determining main intervals and sub-intervals, performing fuzzification, establishing fuzzy logic relationships, and conducting defuzzification to obtain forecasting results. The forecasting process forms 9 main intervals and 13 sub-intervals. The forecasting accuracy is evaluated using the Mean Absolute Percentage Error (MAPE), resulting in a value of 1.56%, indicating that the Fuzzy Time Series method with the percentage change approach performs well in forecasting BI Rate and is suitable as an alternative method for policy interest rate forecasting.
SEPUTAR ALJABAR ENVELOPING UNIVERSAL DARI ALJABAR LIE FROBENIUS BERDIMENSI 4 Edi Kurniadi; Badrulfalah Badrulfalah; Kankan Parmikanti
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 18, No 2 (2024)
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/epsilon.v18i2.13798

Abstract

Setiap aljabar Lie mempunyai aljabar enveloping universal dan bersifat tunggal. Dalam penelitian ini, dipelajari aljabar enveloping universal dari suatu aljabar Lie Frobenius berdimensi 4. Tujuannya adalah untuk membuktikan bahwa aljabar enveloping universal dari suatu aljabar Lie Frobenius berdimensi 4 bersifat primitif. Pertama-tama, dikonstruksi suatu basis untuk aljabar enveloping universal menggunakan Teorema Poincare-Birkhoff-Witt untuk menentukan secara eksplisit aljabar enveloping universalnya dan langkah kedua, menentukan karakteristik aljabar enveloping universal hasil konstruksi. Hasil dalam penelitian ini menunjukkan bahwa setiap aljabar enveloping universal dari aljabar Lie Frobenius berdimensi 4 senantiasa bersifat primitif.