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All Journal Epsilon: Jurnal Matematika Murni dan Terapan Kubik Journal of Natural Sciences and Mathematics Research Jurnal Fourier Edumatsains Desimal: Jurnal Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Jambura Journal of Mathematics Eksakta : Berkala Ilmiah Bidang MIPA Jurnal Matematika UNAND JURNAL PENDIDIKAN MIPA Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Jurnal Statistika dan Aplikasinya KUBIK: Jurnal Publikasi Ilmiah Matematika Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi International Journal of Business, Economics, and Social Development International Journal of Global Operations Research International Journal of Quantitative Research and Modeling Fraction: Jurnal Teori dan Terapan Matematika Industrial Research Workshop and National Seminar SisInfo : Jurnal Sistem Informasi dan Informatika Jurnal Matematika Integratif In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism)
Kankan Parmikanti
Departemen Matematika, Fakultas MIPA, Universitas Padjadjaran
Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Mathematical Model of Paddy Production using Cobb Douglas Method Based On Weather Factors Riaman, Riaman; Parmikanti, Kankan; Subartiny, Betty; Supian, Sudradjat
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 7, No 4 (2023): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v7i4.15446

Abstract

This research was conducted to model paddy production based on weather factors. This needs to be done to predict crop yields and regulate paddy cropping patterns. In setting the cropping pattern, the weather is selected which consists of temperature, wind speed, and rainfall, as a variable factor of production. Meanwhile, other factors (such as fertilization, sunshine, air humidity, etc.) are assumed to be in catteries paribus conditions. The research method used is a mixed method between qualitative methods which are descriptive details and quantitative methods which are based on weather data and Paddy's harvest data. The aim of this research is to analyze the influence of weather on paddy production results. Analysis is done to get the production function. Parameters are estimated using the Ordinary Least Square (OLS) method by minimizing the sum of squared errors. Based on data analysis, a correlation of 0.899 was obtained with a standard error of .051665515. the results of model testing also show significant results with the F statistic obtained at 33.98 with a p-value of 0.028 which is less than 5%. So it can be concluded that there is a significant relationship between weather and paddy productivity. In such a way that the weather can be used as a reference in determining the prediction of loss risk and paddy production. This model can also be recommended for further research, namely to determine insurance losses that may arise when extreme weather events occur. 
Penerapan Model Seasonal Autoregressive Integrated Moving Average (SARIMA) dalam Peramalan Curah Hujan di Kabupaten Bandung Barat nadhira, valda azka; Ruchjana, Budi Nurani; Parmikanti, Kankan
KUBIK Vol 10 No 1 (2025): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Department of Mathematics, Faculty of Science and Technology, UIN Sunan Gunung Djati Bandung

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Abstract

The expansion of the Kabupaten Bandung, namely Kabupaten Bandung Barat (KBB) is located in hilly and lowland areas. Rainfall in Kabupaten Bandung Barat has an impact on the productivity and performance of key sectors, such as agriculture, plantations and tourism. Low rainfall can lead prolonged dry seasons and result in drought. Conversely, extreme rainfall can also have negative impacts, such as causing soil erosion and potentially affecting the appeal and smooth operation of tourist destinations. Therefore, rainfall forecasting is needed in making appropriate policies, especially regarding the impacts of rainfall changes in KBB. The Seasonal Autoregressive Integrated Moving Average (SARIMA) method is applied in this study to forecast rainfall in KBB. The aims of this research are to estimate the parameters of the SARIMA model using the Maximum Likelihood Estimation (MLE) method and to apply the SARIMA method in forecasting rainfall in KBB, particularly during the December-January-February (DJF) period. The results of the analysis show that the SARIMA model can be applied to forecast rainfall in KBB. The best SARIMA model obtained ARIMA(2,1,0)(0,0,1)3 with a MAPE value 17,80%, which indicates an accurate forecasting criterion. Keywords: SARIMA, MLE, Rainfall.
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

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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 Felisya, Nadhira Shafa; Parmikanti, Kankan; 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.
Co-Authors Agus Supriatna Atha Hukama Atika Tresna Arianto Atje Setiawan Abdullah Badrulfalah Badrulfalah Bambang Ruswandi Bambang Suhandi Betty Subartini Budi Nurani Ruchjana Dhea Amelia DHEA ARIESTA Dhea Urfina Zulkifli Diah Ayu Pratiwi Diah Chaerani Diansyah D. Darmawan Dwi Susanti Edi Kurniadi Edi Kurniadi Ema Carnia Emmanuel Parulian Sirait Endang Rusyaman Fadhilah, Dila Nur Fauzi Akhmad Felisya, Nadhira Shafa Firdaniza Firdaniza Hukama, Atha Iin Irianingsih Jaka Nazarudin Kartika Dewi Khafsah Joebaedi Luthfi Ghiffari Moisino, Misel Lindi Monika, Putri Nabila Putri nadhira, valda azka Nendi Suhendi Syafei Nurul Gusriani Pratiwi, Putri Nisa Queency, Aurillya Rafi', Muhammad Thufeil Rahmayanti Putri Desiresta Reffa Ayu Anggraeni Reffa Ayu Anggraeni Riaman Riaman Riaman Soraya, Arthamevia Najwa Subartiny, Betty Sukono Supian, Sudradjat Sussy Susanti Sya’imaa.HS, Audrey Ariij Syifana, Hani Tiara Aprilia K Tiara Aprilia K, Tiara Wahyu, Azkanul Zahra, Nabila