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All Journal Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) Mathvision : Jurnal Matematika EIGEN MATHEMATICS JOURNAL Journal of Mathematics: Theory and Applications Jurnal Siger Matematika Al-Aqlu : Jurnal Matematika, Teknik dan Sains Papanda Journal of Mathematics and Sciences Research Parameter: Jurnal Matematika, Statistika dan Terapannya
Anugrawati, Sri Dewi
Universitas Islam Negeri Alaudddin Makassar
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Mathematics Medicine & Pharmacology

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Stock Portfolio Optimization Using Single Index Model (SIM) with Exponentially Weighted Moving Average (EWMA) Approach Mutmainna, Ainul; Nurwahidah, Nurwahidah; Anugrawati, Sri Dewi
Eigen Mathematics Journal Vol 7 No 2 (2024): December
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v7i2.247

Abstract

The optimal portfolio is a combination of various assets with the aim of reducing investment risk through diversification. This study aims to conduct stock selection using K-Means Clustering and the formation of an optimal stock portfolio from the application of Single Index Model the amount of investment risk in the portfolio using the Exponentially Weighted Moving Average approach, and the amount of portfolio performance. The analysis results show that there are 5 portfolios formed. The best portfolio that can be chosen by investors depends on the investor's risk tolerance. Investors with low risk tolerance can choose Portfolio 3 consisting of ICBP and MIKA stocks with an expected return of 0.01343 and a risk of 0.00714 and a VaR of IDR 2,633,286.63. Investors with moderate risk tolerance can choose Portfolio 1 which consists of ICBP, MIKA, ACES, INCO, ITMG, MAPI, TPIA, AKRA, and MDKA stocks with an expected return of 0.022047, risk of 0.01277 and VaR of IDR 3,083,287.87. Investors with high risk tolerance can choose Portfolio 2 which consists of MIKA, TPIA, and MDKA stocks with an expected return of 0.02504 and a risk of 0.01471 and a VaR of IDR 3,553,167.10.
Application of Extreme Value Distribution on Temperature Data in South Sulawesi Province Sri Dewi Anugrawati
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 13 No 1 (2025): VOLUME 13 NO 1 TAHUN 2025
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v13i1.60223

Abstract

Climate change in recent years has resulted in extreme changes in temperature in Indonesia, especially in South Sulawesi Province. Extreme temperature changes will affect human and investment activities, energy use, and disaster events. Therefore, this study aims to model the maximum and minimum temperature data in South Sulawesi Province for the last 75 years. The data used came from observations of maximum and minimum temperatures from January 1945 to December 2020 and were analyzed using the Generalized Extrem Value distribution with the maxima block approach and the Generalized Pareto Distribution with the Peak Overtreshold (POT) approach. The results of the analysis show that these two models can be used to model extreme minimum and maximum temperature data in South Sulawesi Province with the right and optimal selection of blocks and thresholds. The results of the calculation of the return level every 5 years in the projection of the next 50 years show an increase in maximum and minimum temperatures which suggests the need to mitigate the risk of temperature change in order to adapt to climate change.
Metode Interpolasi Linear dalam Analisis Suku Bunga Kredit Berdasarkan Pembayaran Angsuran: Studi Kasus Pembiayaan Mobil New Agya 1.2 E M/T Abidin, Nurwahidah; Sri Dewi Anugrawati; Asriani Hasan
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 12 No 2 (2024): VOLUME 12 NO 2 TAHUN 2024
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v12i2.53985

Abstract

An interest rate is the price or amount of additional payment paid by the borrower to the lender. The interest rate is usually not shown in the loan instalment brochure. This study aims to analyse the effective interest rate of vehicle financing loans. The method used to determine the effective interest rate in this study is linear interpolation. The calculated interest rates are flat interest rates and effective interest rates. Determining the most profitable car financing alternative for customers can be seen from the lowest interest rate. This study analyses the case of New Agya 1.2 E M/T car price through Kalla Toyota Palopo branch and credit through Mandiri Utama Finance at the end of 2023. Based on the results of data processing using the linear interpolation method, it is found that the higher the instalment payment and the smaller the tenor offered, the lower the interest rate.
PENERAPAN METODE RUNGE KUTTA FEHLBERG PADA PERSAMAAN LOGISTIK DALAM MEMPREDIKSI PERTUMBUHAN PENDUDUK DI SULBAR: Application Of The Runge Kutta Fehlberg Method In Logistic Equations in Predicting Population Growth in Sulbar Syarfiah, Syarfiah; Irwan, Muh.; Anugrawati, Sri Dewi
Al-Aqlu: Jurnal Matematika, Teknik dan Sains Vol. 2 No. 2 (2024): Juli 2024
Publisher : Yayasan Al-Amin Qalbu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59896/aqlu.v2i2.99

Abstract

This research discusses the application of the Runge Kutta Fehlberg method in predicting population growth in West Sulawesi through the logistic equation. Employing applied research methodology, the study seeks to forecast future population trends in the West Sulawesi province. Utilizing a step size of h = 0.01 and a growth rate of m = 0.0198, the Runge-Kutta Fehlberg method (RKF 45) was applied, starting from an initial population value  of   P (t0) = 1.419.229 individuals, resulting in a projected population of P (t10) = 1.506.142 individuals. These findings demonstrate the applicability of the Runge-Kutta Fehlberg (RKF 45) method in predicting population dynamics in West Sulawesi Province.
Implementasi regresi binomial negatif dalam mengatasi overdispersi pada analisis determinan jumlah pengangguran di pulau Sulawesi tahun 2023 Erna; Ermawati; Wahidah Alwi; Sri Dewi Anugrawati
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 13 No 2 (2025): VOLUME 13 NO 2, 2025
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v13i2.61738

Abstract

This study focuses on the implementation of negative binomial regression as a solution to overcome the problem of overdispersion in the analysis of determinants of unemployment on the island of Sulawesi in 2023. Unemployment is not only viewed as a statistical phenomenon or economic issue, but also as an important indicator that reflects social welfare and the success of development in a region. Sulawesi Island, with its growth in the agricultural and industrial sectors, faces serious challenges in reducing unemployment rates, which have the potential to cause regional disparities if not addressed appropriately. This study aims to develop an appropriate negative binomial regression model to overcome overdispersion and identify the main factors that influence the unemployment rate. The method used is negative binomial regression analysis of district/city unemployment data in Sulawesi Island, which is discrete and shows symptoms of overdispersion. With significant variables including population size, Human Development Index (HDI), and the number of job placement or fulfillment services. These three factors have been proven to have a significant effect on the number of unemployed people in Sulawesi Island in 2023.
Autoregressive Distributed Lag (ARDL) Method for Estimating Poverty Levels in Polewali Mandar Regency Abeng, Andi Tenri; Alwi, Wahidah; Sauddin, Adnan; Anugrawati, Sri Dewi; Aeni, Nur
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 13 No 2 (2025): VOLUME 13 NO 2, 2025
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v13i2.60197

Abstract

Polewali Mandar Regency is the region with the highest poverty rate in West Sulawesi. According to a publication by the Central Bureau of Statistics in March 2022, the percentage of the poor population was 11.75%, an increase compared to March 2021. The forecasting method used in this study is the Autoregressive Distributed Lag (ARDL) method. This study aims to determine the Autoregressive Distributed Lag (ARDL) model, which is then used to forecast the number of poor people in Polewali Mandar Regency. The results of the study using the ARDL method yielded the best estimation model, namely ARDL (3, 3, 2, 2). The forecast results for the percentage of the poor population using the ARDL (3, 3, 2, 2) model for the following semesters are 21.79%, 10.15%, and 16.52%, respectively. The forecasting accuracy test using the Mean Absolute Percentage Error (MAPE) yielded a value of 12.18%, indicating that the ARDL model produced in this study is suitable for forecasting the percentage of the poor population in Polewali Mandar Regency.
Comparison of Random Forest and XGBoost Methods for Predicting Work Accident Claim Reserves Anugrah, Sri Ayu; Anugrawati, Sri Dewi; Sauddin, Adnan; Mariani, Andi
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 4 No 3 (2025): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv4i3pp497-508

Abstract

The potential high claim burden in the work accident insurance sector managed by BPJS Ketenagakerjaan have an impact on the company’s financial stability. This encourages insurance companies to provide additional funds to maintain the company’s operational sustainability. Thus, preparing future fund reserves is a crucial step in risk and financial management to minimize payment delays, up to the risk of default. This study aims to determine the best method for predicting work accident claim reserves by comparing the Random Forest and XGBoost methods. The result of the analysis shows that the XGBoost method has an outstanding ability to predict work accident claim reserves on BPJS Ketenagakerjaan in the period July 2016 to August 2023, with a MAPE of 5.14% and an accuracy rate of 94.86%.
Model penentuan biaya long-term care dengan menggunakan anuitas joint life Nurul Anisha Dahlan; Sri Dewi Anugrawati; Wahyuni Abidin
Papanda Journal of Mathematics and Science Research Vol. 5 No. 1 (2026): Volume 5 Nomor 1 Maret 2026
Publisher : Papanda Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56916/pjmsr.v5i1.2925

Abstract

The increasing life expectancy in Indonesia has led to a growing elderly population, thereby intensifying the demand for financial protection against Long-Term Care (LTC) risks. This study aims to calculate the Actuarial Present Value (APV) of Long-Term Care (LTC) benefits for married couples using an actuarial model based on a multistate Markov framework. The model incorporates 15 possible health status transitions between the couple, covering combinations of healthy, ill, and deceased states without distinguishing between husband and wife. Transition probabilities are derived from the Indonesian Mortality Table IV (TMI IV) and the National Morbidity Table. These probabilities are then used to estimate the present value of LTC costs under assumptions of basic benefits, increased benefits when one or both spouses are ill, and a fixed interest rate of 6%. Simulation results show that the total present value of LTC benefits over a 20-year contract period amounts to IDR 96,537,664.69. This model demonstrates both flexibility and accuracy in estimating future care needs and the benefits received. The findings provide valuable insight for the design of spouse-based life insurance products in Indonesia
Penentuan Cadangan Asuransi Jiwa Last Survivor berdasarkan Metode Gross Premium Valuation (GPV) dengan Hukum De’Moivre Jefri, Rhanny Kirana; Anugrawati, Sri Dewi; Nurwahidah, Nurwahidah
Eigen Mathematics Journal Vol 9 No 1 (2026): June
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v9i1.326

Abstract

Insurance is one of the measures that can be used to prepare for various risks that can occur at any time. In the context of life insurance products, multiple life insurance is an efficient option because it is more economical than purchasing separate policies for two people with equivalent benefits. Unlike previous studies that focused on single life models using the GPV (Gross Premium Valuation) approach, this study develops an analysis of more complex multiple life insurance products, thereby providing a more representative picture of premium reserves for cases involving two insured parties. This study aims to formulate a mathematical model and conclude the results of prospective premium reserve calculations for last survivor whole life insurance using the GPV (Gross Premium Valuation) approach and De'Moivre's law De’Moivre This study uses a quantitative method with a documentation data collection technique, namely the 2019 Mortality Table IV data published by the Indonesian Life Insurance Association (AAJI). The results of this study show that the mathematical model of premium reserves for last survivor whole life insurance using the GPV (Gross Premium Valuation) approach and De'Moivre's law is ${_t}V^{GPV} = BA_{\bar{xy}} + U + PAG_{\bar{xy}} + A{\ddot{a}}_{\bar{xy}} + CA_{\bar{xy}} - G_{\bar{xy}}{\ddot{a}}_{\bar{xy}}$. However, when the insured ($y$) dies first, the mathematical model is ${_t}V^{GPV} = BA_{\bar{x}} + U + PAG_{\bar{xy}} + A{\ddot{a}}_{\bar{x}} + CA_{\bar{x}} - G_{\bar{xy}}{\ddot{a}}_{\bar{x}}$ while if the insured ($x$) dies first, the mathematical model is ${_t}V^{GPV} = BA_{\bar{y}} + U + PAG_{\bar{xy}} + A{\ddot{a}}_{\bar{y}} + CA_{\bar{y}} - G_{\bar{xy}}{\ddot{a}}_{\bar{y}}$. In addition, the results of the study show that there is a difference in the last survivor life insurance premium reserve between the conditions when both insured persons are still alive and when one of them dies, and that the use of De'Moivre's law results in a decreasing reserve pattern but ends up exceeding the promised benefits due to linear mortality assumptions so that the present value of the benefits does not fully decrease at the end of the coverage period. These findings indicate that the use of a uniform death distribution needs to be considered in order to produce more realistic premium reserves.
Co-Authors Abeng, Andi Tenri Adnan Sauddin Alwi, Wahidah ida Andi Mariani Anugrah, Sri Ayu Asriani Hasan Ermawati Ermawati Erna Fitrah Irwan Kasse Irwan, Muh. Ismawati Ismawati Iyut Wahyu Saputri Jefri, Rhanny Kirana Jusman Usman M Arlan Darmawan Muhammad Ihsan Salim Mutmainna, Ainul Nur Aeni Nurfadilah, Khalilah Nurhikma Nurul Anisha Dahlan NURWAHIDAH NURWAHIDAH Nurwahidah Nurwahidah Rahma Sri Susanti Sainal Abidin Enal Susanti, Rahma Sri Syarfiah, Syarfiah Wahidah Alwi Wahidah Alwi Wahyuni Abidin Yusrianto