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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.