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Classification of Money Market Mutual Fund Products in Indonesia By Using Mahalanobis Distance and Manhattan Distance Indrawan; Azka, Muhammad; Kamila, Isti; Rauf, Nurul Maqfirah; Santoso, Eka Krisna
Journal of Mathematics, Computations and Statistics Vol. 8 No. 1 (2025): Volume 08 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i1.6143

This study aims to classify money market fund products listed and supervised by the Financial Services Authority (OJK) with minimal classification error. Mahalanobis distance and Manhattan distance were employed to classify these products. Data was sourced from the Indo Premier Online Technology (IPOT) application. Variables utilized in this research include percentage return, Sharpe ratio, unit growth, and Asset Under Management (AUM) . Additionally, Principal Component Analysis (PCA) was employed to reduce data dimensionality by linearly combining correlated original variables into new variables (principal components). PCA was used to visualize data with more than three dimensions. Based on the principal component analysis, the first two principal components captured 74.43% of the original data information, while the first three principal components captured 98.94%. Classification results using three principal components and standardized data showed the same error rates: 13.33% for Mahalanobis distance and 6.67% for Manhattan distance. For the two principal components, both Mahalanobis and Manhattan distances resulted in an error rate of 13.33%. Therefore, Manhattan distance is the most effective method for classification. Forecasting results indicate that mutual fund A is a good investment choice, while mutual fund B is a poor one. Keywords: Mahalanobis distance; Manhattan distance; Principal Component Analysis

Analisis Penyebaran COVID-19 di Sulawesi Selatan Menggunakan Machine Learning (Regression Models) Bahar, Nur Qadri; Rauf, Nurul Maqfirah
Equiva Journal Vol 2 No 2 (2024):
Publisher : Jurusan Matematika dan Teknologi Informasi

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COVID-19 merupakan bencana yang sangat mengganggu manusia secara global abad ini. Berbagai macam dampak buruk diakibatkan oleh pandemi COVID-19, mulai dari dampak sosial, ekonomi, psikologi dan ekonomi. Dunia telah banyak belajar dari pandemi COVID-19, termasuk bagaimana mengatasi dan mengurangi dampak buruk akibat COVID-19 dengan berbagai macam ilmu dan perangkat, termasuk menggunakan machine learning dalam menganalisis bencana dan dampaknya. Machine learning menggunakan berbagai teknik dalam penerapannya, salah satunya adalah regresi yang mampu memberikan solusi bagi banyak permasalahan, termasuk menganilis penyebaran COVID-19. Dengan framework yang dimiliki oleh bahasa pemrograman python, machine learning mampu menganalisis dan memberikan insight yang tersembunyi dari dataset yang dikoleksi oleh Dinas Kesehatan Provinsi Sulawesi Selatan. Dalam penelitian ini, dilakukan analisis penyebaran COVID-19 menggunakan model regresi linear biasa, regresi ridge, dan regresi LASSO. Model regresi ridge mampu menjelaskan variabilitas dataset (variabel target) dengan tingkat yang paling baik dengan . Namun dari ketiga model yang dibangun, semuanya memiliki performa yang kurang, dengan MAPE yang sangat tinggi. Model regresi biasa memiliki MAPE sebesar 2.5722572116 pada training dan 3.0803084681 pada testing. Model regresi ridge memiliki MAPE sebesar pada training dan . Model regresi LASSO memiliki MAPE sebesar pada training dan pada testing. Dengan MAPE yang tinggi pada training dan testing, artinya semua model terindikasi underfitting, sehingga perlu ditindaklanjuti dengan membangun model yang lebih kompleks.

Stability Analysis of a Time-Delayed Disease Transmission Model in Prey–Predator Populations Incorporating a Holling Type II Functional Response Rauf, Nurul Maqfirah; Sianturi, Paian; Jaharuddin, Jaharuddin
Journal of Mathematics, Computations and Statistics Vol. 8 No. 1 (2025): Volume 08 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i1.7428

Abstrak. This article presents a comprehensive study of a mathematical model describing the spread of infectious disease within a prey–predator population, incorporating the Holling type II functional response and a delay parameter, denoted as τ, representing the incubation or infection period. The model captures the interactions among four population groups: susceptible prey, infected prey, susceptible predators, and infected predators. Through analytical investigation, six fixed points (equilibrium points) of the system were identified. The stability of these fixed points was examined using the eigenvalues of the Jacobian matrix, and one locally stable fixed point was found, while the others were identified as saddle points or unstable. To gain deeper insights into the model’s behavior over time, numerical simulations were conducted for different values of the delay parameter . The results indicate that the presence of a time delay significantly affects the dynamics of all four population groups. Specifically, the infection delay can suppress or slow the spread of the disease by delaying the transition from susceptible to infected classes. Oscillatory behavior emerged in certain population groups when the delay was introduced, especially among infected prey and predators, before gradually stabilizing toward the disease-endemic equilibrium. These findings highlight the critical role of time delay in disease transmission dynamics in ecological systems and provide a framework for further research on delay-induced phenomena in epidemiological models. Keywords: Prey–Predator, Disease Spread, Delay Time, Functional Response, Stability Analysis.

Training on Strategies to Pass CPNS Test for CPNS Applicants Through the Giat Belajar Abadi Platform Santoso, Eka Krisna; Azka, Muhammad; Kamila, Isti; Indrawan; Rauf, Nurul Maqfirah; Bahar, Nur Qadri
Jurnal Pengabdian Masyarakat Inovatif Vol. 2 No. 2 (2024): JPMI (Jurnal Pengabdian Masyarakat Inovatif)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Pakuan

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

The acceptance of Civil Servant Candidates (CPNS) is an opportunity highly anticipated by the community to build a career in the government sector. However, tight competition and complex selection stages are often the main challenges for applicants. Many applicants fail due to a lack of understanding of the selection process, ineffective learning strategies, and minimal information about the success criteria. The partner of this Community Service activity is Giat Belajar Abadi. Giat Belajar Abadi (GBA) is a lifelong learning platform designed to help people improve their skills and expand their knowledge. This platform offers a variety of classes and learning programs related to business, self-development, and more. However, Giat Belajar Abadi has not yet opened a class for training strategies to pass the Civil Servant Candidate (CPNS) test. Therefore, a community service program is needed for Giat Belajar Abadi partners by opening a training class on CPNS test strategies. This class will help CPNS applicants to be better prepared for the selection, both technically and mentally, increasing their chances of success. The purpose of this Community Service activity is to increase understanding of CPNS selection strategies through Giat Belajar Abadi partners. Therefore, the target audience of this activity is CPNS applicants. The outcome of this Community Service program is an increased understanding of CPNS selection strategies. Through this program, it is hoped that the success rate of participants in the CPNS selection will increase, while creating more competent human resources ready to contribute to the government sector. This program also has a long-term impact on improving the quality of CPNS applicants’ preparation in the future.

Training on Strategies to Pass CPNS Test for CPNS Applicants Through the Giat Belajar Abadi Platform Santoso, Eka Krisna; Azka, Muhammad; Kamila, Isti; Indrawan; Rauf, Nurul Maqfirah; Bahar, Nur Qadri
Jurnal Pengabdian Masyarakat Inovatif Vol. 2 No. 2 (2024): JPMI (Jurnal Pengabdian Masyarakat Inovatif)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Pakuan

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

The acceptance of Civil Servant Candidates (CPNS) is an opportunity highly anticipated by the community to build a career in the government sector. However, tight competition and complex selection stages are often the main challenges for applicants. Many applicants fail due to a lack of understanding of the selection process, ineffective learning strategies, and minimal information about the success criteria. The partner of this Community Service activity is Giat Belajar Abadi. Giat Belajar Abadi (GBA) is a lifelong learning platform designed to help people improve their skills and expand their knowledge. This platform offers a variety of classes and learning programs related to business, self-development, and more. However, Giat Belajar Abadi has not yet opened a class for training strategies to pass the Civil Servant Candidate (CPNS) test. Therefore, a community service program is needed for Giat Belajar Abadi partners by opening a training class on CPNS test strategies. This class will help CPNS applicants to be better prepared for the selection, both technically and mentally, increasing their chances of success. The purpose of this Community Service activity is to increase understanding of CPNS selection strategies through Giat Belajar Abadi partners. Therefore, the target audience of this activity is CPNS applicants. The outcome of this Community Service program is an increased understanding of CPNS selection strategies. Through this program, it is hoped that the success rate of participants in the CPNS selection will increase, while creating more competent human resources ready to contribute to the government sector. This program also has a long-term impact on improving the quality of CPNS applicants’ preparation in the future.

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