cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota makassar,
Sulawesi selatan
INDONESIA
JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI
Published by Universitas Hasanuddin
ISSN : 18581382     EISSN : 26148811     DOI : -
Core Subject : Education,
Mathematics
Jurnal ini mempublikasikan paper-paper original hasil-hasil penelitian dibidang Matematika, Statistika dan Komputasi Matematika.
Arjuna Subject : -
Articles 496 Documents
 43   44   45   46   47 
Pengelompokan Kecamatan di Provinsi Bali Berdasarkan Indeks Desa Membangun (IDM) Tahun 2022 dengan Analisis Diskriminan Azzah Nazhifa Wina Ramadhani; Aulia Ramadhanti; Aini Divayanti Arrofah; M. Nabil Saputra; Dita Amelia; M. Fariz Fadillah Mardianto; Elly Ana
Jurnal Matematika, Statistika dan Komputasi Vol. 20 No. 3 (2024): May 2024
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v20i3.32662

Abstract

One of the key achievements in national development is the success in building villages as the smallest administrative units because that is starting point for the development of an economy within the community. Therefore, it is crucial for the government to conduct mapping for development to enhance the quality of the population and the respective regions. The purpose of this research is to categorize several districts in Province of Bali into specific statues based on Village Development Index using discriminant analysis method. The result of this research indicates a high classification rate of 92.857% for the discriminant model formed. This suggests that almost all districts in both categories have been classified into groups that align with the original data.  
Estimasi Selang Dana Tabarru’ Pada Asuransi Jiwa Syariah dengan Menggunakan Perhitungan Cost of Insurance Vito Cahyadi; Nurul Azizah; Achmad Zanbar Soleh
Jurnal Matematika, Statistika dan Komputasi Vol. 20 No. 3 (2024): May 2024
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v20i3.32822

Abstract

Contributions is an amount of funds paid by the insured at the beginning of the period of a sharia life insurance contract. Contribution also constitutes the sum of net contributions with expenses. Net contributions are further categorized as Tabarru' funds obtained based on the Cost of Insurance (COI) method. This research incorporates the influence of interest rate in estimating Tabarru' funds. Assuming a Normal Distribution of interest rate and the Central Limit Theorem for a confidence level, a confidence interval is obtained from the interest rate mean. The research findings indicate that the larger the management costs and the older the insurance participants, the greater the COI value will be. Furthermore, the larger the interest rate value, the smaller the COI value. Consequently, as the interest rate value increases, the Tabarru' funds will decrease, while the management costs increase and the age of the insurance participants rises, the Tabarru’ funds will increase.
Integer Linear Programming In Production Profit Optimization Problems Using Branch And Bound Methods & Gomory Cutting Plane Nurweni putri; Maya Sari Syahrul; Rosi Ramayanti
Jurnal Matematika, Statistika dan Komputasi Vol. 20 No. 3 (2024): May 2024
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v20i3.32888

Abstract

Integer Linear Programming is a mathematical model that allows the results of solving cases in linear programming in the form of integers. Methods to solve Integer Programming problems include the Branch and Bound Method and the Gomory Cutting Plane Method. Both of these methods have certain rules for adding new constraint functions until an optimal solution to an integer is obtained. The purpose of this study is to optimize the profits of the production of UMKM Capal Classic Shoes Kab. Agam  by using the Branch and Bound method and the Gomory Cutting Plane method and analyzing the comparison of optimal results resulting from the two methods. The data used in the study are data on raw materials for making classic sandals and profit data. The results obtained by these two methods produce the same maximum profit, namely RP. 664,000 with each producing 15 pairs of men's sandals and 13 pairs of women's sandals. But in its completion, the Branch and Bound method requires many iterations and a longer time compared to the Gumory Cutting plane method.
Performance Evaluation of Classification Methods on Big Data: Decision Trees, Naive Bayes, K-Nearest Neighbors, and Support Vector Machines Justin Eduardo Simarmata; Gerhard-Wilhelm Weber; Debora Chrisinta
Jurnal Matematika, Statistika dan Komputasi Vol. 20 No. 3 (2024): May 2024
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v20i3.32970

Abstract

Performance evaluation of classification methods on big data is becoming increasingly important in addressing the challenges of data analysis at scale. This study aims to conduct a comparative evaluation of the classification method, namely Decision Trees (DT), Naive Bayes (NB), k-Nearest Neighbors (KNN), and Support Vector Machines (SVM), in analysis on big data evaluated from data simulation and application of real data available in the Rstudio package, namely ISLR. The simulation data used consisted of 2 types of datasets generated based on predictor variables that were normally distributed with different averages and variants and response variables generated in classes adjusted to the characteristics of predictor variables with different proportions. Real data are taken from two types of numeric variables and predictor variables available in the package. The number of sample sizes to be evaluated in each method is n = 500, n = 1000 and n = 5000. In real data, sample division is done randomly to maintain data representativeness. At the evaluation stage, the performance of the method is measured using accuracy metrics. The results of the evaluation of the simulation of Dataset 1 show that the methods that have an influence on the quality of the classification produced if applied to Big Data are the DT and KNN methods. However, in Dataset 2 there is a change in the results of the DT method, because of the influence on the number of classes and the proportion of class distribution in the data. The results obtained from data simulation, proven by applying to real data by showing that similar methods provide a quality influence if applied to Big Data, while the NB and SVM methods do not show a consistent influence when applied to Big Data. The results of observations in this study show that the DT and KNN methods have several advantages that make them suitable for application to Big Data.
Perbandingan Metode Klasifikasi dalam Memprediksi Penjualan Produk Ban Terlaris moch anjas aprihartha; Fitri Astutik; Nani Sulistianingsih
Jurnal Matematika, Statistika dan Komputasi Vol. 20 No. 3 (2024): May 2024
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v20i3.33187

Abstract

Data mining is a term to describe the process of moving through large databases in search of certain previously unknown patterns. In finding certain patterns, you need a supporting technique, called machine learning. Machine learning involves learning hidden patterns in data and further using patterns to classify or predict an event related to a problem. One of the problems can be solved with machine learning such as predicting the sales rate of tire products. This can help companies predict tire products that are selling well in the market. In producing an accurate prediction model, it will be compared with decision tree classification methods of CART, CART + Discrete Adaboost, and Naive Bayes applied to tire sales data by PT. Mitra Mekar Mandiri. The results of the study based on successive model performance evaluations are model Naive Bayes < model CART < model CART+Discrete Adaboost. The Discrete Adaboost model with a data proportion of 90:10 is the best model for predicting tire sales. The accuracy, sensitivity and specificity values for the model were 79.17%; 89.47%; and 68.84%. The AUC value is 0.8 which indicates the model is good
Analisis Faktor-faktor Academic Hardiness yang Mempengaruhi Kelelahan Emosional Mahasiswa di Kota Malang Menggunakan Model Logit dan Probit Siti Nuradilla
Jurnal Matematika, Statistika dan Komputasi Vol. 20 No. 3 (2024): May 2024
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v20i3.33220

Abstract

The prevalence of emotional exhaustion as an indication of academic burnout among students during online learning is very high. Responding to the issues and neglect of studies on academic burnout, it is necessary to analyze the factors of academic hardiness among students in Malang City regarding emotional exhaustion. The ordinal probit regression model yields the best fit with 120 samples in analyzing the factors of academic hardiness on emotional exhaustion due to its smaller AIC value. Significant factors affecting emotional exhaustion are commitment to academic tasks (), control over struggle (), and control individual difficulties (). The ordinal probit regression model obtained is  and . The marginal effect states that for every one-unit change in the ratio  will increase students low emotional exhaustion by 0.016, and decrease students moderate emotional exhaustion by 0.044, and high emotional exhaustion by 0.060. Every one-unit change in the ratio  will decrease students low emotional exhaustion by 0.018, and increase students moderate emotional exhaustion by 0.049, and high emotional exhaustion by 0.067. Every one-unit change in the ratio  will increase students low emotional exhaustion by 0.025, and decrease students moderate emotional exhaustion by 0.070, and high emotional exhaustion by 0.095.
Implementasi Jump Diffusion Untuk Memprediksi Harga Saham Serta Analisis Risiko Menggunakan Value At Risk Dan Expected Shortfall (Studi Kasus: PT. Indofood Sukses Makmur Tbk) Feby Seru; Miftachul Jannah; Tiku Tandiangnga
Jurnal Matematika, Statistika dan Komputasi Vol. 20 No. 3 (2024): May 2024
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v20i3.33261

Abstract

Stock prices often fluctuate; therefore, a model is needed to predict the stock price. One of the models that can be used to predict stock prices when experiencing a jump is Jump Diffusion. In addition to predicting, investment is inseparable from the risks that may be borne, so it is also necessary to measure risk. This study aims to implement the Jump Diffusion Model in predicting the stock price of PT Indofood Sukses Makmur Tbk and conduct a risk analysis of the prediction results using Value at Risk (VaR) and Expected Shortfall (ES). In this study, a model was obtained that was used to predict the share price of PT Indofood Sukses Makmur Tbk with a Mean Absolute Percentage Error (MAPE) value of 6.41%. This shows that the accuracy of the stock price prediction results is included in the very good category. In addition, the VaR value of the prediction results with a confidence level of 90%, 95%, and 99% is 0.0292, 0.0372, and 0.0523, and the ES value is 0.0402, 0.0474, and 0.0613.
Penerapan Teori Permainan Dalam Menentukan Strategi Optimal Kemenangan Calon Presiden Dan Wakil Presiden Pada Ajang Pemilu 2024 M Fauzul; Ayes Malona Siboro; Putri Kurnia Chairunnisa; I Gede Adhitya Wisnu Wardhana; Baiq Rika Ayu Febrilia
Jurnal Matematika, Statistika dan Komputasi Vol. 20 No. 3 (2024): May 2024
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v20i3.33285

Abstract

Game theory is applied in the context of the 2024 general election to determine effective strategies for each pair of candidates (paslon) presidential and vice presidential in the competition. This research yields several significant findings. In the match between paslon 1 and paslon 2, paslon 2 successfully secured victory with a score of -18, employing an optimal strategy focused on (candidate experience). Conversely, paslon 1 emerged victorious against paslon 3 with a score of 20, utilizing an optimal strategy based on (candidate vision and mission). In the final match between paslon 2 and paslon 3, paslon 2 once again achieved victory with a score of 36.88889. The optimal strategy for paslon 2 includes (candidate character), (candidate vision and mission), and (candidate experience). Paslon 3 also adopts a similar strategy. The results of this research provide insights into the development of candidate campaign strategies in the political competition context using a game theory approach.
Penerapan K-Means Cluster untuk Pembentukan Portofolio Model Black-Litterman Fitri Amanah; Fauziah Roshafara; Puri Indah Lestari; Salwa Salsabila; Renita Maharani
Jurnal Matematika, Statistika dan Komputasi Vol. 20 No. 3 (2024): May 2024
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v20i3.34165

Abstract

A portfolio in finance is a collection of investment assets that aims to reduce risk by spreading investment across various assets. In building a portfolio, cluster analysis is used to select assets. K-Means cluster is often used because it is considered efficient for handling large data. In addition, the Black-Litterman Model is used because it can combine investor knowledge into asset allocation efficiently, so that the portfolio becomes more diverse, stable and adaptive to economic conditions, and reflects the investment manager's views. The research results show that k-means cluster analysis can be applied in forming the Black-Litterman model portfolio. Two clusters were obtained, namely cluster I consisting of ADRO, AKRA, BRMS, MIKA, TLKM, UNVR shares, and cluster II consisting of INDF, INKP, SMGR, UNTR. The two clusters were then formed into portfolios I and II. The calculation of expected return and portfolio risk shows that portfolio II produces profits (expected return portfolio) that are greater than portfolio I, namely 0.04445 or IDR 4.445.344,00, and the risk level of portfolio II is also smaller than portfolio I, namely 0.02104 or IDR 2.104.400,00
Implementation of Robust Optimization Model to Controlling the Inventory Costs of Consumable Medical Equipment at Malahayati Islamic Hospital Linna Syahputri; Hendra Cipta
Jurnal Matematika, Statistika dan Komputasi Vol. 20 No. 3 (2024): May 2024
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v20i3.34284

Abstract

Inventory management is critical to hospitals capacity to meet patient requests. Because of the fluctuating patient volume, hospitals frequently have trouble managing their inventory of consumable medical equipment. An optimization model must therefore be used to control inventories. One hospital that calculates inventory costs using traditional methods is Malahayati Islamic Hospital. This leads to high inventory expenses and storage costs when acquiring medical supplies like three-count syringes. anything meant to lower the cost of inventories. An optimization model that can use linear programming techniques to discover the optimal solution even in situations when the data is unclear is referred to as strong optimization. By applying a strong optimization model, it shows that the results of calculating the inventory costs of consumable medical equipment at the Malahayati Islamic Hospital can save costs of 24.71% of the total inventory costs of the Malahayati Islamic Hospital.

Page 45 of 50 | Total Record : 496

 43   44   45   46   47 

Filter by Year

2005 2025


Reset
Filter By Issues
All Issue Vol. 21 No. 2 (2025): JANUARY 2025 Vol. 21 No. 1 (2024): SEPTEMBER 2024 Vol. 20 No. 3 (2024): May 2024 Vol. 20 No. 2 (2024): JANUARY 2024 Vol. 20 No. 1 (2023): SEPTEMBER, 2023 Vol. 19 No. 3 (2023): MAY, 2023 Vol. 19 No. 2 (2023): JANUARY 2023 Vol. 19 No. 1 (2022): SEPTEMBER, 2022 Vol. 18 No. 3 (2022): MAY, 2022 Vol. 18 No. 2 (2022): JANUARY 2022 Vol. 18 No. 1 (2021): September 2021 Vol. 17 No. 3 (2021): May, 2021 Vol. 17 No. 2 (2021): JANUARY 2021 Vol. 17 No. 1 (2020): JMSK, SEPTEMBER, 2020 Vol. 16 No. 3 (2020): JMSK, MAY, 2020 Vol. 16 No. 2 (2020): JMSK, JANUARY, 2020 Vol. 15 No. 2 (2019): JMSK Vol. 15, No. 2, January 2019 Vol. 16 No. 1 (2019): JMSK, July, 2019 Vol. 15 No. 1 (2018): July 2018 Vol. 14 No. 2 (2018): January 2018 Vol. 14 No. 1 (2017): July 2017 Vol. 13 No. 2 (2017): January 2017 Vol. 13 No. 1: July 2016 Vol. 12 No. 2: January 2016 Vol. 12 No. 1: July 2015 Vol. 11 No. 2: January 2015 Vol. 11 No. 1: July 2014 Vol. 10 No. 2: January 2014 Vol. 10 No. 1: July 2013 Vol. 9 No. 2: January 2013 Vol. 9 No. 1: July 2012 Vol. 8 No. 2: January 2012 Vol. 8 No. 1: July 2011 Vol. 7 No. 2: January 2011 Vol. 7 No. 1: July 2010 Vol. 6 No. 2: January 2010 Vol. 6 No. 1 (2009): July 2009 Vol. 5 No. 2: January 2009 Vol. 5 No. 1: July 2008 Vol. 4 No. 2: January 2008 Vol. 4 No. 1: July 2007 Vol. 3 No. 2: January 2007 Vol. 3 No. 1: July 2006 Vol. 2 No. 2: January 2006 Vol. 2 No. 1: July 2005 More Issue