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Annals of Mathematical Modeling
Published by Research and Social Study Institute
ISSN : -     EISSN : 27157822     DOI : https://doi.org/10.33292/amm
Core Subject : Science, Education,
Computer Science & IT Mathematics
Annals of Mathematical Modeling is a peer-reviewed open-access journal that publishes educational research articles in mathematics education. Every submitted manuscript will be reviewed by at least two peer-reviewers using the double-blind review method. This journal is published biannually
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 26 Documents
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Lung cancer classification based on support vector machine-recursive feature elimination and artificial bee colony Alhadi Bustamam; Zuherman Rustam; Selly A. A. K; Nyoman A. Wibawa; Devvi Sarwinda; Nadya Asanul Husna
Annals of Mathematical Modeling Vol. 3 No. 1 (2023)
Publisher : Research and Social Study Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33292/amm.v3i1.26

Abstract

Early detection of cancerous cells can increase survival rates for patients by more than 97%. Microarray data, used for cancer classification, are comp osed of many thousands of features and from tens to hundreds of instances. Handling these huge datasets is the most imp ortant challenge in data classification. Feature selection or reduction is therefore an essential task in data classification. We prop ose a cancer diagnostic to ol using a supp ort vector machine for classifier and feature selection. First, we use supp ort vector machine-recursive feature elimination to prefilter the genes. This was enhanced with the artificial b ee colony algorithm. We ran four simulations using Ontario and Michigan lung cancer datasets. This approach provides higher classification accuracy than those without feature selection, supp ort vector machine-recursive feature elimination, or the artificial b ee colony algorithm. The accuracy of a supp ort vector machine using a feature selection-based recursive feature elimination metho d combined with the artificial b ee colony algorithm reached 98% with 100 b est features for the Michigan lung cancer dataset and 97% with 70 b est features for the Ontario lung cancer dataset. SVM with RFE-ABC as the feature selection metho d gives us an accurate result to diagnose Lung cancer using microarray data.
Heat transfer of thin-film Casson hybrid nanofluid flow across an unsteady stretching sheet Nur Ilyana Kamis; Md Faisal Md Basir; Taufiq Khairi Ahmad; Lim Yeou Jiann
Annals of Mathematical Modeling Vol. 3 No. 1 (2023)
Publisher : Research and Social Study Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33292/amm.v3i1.27

Abstract

Hybrid nanoparticles copper and alumina effect on the heat transfer of thin-film blood flow toward an unsteady permeable stretching sheet is studied. The influence of suction is considered. The governing partial differential equations together with boundary conditions are reduced into the set of ordinary differential equations by implementing the similarity transformations. The Keller-box method is used to solve the momentum and heat equations. The characteristics of the blood flow and heat transfer under the effect of unsteadiness parameter, nanoparticles volume fraction, Casson parameter, and intensity of suction for different thin-film thickness are discussed. The numerical results of the velocity and temperature profiles are graphically displayed. The physical interest such as the local skin friction and Nusselt number are depicted in a tabular form.
Cluster analysis of type II Diabetes Mellitus Patients with the Fuzzy C-means method Simeftiany Indrilemta Lomo; Endang Darmawan; Sugiyarto
Annals of Mathematical Modeling Vol. 3 No. 1 (2023)
Publisher : Research and Social Study Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33292/amm.v3i1.28

Abstract

Cluster analysis has been widely used in the fields of mathematics and health sciences. This study aims to classify distance-based data which are divided into several clusters. Accurate prediction from the outcome or survival rate of diabetic patients can be the key for the stratification of prognosis and therapy. A retrospective study of 447 medical record data of type II diabetes mellitus patients aged 18 years old or above and were hospitalized in the PKU Muhammadiyah Gamping Hospital from 2015-2019. Clustering is using the PCA-Fuzzy C-Means method based on patients’ survival status, demographic characteristics, therapy, and blood glucose (BG) levels. Clustering evaluation by Davies Bouldin Index (DBI). Data analysis is using Jupyter Notebook programme. Cluster formation are first cluster consists of 171 members, second cluster consists of 9 members, third cluster consists of 267 members with DBI 2,2645. 401 patients (89,7%) were recorded as alive and 46 patients (10,3%) were recorded as dead. A total of 447 patients: 54,1% were male; 90,6% were ≥ 45 years old; 66,4% has comorbidities; 51,7% had BG level of more than 200 mg/dl, and 57,7% received combination insulin+oral antidiabetic therapy.
Research on Regional Economic development of Guangxi based on multiple statistic analysis Xin Jian; Weizhang Lai
Annals of Mathematical Modeling Vol. 3 No. 1 (2023)
Publisher : Research and Social Study Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33292/amm.v3i1.29

Abstract

Economic development is a prerequisite for social stability and development. However, the regional economic development in various regions of our country is unbalanced, especially in the western region. As one of the minority autonomous regions in western of my country, Guangxi Province is undoubtedly of great practical significance to study its regional economic development. In this context, this paper is based on 8 economic indicators and related economic data of 14 cities in Guangxi Province in 2018, and is based on the theory of dimensionality reduction methods and cluster analysis, using principal component analysis (PCA) and hierarchical clustering methods to assess the comprehensive level of Guangxi’s economic development. The result shows that most cities' economic development in Guangxi Province is great. However, there are signature differences in economic development between urban areas.
Parameter estimation of HFMD infection in Malaysia with SIR model Hanis Nasir; Fuaada Mohd Siam
Annals of Mathematical Modeling Vol. 3 No. 1 (2023)
Publisher : Research and Social Study Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33292/amm.v3i1.30

Abstract

Hand, foot and mouth disease (HFMD) is a mildly infectious disease that happens to children due to low body immunity against viruses. In this paper, a simple SIR model is employed to represent the dynamics of HFMD in Malaysia. A weekly reported data of HFMD infection from week-1 of 2017 to week-36 of 2018 is used in the mathematical analysis. The procedure of parameter estimation is implemented in order to identify the parameter of the SIR model that fits the model with the reported data. The fminsearchbnd routine is used to minimize the objective function, which is the sum of absolute error minimization. By the Chi-squared test, the estimated parameters are reasonable. Based on the average value of the basic reproduction number R0, HFMD infection will remain to exist in the population under the current condition. Overall, this finding may be useful for public health personnel to reduce disease infection risk by planning more effective prevention strategies.
The effect of time management, motivation, and independence on mathematics learning outcomes with a focus on mediation Hidayati, Siti Nur; Tusyanah, Tusyanah; Ismiyati, Ismiyati; Tasya, Azza Man
Annals of Mathematical Modeling Vol. 5 No. 1 (2025)
Publisher : Research and Social Study Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33292/amm.v5i1.36

Abstract

This research aims to determine the role of learning focus in mediating the effect of time management, learning motivation, and learning independence on mathematics learning outcomes. This study used a quantitative method with data collection through questionnaires and analyzed with SEM-PLS. The sampling technique was saturated sampling, where all 105 students of grade IX of Nafsa Zakiyyah Junior High School in the 2025/2026 academic year were respondents. The results showed that of the 10 (ten) hypotheses proposed, 5 (five) hypotheses were accepted and 5 (five) hypotheses were rejected. The results showed that time management had a positive but insignificant effect on mathematics learning outcomes, learning motivation had a positive and significant effect on mathematics learning outcomes, learning independence had a positive and significant effect on mathematics learning outcomes, learning focus had a positive and significant effect on mathematics learning outcomes, time management had a positive but insignificant effect on learning focus, learning motivation had a positive and significant effect on learning focus, learning independence had a positive but insignificant effect on learning focus. Then, time management mediated by learning focus has a positive but insignificant effect on mathematics learning outcomes, learning motivation mediated by learning focus has a positive and significant effect on mathematics learning outcomes, and learning independence mediated by learning focus has a positive but insignificant effect on mathematics learning outcomes.

Page 3 of 3 | Total Record : 26

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