Bulletin of Applied Mathematics and Mathematics Education
BAMME welcomes high-quality manuscripts resulted from a research project in the scope of applied mathematics and mathematics education, which includes, but is not limited to the following topics: Analysis and applied analysis, algebra and applied algebra, logic, geometry, differential equations, dynamical system, fuzzy system, etc. Graph theory, combinatorics, number theory, coding theory, cryptography, etc. Mathematical modeling in economics, physics, biology, medicine, engineering, control theory and automation, optimization, operational research, neural network, data science, machine learning, etc. Applied statistics and probability, finance mathematics, biostatistics, actuary, etc. RME-based mathematics education. Development studies in mathematics education. Mathematics Ability, includes the following abilities: reasoning, connection, communication, representation, and problem solving. Ethnomathematics, the results of research on the relationship between mathematics and culture practiced by members of cultural groups who share experiences and practices similar to mathematics that can be in a unique form. Application of ICT in mathematical learning and the design, development, and evaluation of the implementation or application of learning media.
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Optimization of feature selection on semi-supervised data
Wijayanti, Dian Eka;
Afriyani, Sintia;
Surono, Sugiyarto;
Dewi, Deshinta Arrova
Bulletin of Applied Mathematics and Mathematics Education Vol. 4 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan
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DOI: 10.12928/bamme.v4i1.11104
This research explores feature selection optimization in semi-supervised text data by utilizing the technique of dividing data into training and testing sets and implementing pseudo-labeling. Proportions of data division, namely 70:30, 80:20, and 90:10, were used as experiments, employing TF-IDF weighting and PSO feature selection. Pseudo-labeling was applied by assigning positive, negative, and neutral labels to the training data to enrich information in the classification model during the testing phase. The research results indicate that the linear SVM model achieved the highest accuracy with a 90:10 data division proportion with a value of 0.9051, followed by Random Forest, which had an accuracy of 0.9254. Although RBF SVM and Poly SVM yielded good results, KNN showed lower performance. These findings emphasize the importance of feature selection strategies and the use of pseudo-labeling to enhance the performance of classification models in semi-supervised text data, offering potential applications across various domains that rely on semi-supervised text analysis.
Developing problem-based learning student worksheet on matrix materials to improve students’ critical thinking skills
Khoirunisa, Zahro;
Nurnugroho, Burhanudin Arif
Bulletin of Applied Mathematics and Mathematics Education Vol. 4 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan
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DOI: 10.12928/bamme.v4i2.11298
This research was conducted based on problems at MAS Taruna Al Quran Yogyakarta, that the mathematics learning still relied on a publisher generated sources which only focused on students’ understanding, but not yet targeted their middle-low critical thinking skills. It then aims to develop a problem-based learning worksheet on matrix material, which can improve students' critical thinking skills, especially on interpretation and inference indicators. The research used ADDIE development model which has five stages, including analysis, design, development, implementation, and evaluation. Finally, it successfully developed the worksheet rich of learning activities stimulating the students’ critical thinking through the syntax of problem-based learning. The media expert assessment scored 46/50 (very good) and the content expert assessment scored 100/105 (very good). The worksheet also considered practical for use, as shown by the average results of participant questionnaire response scored 84.4 (very good) in the small-scale test and scored 90.5 (very good) in the large-scale test. The developed worksheet also created a significant influence in improving the students’ critical thinking skills by an increase of 25.3%.
HOTS-oriented mathematical problem-solving ability reviewed from the students’ learning styles
Sheilawati, Kharisa Rinandyta;
Setyaningsih, Rini;
Rejeki, Sri
Bulletin of Applied Mathematics and Mathematics Education Vol. 4 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan
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DOI: 10.12928/bamme.v4i2.11579
This research aims to analyze the students' mathematical problem-solving abilities in solving higher order thinking skills (HOTS) oriented mathematics problems in algebra material, particularly reviewed from their learning styles. This research used a qualitative descriptive method. The subjects of this research consisted of 6 students of Class VIII Science 4 at MTs Negeri 1 Surakarta. Data collection techniques consist of questionnaires, tests, and interviews. Data analysis techniques consist of data presentation, data reduction, and conclusion. The results of this research are the mathematical problem-solving abilities of Class VIII Science 4 students based on the visual learning style type which is the same as the auditory learning style in solving problems on linear equation system in two variable material, namely being able to carry out up to the fourth stage of Polya (understanding problems, planning, solving problems, and looking back at the process). Meanwhile, the mathematical problem-solving abilities of Class VIII Science 4 students are based on the kinesthetic learning style, namely implementing up to the third stage of Polya (understanding the problem, planning, and solving the problem).
The Tahani fuzzy logic method for detecting violence against women in North Sumatra
Nisa, Khairun;
Sari, Rina Filia
Bulletin of Applied Mathematics and Mathematics Education Vol. 4 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan
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DOI: 10.12928/bamme.v4i2.11627
Violence against women is a pervasive issue in society. Violence often encompasses various forms, such as physical, psychological, economic, and sexual violence. This research employs the Tahani fuzzy logic method to predict cases of violence against women. The results of the analysis in query fuzzification indicate that there are 16 districts experiencing high number of cases of violence against women, namely: Asahan, Batu Bara, Dairi, Deli Serdang, Karo, Binjai, Gunung Sitoli, Pematang Siantar, Tanjung Balai, Labuhan Batu Utara, Labuhan Batu, Langkat, Padang Lawas Utara, and Simalungun. This research also provides recommendations based on detection results, utilizing the fire strength value as the highest-level ranking. Looking at the total 33 districts in North Sumatra, the highest level of violence against women is in Medan, which occurred from July to December 2022, where all four criteria for typical cases of violence against women are significantly high.
Comparison of continuous review system method and min-max method in soybean inventory control
Syafitri, Ellysa;
Lubis, Riri Syafitri
Bulletin of Applied Mathematics and Mathematics Education Vol. 4 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan
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DOI: 10.12928/bamme.v4i2.11670
This study aims to compare the effectiveness of two inventory control methods, namely continuous review system and min-max in controlling soybean raw material inventory in tofu production. The continuous review system method is an inventory control system where raw material inventory is checked continuously while the min-max method is a method that maintains raw materials between the minimum and maximum limits. The data used are data on soybean raw material inventory and needs at the Ali Musa tofu factory in Serdang Bedagai Regency, Indonesia. Based on the results of the analysis of total inventory costs using the continuous review system method, it is IDR 418,978,693 in 2021 and IDR 430,271,763 in 2022. While the total inventory cost using the min-max method is IDR 366,272,031 in 2021 and IDR 367,964,100 in 2022. While the company uses IDR 429,321,708 in 2021 and IDR 445,381,200 in 2022. From the calculations above, the min-max method is more effective in reducing total inventory costs with infrequent ordering frequencies. Since orders are not made regularly, this strategy reduces the number of soybean orders and reduces the cost of ordering. When the reorder limit is reached, the company will place the order. The choice of inventory control method must be adjusted to the needs and operational characteristics of the company. The continuous review system method is better for companies with high and fluctuating raw material needs, while min-max can be used for companies with more stable raw material needs. The findings and the method used in this study could be beneficial for the factory to organize its inventory efficiently.
Identifying malaria disease through red-blood microscopic image with XGBoost and random forest methods
Fajriyah, Rohmatul;
Muhajir, Muhammad;
Abdullah, Ahmad Hussain;
Ayu, Devina Gilar;
Rahman, Iqbal Fathur
Bulletin of Applied Mathematics and Mathematics Education Vol. 4 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan
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DOI: 10.12928/bamme.v4i2.11740
Blood cells that flow in the human body provide information to diagnose a disease. The information provided can be obtained through images of these blood cells using image processing techniques. Malaria is a very deadly disease and can affect everyone. Patients with malaria will experience anaemia because the red blood cells or erythrocytes are contaminated with plasmodium. This study offers an alternative solution to malaria disease identification through the image classification of red blood cells, by applying image processing and image classification methods with XGBoost and random forest. The research was conducted using the R programming language in RStudio and Python. The accuracy of XGBoost and random forest methods were 71.26% and 77.58%, respectively. Therefore, the random forest provided a better optimal classification model with higher accuracy. The model is used to build an application which is R web-based, RShiny. In practice, this application can be used by health workers in classifying patients based on red blood cell images such that the health centre would be easier to manage the existing patients.