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All Journal Pelita Eksakta Jurnal Statistika dan Matematika (Statmat)
Fadhillah Fitri
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Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Physics Other

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Statistics Topics Training For High School Teachers in Padang Admi Salma; Dodi Vionanda; Dony Permana; Fadhillah Fitri; Dina Fitria; Zilrahmi Zilrahmi
Pelita Eksakta Vol 5 No 1 (2022): Pelita Eksakta Vol. 5 No. 1
Publisher : Fakultas MIPA Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/pelitaeksakta/vol5-iss1/181

Abstract

One of a part mathematics subjects for high school students is statistics. Some statistics topics were usually studied by university students, but now they are studied by high school students. Teachers have difficulty teaching the topic to students for several reasons. The training is needed in order to improve the ability and knowledge of teachers about the statistics topics . The training was given to high school mathematics teachers in Padang under group named MGMP. There are 25 participans of the training. The results of activity evaluation showed an increase in the knowledge of statistics topics. In conclusion, this activity has been effectively carried out and can help the mathematics teachers to deeply understanding statistical topics
Klasterisasi Pendapatan Nasional dan Pola Konsumsi Negara-Negara G20 Tahun 2023 Menggunakan Metode K-Means Fatta, M Fatta Arya Irwanda; Ridho Saputra; M. Allif Khair; Fadhillah Fitri
STATMAT : JURNAL STATISTIKA DAN MATEMATIKA Vol 8 No 1 (2026)
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Pamulang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/sm.v8i1.55980

Abstract

The G20 countries are often treated as a relatively homogeneous group in macroeconomic analysis, despitesubstantial differences in income levels, economic growth, and consumption patterns among member countries.This study aims to classify G20 countries based on national income, economic growth, and consumptionindicators in order to identify structural differences in their economic characteristics. The analysis employsthe K-Means clustering method using standardized data to ensure comparability across variables with differentmeasurement scales. Prior to clustering, data standardization is applied using the Z-score method. The optimalnumber of clusters is determined using a cluster validity measure, and the clustering process is performedusing Euclidean distance. The results indicate that the optimal clustering structure is achieved with threeclusters. The K-Means algorithm successfully groups G20 countries into three distinct clusters with clearlydifferentiated economic profiles. The centroid analysis reveals that each cluster exhibits unique characteristicsin terms of income level, growth dynamics, and consumption patterns, allowing for objective and data-drivencluster categorization. The findings also show that higher income levels are not always associated with higherconsumption patterns, and that developing economies tend to form a separate cluster characterized byrelatively higher economic growth. The evaluation of cluster quality indicates good cohesion within clustersand clear separation between clusters, suggesting that the clustering results are valid and reliable. Overall,this study demonstrates that cluster analysis provides an effective framework for capturing the heterogeneityof economic structures among G20 countries. The findings contribute to a more nuanced understanding ofglobal economic diversity and may serve as a basis for comparative economic analysis and policy orienteddiscussions.
Co-Authors Admi Salma Dina Fitria Dodi Vionanda Dony Permana Fatta, M Fatta Arya Irwanda M. Allif Khair Ridho Saputra Zilrahmi, Zilrahmi