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All Journal Bilangan: Jurnal Ilmiah Matematika, Kebumian dan Angkasa
Farel Al Azmi
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Astronomy Mathematics

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Penerapan Distribusi Normal Dalam Pengukuran Tinggi Badan Mahasiswa FMIPA Universitas Negeri Medan 2024 Arnah Ritonga; Endang Lyfia Saragih; Grace Amelia Purba; Petra Putri Sarinah Pandiangan; Rizka Nabila Damanik; Farel Al Azmi
Bilangan : Jurnal Ilmiah Matematika, Kebumian dan Angkasa Vol. 3 No. 2 (2025): Bilangan : Jurnal Ilmiah Matematika, Kebumian dan Angkasa
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/bilangan.v3i2.465

Abstract

This study explores the application of the normal distribution in analyzing the height data of Mathematics Education students at FMIPA Universitas Negeri Medan in 2024. Employing a quantitative descriptive-analytic methodology, the research involved collecting primary data from 10 randomly selected students through a questionnaire-based survey. Descriptive statistical analysis revealed a mean height of 161.4 cm with a standard deviation of 8.79 cm. The median height was found to be 164 cm, while the mode was 150 cm, indicating a slightly skewed distribution. To assess the suitability of the normal distribution model, the Shapiro-Wilk test was applied, resulting in a W value of 0.921 and a p-value of 0.361, which exceeds the 0.05 significance level. This confirms that the sample data follow a normal distribution pattern. The findings were further supported through visual representation using histograms and analysis based on the empirical rule, which showed that approximately 68% of the students' heights fall within one standard deviation of the mean (152.81–169.99 cm). Additionally, probability calculations demonstrated that the likelihood of a student being 160 cm tall or shorter is approximately 43.64%. These results validate the effectiveness of the normal distribution as a tool for analyzing biological or physical characteristics, even in small sample sizes. However, the study acknowledges its limitation in terms of sample size and suggests that future research involve larger and more diverse populations to enhance generalizability. The study highlights the relevance of normal distribution in statistical modeling, particularly for educational and health-related data interpretation and decision-making processes.
Penerapan Integral Lipat Dua dalam Prediksi Jumlah Penduduk di Kota Tebing Tinggi Tahun 2030 : Visualisasi 3D Menggunakan Geogebra Petra Putri Sarinah Pandiangan; Alvi Sahrin Nasution; Grace Amelia Purba; Rizka Nabila Damanik; Endang Lyfia Saragih; Farel Al Azmi
Bilangan : Jurnal Ilmiah Matematika, Kebumian dan Angkasa Vol. 3 No. 6 (2025): Desember : Bilangan : Jurnal Ilmiah Matematika, Kebumian dan Angkasa
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/bilangan.v3i6.884

Abstract

Tebing Tinggi City, which has a strategic position in North Sumatra, is experiencing changes in population growth that need to be predicted for development planning purposes. The purpose of this study is to forecast the population of Tebing Tinggi City in 2030 by applying the Double Integral method, and visualize the results in 3D using GeoGebra. The method used is a quantitative approach with a case study, where the population density function is created based on secondary data from the Central Statistics Agency (BPS) of Tebing Tinggi City for the period 2010 to 2024. Data on area and population per sub-district are used to develop a population growth model calculated using the double integral. The forecast results show that the population of Tebing Tinggi City is estimated to reach 26,038 people in 2030, with varying growth rates in each sub-district. 3D visualization through GeoGebra is able to depict the distribution of population density in an interactive geometric form, thus facilitating the understanding of complex mathematical concepts. The conclusion of this study is that double integrals can be applied effectively to predict population size, and GeoGebra serves as a very useful visual aid in presenting the results of multivariable calculus analysis.
Co-Authors Alvi Sahrin Nasution Arnah Ritonga Endang Lyfia Saragih Grace Amelia Purba Petra Putri Sarinah Pandiangan Rizka Nabila Damanik