Penerapan Distribusi Normal Dalam Pengukuran Tinggi Badan Mahasiswa FMIPA Universitas Negeri Medan 2024

Authors

  • Arnah Ritonga Universitas Negeri Medan
  • Endang Lyfia Saragih Universitas Negeri Medan
  • Grace Amelia Purba Universitas Negeri Medan
  • Petra Putri Sarinah Pandiangan Universitas Negeri Medan
  • Rizka Nabila Damanik Universitas Negeri Medan
  • Farel Al Azmi Universitas Negeri Medan

DOI:

https://doi.org/10.62383/bilangan.v3i2.465

Keywords:

Descriptive statistics, Height measurement, Normal distribution, Probability, Shapiro-Wilk test

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.

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References

Avram, C., & Mărușteri, M. (2022). Penilaian normalitas, beberapa paradigma dan kasus penggunaan. Revista Romana de Medicina de Laborator, 30(3), 251–260. https://doi.org/10.2478/rrlm-2022-0033 (jika DOI tersedia, tambahkan)

Cheng, Z. (2024). Remarks on normal distribution and central limit theorem. Highlights in Science, Engineering and Technology, 94, 442–446.

Expectation-, M. A. (2019). Estimasi parameter distribusi T Ahmad Yani. (Penerbit tidak disebutkan).

Faturochman, F., & Dwiyanto, A. (2016). Validitas dan reliabilitas pengukuran keluarga sejahtera. Populasi, 9(1), 1–19. https://doi.org/10.22146/jp.11710

Luzuriaga Jaramillo, H. A., Espinosa Pinos, C. A., Haro Sarango, A. F., & Ortiz Román, H. D. (2023). Histograma y distribución normal: Shapiro-Wilk y Kolmogorov Smirnov aplicado en SPSS. Revista Latinoamericana de Ciencias Sociales y Humanidades, 4(4), 596–607. https://latam.redilat.org/index.php/lt/article/view/1242

Nurudin, M., Mara, M. N., & Kusnandar, D. (2014). Ukuran sampel dan distribusi sampling dari beberapa variabel random kontinu. Jurnal Ilmiah, 03(1), 1–6.

Permana, R. A., & Ikasari, D. (2023). Uji normalitas data menggunakan metode empirical distribution function dengan memanfaatkan Matlab dan Minitab 19. Semnas Ristek (Seminar Nasional Riset dan Inovasi Teknologi), 7(1), 7–12. https://doi.org/10.30998/semnasristek.v7i1.6238

Pratikno, A. S., Prastiwi, A. A., & Ramahwati, S. (2020). Sebaran peluang acak kontinu, distribusi normal, distribusi normal baku, distribusi T, distribusi Chi Square, dan distribusi F. OSF Preprints, 27(3), 1–5.

Sintia, I., Pasarella, M. D., & Nohe, D. A. (2022). Perbandingan tingkat konsistensi uji distribusi normalitas pada kasus tingkat pengangguran di Jawa. Prosiding Seminar Nasional Matematika, Statistika, dan Aplikasinya, 2(2), 322–333.

Sungkono, J., Wulandari, A. A., & Syaifuddin, M. W. (2023). Visualisasi R dalam pembelajaran distribusi normal. Widya Didaktika - Jurnal Ilmiah Kependidikan, 2(1), 71–77. https://doi.org/10.54840/juwita.v2i1.118

Syagata, A. S., Rohmah, F. N., Khairani, K., & Arifah, S. (2021). Evaluasi pelaksanaan pengukuran tinggi badan oleh kader Posyandu di wilayah Yogyakarta. Jurnal Kebidanan dan Keperawatan Aisyiyah, 17(2), 195–203. https://doi.org/10.31101/jkk.2311

Ummah, M. S. (2019). No 主観的健康感を中心とした在宅高齢者における 健康関連指標に関する共分散構造分析Title. Sustainability (Switzerland), 11(1), 1–14. http://scioteca.caf.com/bitstream/handle/123456789/1091/RED2017-Eng-8ene.pdf

Ye, X. (2024). Unveiling the intricacies of the normal distribution: From theory to applications. Theoretical and Natural Science, 36(1), 175–179. https://doi.org/10.54254/2753-8818/36/20240617

Yusa, M., Santoso, J. D., & Sanjaya, A. (2021). Implementasi dan perancangan pengukur tinggi badan menggunakan sensor ultrasonik. Pseudocode, 8(1), 90–97. https://doi.org/10.33369/pseudocode.8.1.90-97

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Published

2025-04-09

How to Cite

Arnah Ritonga, Endang Lyfia Saragih, Grace Amelia Purba, Petra Putri Sarinah Pandiangan, Rizka Nabila Damanik, & Farel Al Azmi. (2025). Penerapan Distribusi Normal Dalam Pengukuran Tinggi Badan Mahasiswa FMIPA Universitas Negeri Medan 2024. Bilangan : Jurnal Ilmiah Matematika, Kebumian Dan Angkasa, 3(2), 39–53. https://doi.org/10.62383/bilangan.v3i2.465

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