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All Journal Jurnal Riset Rumpun Matematika dan Ilmu Pengetahuan Alam (JURRIMIPA) Bilangan: Jurnal Ilmiah Matematika, Kebumian dan Angkasa Algoritma: Jurnal Matematika, Ilmu Pengetahuan Alam, Kebumian dan Angkasa
Grace Amelia Purba
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Astronomy Earth & Planetary Sciences 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.
Analisis Perbandingan Tingkat Depresi pada Mahasiswa Angkatan 2022 dan 2024 Jurusan Biologi Universitas Negeri Medan Findi Septiani; Endang Lyfia Saragih; Grace Amelia Purba; Petra Putri Sarinah Pandiangan; Rizka Nabila Damanik
Algoritma : Jurnal Matematika, Ilmu pengetahuan Alam, Kebumian dan Angkasa Vol. 3 No. 2 (2025): Algoritma : Jurnal Matematika, Ilmu pengetahuan Alam, Kebumian dan Angkasa
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/algoritma.v3i2.444

Abstract

Mental health disorders, particularly depression, are becoming an increasing concern among university students. This study aims to analyze the comparative levels of depression among students from the 2022 and 2024 cohorts in the Biology Department at Universitas Negeri Medan. The research employs a mixed-method approach, integrating both quantitative and qualitative methodologies. Data were collected through questionnaires distributed to 51 active students. The results indicate that students from the 2022 cohort exhibit higher levels of depression compared to those from the 2024 cohort, due to academic pressure, social factors, and lifestyle habits. These findings highlight the importance of preventive strategies and interventions to mitigate depression risks, such as stress management, promoting healthy lifestyle habits, and strengthening social support in academic environments. Therefore, educational institutions must prioritize student mental health to foster a more conducive learning environment.
Penerapan Konsep Bunga Majemuk dalam Analisis Pertumbuhan Modal Usaha Penjual Sayur di Pasar Tradisional MMTC Medan Arnah Ritonga; Endang Lyfia Saragih; Grace Amelia Purba; Petra Putri Sarinah Pandiangan; Rizka Nabila Damanik
JURNAL RISET RUMPUN MATEMATIKA DAN ILMU PENGETAHUAN ALAM Vol. 4 No. 2 (2025): Agustus: Jurnal Riset Rumpun Matematika dan Ilmu Pengetahuan Alam
Publisher : Pusat riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurrimipa.v4i2.6937

Abstract

This study analyzes the application of the compound interest concept in evaluating capital growth among vegetable vendors at the MMTC Traditional Market in Medan, North Sumatra. The research highlights the low level of financial literacy among micro-entrepreneurs in Indonesia, which currently stands at only 38.03%, and its implications for business sustainability. Traditional market traders generally employ basic bookkeeping practices focused solely on daily cash flow, without considering the time value of money or the growth potential from systematic profit reinvestment. Using a mixed-methods approach, this study combines semi-structured interviews to explore existing financial management practices with quantitative modeling based on the discrete compound interest formula to simulate various capital growth scenarios. The analysis reveals that disciplined reinvestment strategies, even when initiated with modest capital and conservative growth rates, can lead to substantial capital accumulation within three to five years. Three primary barriers to capital growth were identified: limited understanding of financial mathematics, lack of long-term planning, and a tendency to prioritize immediate consumption over investment. This research underscores the transformative potential of compound interest principles for micro-enterprise development and recommends practical financial literacy training along with supportive financial ecosystems that encourage sustainable reinvestment practices.
Co-Authors Arnah Ritonga Endang Lyfia Saragih Farel Al Azmi Findi Septiani Petra Putri Sarinah Pandiangan Rizka Nabila Damanik