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All Journal Inventa: Journal of Science, Technology, and Innovation
Feri Pahriansya
Universitas Pamulang
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Pemodelan Jumlah Tugas Mingguan Mahasiswa Menggunakan Distribusi Poisson: Studi Kasus Kelas Reguler CK Universitas Pamulang Feri Pahriansya; Novianto Dwi Nugroho; Achmad Wahyudin; Aditya Efendi
Journal of Science, Technology, and Innovation Vol 1 No 2 (2025): December: Inventa: Journal of Science, Technology, and Innovation
Publisher : CV SCRIPTA INTELEKTUAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65310/necaqv09

Abstract

This study aims to model the weekly number of academic assignments received by students using the Poisson distribution, with a case study of Regular CK class students at Universitas Pamulang. The data were collected from 20 students through an online questionnaire that recorded the total number of assignments received from all courses during the previous week. Descriptive statistical analysis shows that the average number of weekly assignments is 4.25, with a variance of 2.41 and observed values ranging from 2 to 8 assignments. These characteristics indicate a discrete count data structure within a fixed time interval. The Poisson distribution parameter was estimated using the sample mean, and a Chi-Square Goodness-of-Fit test was applied to examine the suitability of the Poisson model. The test results indicate that the observed frequency distribution does not significantly differ from the expected Poisson distribution at the 5 percent significance level. This finding suggests that the weekly assignment distribution can be adequately represented by a Poisson model. The study demonstrates the practical application of Poisson distribution in educational data analysis and provides a quantitative perspective on academic workload patterns among working students.
Co-Authors Achmad Wahyudin Aditya Efendi Novianto Dwi Nugroho