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All Journal Semeton Mathematics Journal IJASDS: Indonesian Journal of Applied Statistics and Data Science
Auladi, Muhammad Yuzaul
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Economics, Econometrics & Finance Environmental Science Mathematics Public Health Social Sciences

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Pengaruh metode pembelajaran project based learning terhadap motivasi belajar mahasiswa prodi matematika FMIPA Universitas Mataram Ayudia, Nurul Ulya; Pradana, Satriawan; Juliansyah, Wahyu Ari; Pratama, Muhammad Imran Ade; Auladi, Muhammad Yuzaul; Purnamasari, Nur Asmita
Semeton Mathematics Journal Vol 2 No 1 (2025): April
Publisher : Program Studi Matematika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/semeton.v2i1.267

Abstract

This study evaluates the impact of the Project-Based Learning (PBL) method on the learning motivation of Mathematics students at FMIPA Universitas Mataram. The primary objective is to assess the effectiveness of PBL in enhancing learning motivation and to explore the influencing factors, namely Facilities (X₁), Lecturer Role (X₂), and Skill Development (X₃). This research employs a quantitative descriptive method, with a population of 257 Mathematics students from FMIPA Universitas Mataram, covering the 2020–2023 cohorts. The sample is determined using the Stratified Random Sampling method. Data were collected through research instruments that had been tested for validity and reliability. Data analysis was conducted using descriptive analysis (pie charts, bar charts, histograms, and scatter plots) and multiple linear regression to identify the influence of the independent variables (X₁, X₂, X₃) on (Y). The findings indicate that 63.8% of the variation in learning motivation (Y) can be explained by Facilities (X₁), Lecturer Role (X₂), and Skill Development (X₃). Both simultaneous and partial tests confirm that all independent variables contribute significantly to students’ learning motivation. These results suggest that the PBL method is not only effective in enhancing learning motivation but also holds potential as an innovative teaching strategy in higher education.
Pengklasifikasian 10 Kabupaten/Kota di Provinsi Nusa Tenggara Barat untuk Kasus Kemiskinan Tahun 2022 Menggunakan Analisis Cluster Metode K-Means Sabina, Sabna Zulfaa; Alfarez, Dzaki Ade; Graha, Syifa Salsabila Satya; Auladi, Muhammad Yuzaul; Lisa , Harsyiah; Lisa Harsyiah
Indonesian Journal of Applied Statistics and Data Science Vol. 1 No. 1 (2024): November
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ijasds.v1i1.5415

Abstract

Poverty is a very serious problem for countries in the world, especially for developing countries like Indonesia. Poverty will have a big impact if it occurs in the long term with different factors. One province that is still in the spotlight for high levels of poverty is West Nusa Tenggara Province. Even though the number of poor people in West Nusa Tenggara Province has decreased, conditions of the ground show that there are still many people whose lives are far from decent. Therefore, the government must immediately find a solution to overcome the problem of poverty. To overcome cases of poverty in a region, we can group the characteristics of these regions based on poverty indicators into several clusters. Grouping in this case is carried out with data that will be analyzed using the K-Means cluster analysis method. So the results obtained by analysis using the K-Means cluster method for grouping 10 regencies/cities in West Nusa Tenggara Province based on poverty in 2022 formed 3 clusters, namely cluster 1 consisting of West Sumbawa Regency, Bima City and Mataram City, cluster 2 consisting of Bima Regency, Dompu Regency, West Lombok Regency, Central Lombok Regency, East Lombok Regency, and Sumbawa Regency, and cluster 3 consists of North Lombok Regency. Apart from that, the characteristics of each cluster were also obtained, namely cluster 1 containing the districts/cities with the highest PPM values. While RLS, AHH, and TPT have very high numbers in 2022, cluster 2 contains districts/cities that have quite low PPM, RLS, AHH, and TPT numbers in 2022, and cluster 3 contains a group of districts/cities with RLS, AHH, and TPT has quite low numbers compared to the high PPM in 2022.
Co-Authors Alfarez, Dzaki Ade Ayudia, Nurul Ulya Graha, Syifa Salsabila Satya Harsyiah, Lisa Juliansyah, Wahyu Ari Lisa , Harsyiah Pradana, Satriawan Pratama, Muhammad Imran Ade PURNAMASARI, NUR ASMITA Sabina, Sabna Zulfaa