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A Study of Grouping of Earthquake Damage from Magnitude Scale in Lombok Using K-Means Modeling Kertanah; Alissa Chintyana; Chandrawati; Basirun; Mutia Rosiana Nita Putri; Nasibatul Mahmudah
Kappa Journal Vol 8 No 3 (2024): Desember
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/kpj.v8i3.27563

Abstract

This study aims to group earthquake damage from its magnitude scale and visualize it on a geographical map. The magnitude of the earthquake was grouped using the K-means model. It is one of the most popular and effective clustering models in grouping data, such as earthquake data. The dataset used in this study is earthquake data for the last ten years on Lombok Island. The optimal number of clusters was used which is 2 in this case, based on the highest Silhouette score of 0.930. The highest Silhouette score shows the optimal number of clusters. The cluster on the geographical map shows most earthquakes' distribution in Northen Lombok Island with cluster 1 consisting of 145 earthquakes, while cluster 2 consists of 3 earthquakes. In addition, the earthquake's damage based on its magnitude scale, there were four different kinds of earthquake damage: slight, limited, minor, and severe damage that have occurred for the last ten years in Lombok Island. Minor and Slight damages were dominant, respectively. However, severe damage occurred in the northern part of Lombok Island due to an earthquake in 2018.
Parental Income and Education as Predictors of Physics Exam Success: A Neural Network and Random Forest Regression Analysis Putri, Mutia Rosiana Nita; Kertanah; Bustari, Mugni; Aminuddin, Muhammad; Khotimah, Baiq Husnul
Jurnal Penelitian Pendidikan IPA Vol 11 No 10 (2025): October: In Progress
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i10.12307

Abstract

This study examines the relationship between the socioeconomic status (SES) of tenth-grade students at SMA Negeri 4 Praya and their final physics exam scores for the 2022/2023 academic year. SES indicators include parents' income and education level, collected via qualitative questionnaires and quantitative assessment of physics exam scores. Random Forest Regression and Neural Network techniques were used for analysis. The results showed no significant relationship between SES and physics scores. For parents' education level, Neural Network Regression yielded a Mean Squared Error (MSE) of 323.78 and an R² score of -0.0129, while Random Forest Regression produced an MSE of 327.08 and an R² score of -0.0232. Similarly, for parents' income, Random Forest Regression resulted in an MSE of 327.08 and an R² score of -0.0232, and Neural Network Regression yielded an MSE of 323.78 and an R² score of -0.0129. These negative R² scores indicate that SES does not significantly impact physics exam scores, highlighting the complexity of factors influencing academic performance. This research suggests that other variables may play a more critical role in determining students' success in physics. This research underscores the need for a more comprehensive approach to understanding and supporting student achievement in education.
Co-Authors Alissa Chintyana Basirun Bustari, Mugni Chandrawati Khotimah, Baiq Husnul Muhammad Aminuddin, Muhammad Mutia Rosiana Nita Putri Nasibatul Mahmudah Putri, Mutia Rosiana Nita