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All Journal Cendikia : Media Jurnal Ilmiah Pendidikan KAMBOTI : Jurnal Sosial dan Humaniora
Werluka, Baceria
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Religion Arts Humanities Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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Penggunaan Model Problem Based Learning Melalui Google Slides untuk Meningkatkan Pemahaman Konsep Matematika pada Materi Regresi Werluka, Baceria; Ratuanik, Mesak; Laritmas, Endemina O
KAMBOTI: Jurnal Sosial dan Humaniora Vol. 5 No. 2 (2025): KAMBOTI: Jurnal Sosial dan Humaniora
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah XII

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51135/kambotivol5issue2page148-162

Abstract

Technology can act as a communication tool between educators and students, transforming traditional teaching methods into more innovative approaches. For the fourth-semester students in the Mathematics Education Study Program, who struggle to understand mathematical concepts like regression, the proposed solution is using the Problem-Based Learning (PBL) model with Google Slides to enhance learning quality. This study aims to assess the impact of using the PBL model with Google Slides on students' understanding of mathematical concepts. The research uses a descriptive qualitative method to provide an in-depth explanation of how PBL supported by Google Slides can improve students' understanding of regression material. Data were collected through observation, interviews, documentation, tests, field notes, and literature studies. The results showed a 63% improvement in students' understanding of regression concepts. Nine students scored between 70-100 (high category), three students scored between 55-69.9 (medium category), and one student scored below 54 (low category). The integration of PBL with Google Slides proved effective in enhancing students' understanding of regression topics, such as gradient, y-intercept, and regression. This approach is an effective solution for improving students' comprehension of the material.
Classification of villages in Tanimbar Islands based on stunting service packages using the K-Means Algorithm Ratuanik, Mesak; Urath, Samuel; Jabar, Pesparani Diana; Werluka, Baceria; Batbual, Inda A.; Melemabessy, Thobias
Cendikia : Media Jurnal Ilmiah Pendidikan Vol 14 No 5 (2024): May: Education Science
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cendikia.v14i5.4947

Abstract

The Tanimbar Islands Regency still has a high prevalence of stunting in toddlers, so we must work together to eradicate it. According to WHO, the prevalence of stunting should not exceed 20%. According to data from the 2021 Indonesian Nutritional Status Survey (SSGI), the prevalence of stunting in toddlers is currently 25.1% in the Tanimbar Islands District, Maluku Province. The purpose of this study was to classify villages based on the indicators of the stunting service package in the Tanimbar Islands District. This research uses an analytic survey approach using secondary data obtained from the Central Bureau of Statistics (BPS) of the Republic of Indonesia in 2022 and the Tanimbar Islands District Health Office in 2022 by utilizing the K-Means Algorithm. The stages of data analysis in this study consisted of library research, data collection, data processing, the K-Means algorithm. Furthermore, the last stage is to verify the data consisting of analysis of findings based on the theory used. At this analysis stage, the K-Means Clustering Method was also applied to classify villages in the Tanimbar Islands District based on the stunting service package. Research results based on analysis using the K-Means algorithm (Number of causes in each cluster) provide an overview of the number of clusters that enter each cluster. Cluster 1 consists of 20 villages, cluster 2 consists of 66 villages, cluster 3 consists of 1 village and cluster 4 consists of 1 village.
Co-Authors Batbual, Inda A. Laritmas, Endemina O Melemabessy, Thobias Pesparani Diana Jabar