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The Effect of Family Environment on Student Learning Achievement: A Review of the Literature in Indonesia Suwandi, Mohamad Ardin; Rakuasa, Heinrich; Latue, Philia Christi
Journal of Loomingulisus ja Innovatsioon Vol. 1 No. 2 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/innovatsioon.v1i2.1204

Abstract

Contains a detailed summary of the research conducted and written in 1 This research examines the influence of family environment on student learning achievement in Indonesia. By analyzing existing literature, this research identifies key factors such as parental involvement, socioeconomic status and family dynamics that influence student learning outcomes. The methods used include quantitative, qualitative and mixed research to provide a comprehensive understanding of this relationship. Findings show that a supportive family environment contributes positively to students' academic achievement and educational aspirations. This research provides important implications for parents, educators and policy makers in creating an environment conducive to learning.
Utilization of Bing Image Creator to Design Learning Media with the Theme of Natural Disasters in the Form of Artificial Intelligence-Based Animation Yamres Pakniany; Latue, Philia Christi; Heinrich Rakusa
Journal Education Innovation (JEI) Vol. 1 No. 1 (2023): Oktober 2023
Publisher : Yayasan Perguruan Kampus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65474/t22nyy65

Abstract

This research describes the utilization of the Bing Image Creator platform in designing learning media with the theme of natural disasters in the form of animations supported by Artificial Intelligence (AI). Increasingly sophisticated AI technology has brought significant innovation in education, and in the context of natural disaster learning, it opens the door for educators to create more engaging, informative and adaptive learning experiences. Bing Image Creator provides access to a variety of high-quality images and illustrations that allow curriculum creators to depict in detail the phenomenon of natural disasters.  This research uses a descriptive qualitative approach. This research uses the Bing Image Creator platform to design learning media with the theme of natural disasters in the form of animation. The results showed that the integration of AI Bing Image Creator really helped the teacher to design learning media with the theme of natural disasters in the form of animations which included floods, landslides, volcanic eruptions, tsunamis, putting winds, tsunamis and earthquakes to help in the teaching and learning process. Another result is a learning media that allows students to better understand the causes, impacts and coping tactics of natural disasters, as well as increase awareness and preparedness in facing disaster threats. This article discusses the concepts and implications of using Bing Image Creator and AI in the context of natural disaster education and its impact on learning effectiveness and student understanding.
Spatial Distribution and Suitability of the Endemic Babirusa Habitat (Babyrousa babyrussa) on Buru Island, Maluku using Maximum Entropy Rakuasa, Heinrich; Khromykh, Vadim V; Latue, Philia Christi; Manakane, Susan E; Somae, Glendy; Joshua, Benson
BIOPENDIX: Jurnal Biologi, Pendidikan dan Terapan Vol 13 No 1 (2026): Biopendix: Jurnal Biologi, Pendidikan & Terapan
Publisher : Program Studi Pendidikan Biologi FKIP Unpatti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/biopendixvol13issue1page41-51

Abstract

Buru Island is the endemic habitat of the Babirusa (Babyrousa babyrussa), facing pressures from human activities and habitat fragmentation. This study used the Maximum Entropy (MaxEnt) modeling method to map the spatial distribution and assess the habitat suitability of Babirusa based on environmental variables including elevation, slope, temperature, land cover, distance to water, and distance from built-up areas. The results show that the habitat is divided into four main classes: Very Low at 24.95%, Low at 31.67%, Moderate at 29.71%, and High at 13.68% of the total island area, which requires more intensive management and protection. Elevation and distance from settlements have an influence but with relatively small contributions, indicating the species’ tolerance to elevation variation. This model provides a scientific basis for integrated conservation strategies, including habitat management, reduction of anthropogenic pressures, and sustainable spatial planning based on habitat suitability to ensure the long-term survival of Babirusa on Buru Island.