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All Journal JURIKOM (Jurnal Riset Komputer) Jurnal Pendidikan, Sains, Geologi, dan Geofisika (GeoScienceEd Journal)
Hidayati, Risma
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Agriculture, Biological Sciences & Forestry Chemistry Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Physics

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Meningkatkan Motivasi Belajar Peserta Didik melalui Pendekatan Culturally Responsive Teaching (CRT) pada Mata Pelajaran Pendidikan Pancasila Kelas V SDN 36 Cakranegara Hidayati, Risma; Malik, Imam; Ayu Tirtawati, Sang
Jurnal Pendidikan, Sains, Geologi, dan Geofisika (GeoScienceEd Journal) Vol. 6 No. 3 (2025): Agustus
Publisher : Mataram University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/goescienceed.v6i4.840

Abstract

This study aims to improve students’ learning motivation in the Pancasila Education subject by applying the Culturally Responsive Teaching (CRT) approach. The research was designed and conducted using the Classroom Action Research (CAR) method, implemented in two cycles. The subjects of this study were 24 fifth-grade students of SDN 36 Cakranegara in the 2024/2025 academic year. Data were collected through a student learning motivation questionnaire administered in each cycle. The questionnaire consisted of 23 items, including both positive and negative statements. The collected data were analyzed using quantitative techniques. The improvement in students’ learning motivation was reflected in the increase in the percentage of students categorized as having high motivation—from 16.67% in the pre-cycle to 33.33% in cycle I and 54.17% in cycle II. Meanwhile, the percentage of students with very high motivation increased from 8.33% in the pre-cycle to 16.67% in cycle I and 37.50% in cycle II. Based on these results, it can be concluded that the application of the Culturally Responsive Teaching (CRT) approach effectively enhances students’ learning motivation in Pancasila Education at SDN 36 Cakranegara.
Public Opinion Sentiment Analysis of the Brain Drain Phenomenon on Social Media X Using the Naive Bayes Classifier Algorithm Hidayati, Risma; Hasugian, Abdul Halim
JURNAL RISET KOMPUTER (JURIKOM) Vol. 12 No. 5 (2025): Oktober 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i5.9131

Abstract

The brain drain phenomenon is an important issue in Indonesia due to the increasing number of young professionals choosing to work abroad, which reduces the quality of human resources within the country. This study aims to analyze public opinion toward the brain drain phenomenon through the X (Twitter) social media platform and classify public sentiment using the Naive Bayes Classifier algorithm. Data were collected through a web crawling process within the last two years, resulting in 1,170 relevant Indonesian-language tweets. The preprocessing stage included cleaning, case folding, tokenizing, normalization, stopword removal, and stemming to produce clean and structured data. Word weighting was performed using the Term Frequency–Inverse Document Frequency (TF-IDF) method to measure the significance of each term. The findings show that public opinion is divided into two main sentiments: positive and negative. Positive sentiment reflects the perception that working abroad offers career advancement and experience, while negative sentiment expresses concern about the loss of skilled human resources. The classification model achieved a high level of accuracy in categorizing sentiment data. This research contributes to understanding public perceptions and provides a foundation for developing strategic policies to address the brain drain issue in Indonesia
Co-Authors Abdul Halim Hasugian Ayu Tirtawati, Sang