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All Journal Pendas : Jurnah Ilmiah Pendidikan Dasar Ta’wiluna: Jurnal Ilmu Al-Qur’an,Tafsirdan Pemikiran Islam Mimbar Pendidikan Indonesia TOFEDU: The Future of Education Journal IHSAN : Jurnal Pendidikan Islam Jurnal Nakula: Pusat Ilmu Pendidikan, Bahasa Dan Ilmu Sosial Jurnal Informatika: Jurnal Pengembangan IT Diversitas : Jurnal Manajemen
Ahmad Syarifuddin
Unknown Affiliation
Religion Humanities Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Deep Learning-Based Sentiment Analysis of Islamic Boarding School Google Reviews Using IndoBERT Variants and XLM-RoBERTa Ahmad syarifuddin
Jurnal Informatika: Jurnal Pengembangan IT Vol 11, No 1 (2026)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v11i1.10021

Abstract

Online reviews on platforms like Google Maps have become a crucial data source for analyzing public opinion and consumer behavior, including in the context of selecting religious educational institutions, specifically pesantren (Islamic boarding schools). This study aims to perform sentiment analysis to measure public perception towards pesantren located across the island of Java. The data were collected via web scraping, yielding a total of 8,577 reviews, which subsequently underwent essential text preprocessing steps including cleansing, case folding, tokenization, stopword removal, and stemming. The prepared dataset was then partitioned using the Stratified Train-Test Split method into 70% for training and 30% for testing.The research evaluated the performance of three pre-trained language models IndoBERT Base, IndoROBERTa Small, and XLM-RoBERTa, which were fine-tuned using the Focal Loss function. The training strategy prioritized saving the best model based on the neutral F1-score.The final evaluation on the unseen test data demonstrated that the IndoBERT Base model significantly outperformed the others, achieving the highest overall accuracy of 0.92 (92%). This strong balance confirms the model's excellent generalization ability, indicating no significant overfitting and successful mitigation of classification bias. The findings validate IndoBERT Base as the optimal model for sentiment classification of pesantren reviews. Future research is recommended to shift focus toward building a larger, more diverse dataset to further enhance model generalizability.
PENGARUH METODE PEMBELAJARAN TEAM GAMES TOURNAMENT (TGT) BERBANTU WORDWALL TERHADAP HASIL BELAJAR PESERTA DIDIK PADA MATA PELAJARAN IPA KELAS VI DI MI DAARUL AITAM PALEMBANG Echa Silvia; Ahmad Syarifuddin; Agra Dwi Saputra; Tutut Handayani
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 11 No. 2 (2026): Volume 11 No. 02, Juni 2026.
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i2.56158

Abstract

In the current educational landscape, student-centered and interactive learning methods are increasingly important for improving learning outcomes. However, the implementation of innovative teaching strategies is often limited by the availability of effective learning media. This study aimed to examine the effect of the Team Games Tournament (TGT) learning method assisted by Wordwall on the science learning outcomes of sixth-grade students at MI Daarul Aitam Palembang. The research employed a quantitative approach using a quasi-experimental design, specifically the Nonequivalent Control Group Pretest–Posttest Design. Samples were selected through purposive sampling, and data were collected using observation, tests, and documentation. Data analysis included validity, reliability, discrimination, difficulty level, normality, homogeneity, and hypothesis testing. The findings revealed that the experimental class achieved a mean post-test score of 84.56, while the control class obtained a mean score of 68.75. The Independent Samples t-Test produced a significance value of 0.000, which is lower than 0.05, indicating that the null hypothesis (H₀) was rejected and the alternative hypothesis (H₁) was accepted. These results demonstrate that the TGT learning method supported by Wordwall has a significant positive effect on students’ science learning outcomes. The study suggests that integrating game-based cooperative learning with digital media can enhance student engagement, motivation, and academic achievement. Therefore, the application of TGT assisted by Wordwall can serve as an effective and enjoyable strategy for improving science learning in elementary schools.
Co-Authors Ade Rizky Yuliarto Afriza Media Agra Dwi Saputra Agung Muhamad Bisri Agustin Windianingsih Amir Hamzah Ari Suriani Azkha Fajar Ramadhan Echa Silvia Faisol Bahri Idris Hakim Lubis Ifan Afandy Julita Lailatul Mukjizat M. Qinthar Rahman Mardiah Astuti Miftahul Husni Minuk Riyana Muhamad Arif Alfa Rizi Muhammad Qinthar Rahman Nabila Rahmatul Husna Najwaa Yasmine Ramadhani Nur Fadhilah Nurma Adlina Puji Hartono Retno Wuri Sulistyowati Sadrack L Pagiling SITI FATIMAH Sri Lestari, Dian Tutut Handayani Wahyu Divangga Tirta Winda Agustin Yonarlianto Tembang Zaenatul Hakamah