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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Community Development Journal: Jurnal Pengabdian Masyarakat
Suryabuana, Andi Sahra
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Humanities Computer Science & IT Economics, Econometrics & Finance Education Health Professions Public Health

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DESAIN PEMBUATAN MEDIA PEMBELAJARAN INTERAKTIF DENGAN CLASS POINT AI DI UPTD SD 62 PAREPARE Rahman, Rakhmadi; Mar’atuttahirah, Mar’atuttahirah; Tunnisa, Khaera; Putra, Alvian Tri; Abdullah, Abdullah; Al-Amin, Muh.; Suryabuana, Andi Sahra; Ramadhan, Syam Syahru; Fathuresqi, Fathuresqi
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 4 No. 6 (2023): Volume 4 Nomor 6 Tahun 2023
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v4i6.21982

Abstract

Kegiatan pengabdian yang akan dilaksanakan di UPTD SD 62 Parepare merupakan kegiatan pengabdian yang akan dilaksanakan berdasar dari masalah yang ada di UPTD SD 62 Parepare yaitu dalam Dalam proses pembelajaran, guru menggunakan aplikasi power point sebagai media untuk menyampaikan materi, belum ada pengembangan sumber daya dalam pembelajaran dengan memberikan pelatihan desain pembuatan media pembelajaran interaktif. Ternyata dengan hal tersebut dapat menurunkan semangat belajar siswa sehingga tujuan pembelajaran tidak tercapai dengan baik. Tujuan kegiatan pengabdian ini adalah untuk memberikan pelatihan desain pembuatan media pembelajaran interaktif di UPTD SD 62 Parepare dengan Class Point AI sehingga nantinya guru dapat membuat media pembelajaran  dengan pemanfaatan teknologi AI sebagai solusi yang komprehensif untuk guru mampu berkembang secara professional, mampu meningkatkan efektifitas siswa, bekerja secara efisien, mengajar secara interaktif dengan pemanfaatan Class Point AI  sehingga mendorong integritas akademik untuk mendukung pembelajaran yang aktif, kreatif dan inovatif. Luaran Kegiatan PKM akan di publikasikan pada Jurnal Pengabdian Kepada Masyarakat.
Evaluation of Machine Learning Algorithm for Automatic Assessment of School Students' English Essay Ali, Andi Nurfadillah; Hading, Muhaimin; Suryabuana, Andi Sahra
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 1 (2026): Article Research January 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i1.15496

Abstract

The manual assessment of essays in English language learning often faces challenges related to objectivity and efficiency, especially on a large scale. With advancements in artificial intelligence technology, machine learning-based approaches have begun to be adopted to automate this process through Automated Essay Scoring (AES) systems. However, most existing AES models tend to rely solely on the final scores from the dataset without considering the structural quality of the writing, such as coherence between paragraphs. This study aims to evaluate the effectiveness of machine learning algorithms in assessing school students' essays by adding coherence features as predictor variables in a regression model. This approach uses linguistic feature representation techniques to explicitly build coherence indicators. The proposed model achieved a QWK improvement from 0.69 to 0.89 using SMOTE and coherence features. Meanwhile, human evaluation results showed that the pair of Rater 1 and Rater 2 achieved a QWK of 0.82, the pair of Rater 1 and Rater 3 scored 0.79, and the pair of Rater 2 and Rater 3 scored 0.81. These values indicate a high level of agreement among raters, suggesting that the assessment instrument used is stable. The main contribution of this study is introducing the coherence feature as an explicit predictor in the AES model, filling the gap not provided by standard datasets and proving that coherence improves model accuracy. This research provides practical benefits such as speeding up the evaluation process, reducing teachers' workload, and improving the objectivity and consistency of assessment in language education and evaluation.
Co-Authors Abdullah B Al-Amin, Muh. Alvian Tri Putra Darti Akhsa Andi Nurfadillah Ali Fathuresqi, Fathuresqi Hading, Muhaimin Khaera Tunnisa, Khaera Mar’atuttahirah, Mar’atuttahirah Rakhmadi Rahman Ramadhan, Syam Syahru