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All Journal Jiko (Jurnal Informatika dan komputer) Jurnal EDUCATIO: Jurnal Pendidikan Indonesia
Muhammad Sabri Ahmad
universitas Khairun
Computer Science & IT Education

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Implementasi evaluasi model kirkpatrick terhadap kualitas sistem pembelajaran Effendi M; Zainuddin Zainuddin; Muhammad Sabri Ahmad
Jurnal EDUCATIO: Jurnal Pendidikan Indonesia Vol 8, No 1 (2022): Jurnal EDUCATIO: Jurnal Pendidikan Indonesia
Publisher : Indonesian Institute for Counseling, Education and Therapy (IICET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/1202221160

Abstract

Penelitian ini bertujuan untuk mengetahui dan menganalisis persepsi mahasiswa UPBJJ-UT Ternate atas kualitas pembelajaran di Universitas Terbuka dengan evaluasi Kirkpatrick, dan pendekatan deskriptif kuantitatif dengan tujuan untuk mendiskripsikan objek penelitian ataupun hasil penelitian. Populasi dalam penelitian ini adalah Mahasiswa UPBJJ-UT. Teknik sampling yang digunakan adalah non probability sampling, dengan menggunakan metode proporsional random sampling. Dengan Jumlah sampel dalam penelitian ini adalah 232 mahasiswa yang teregistrasi pada tahun akademik 2020.1. Teknik pengumpulan data menggunakan angket. Dengan Analisis deskriptif kuantitaif. Hasil dari  penelitian menunjukkan bahwa Pada Reaction Level, mahasiswa menunjukkan tingkat kepuasan atas kesesuaian materi dengan modul/BMP dan pelayanan administrasi di UT, namun merasa perlu perbaikan pada feedback tutor, keaktifan tutor dalam forum diskusi (tutorial online) dan lemahnya koneksi jaringan internet utamanya di Bobong. Pada Learning Level, mahasiswa puas dengan relevansi materi dalam kehidupan sehari-hari. Namun mahasiswa merasa sulit mengakses informasi tentang UT di daerah kepulauan. Pada Behavior Level, mahasiswa merasa puas atas proses tutorial di UT baik TTM/Tuton maupun Tuweb, mahasiswa juga tidak ragu membagikan pengalaman tutorialnya kepada orang-orang disekitarnya. Namun yang masih perlu menjadi perhatian UPBJJ-UT Ternate yaitu sarana dan prasarana yang menunjang proses pembelajaran utamanya di daerah kepulauan seperti Bobong. Pada Result Level, mayoritas mahasiswa merasa pengetahuan maupun pengalaman mereka meningkat setelah mengikuti tutorial.
DEVELOPMENT OF A BUGIS LANGUAGE DICTIONARY APPLICATION WITH SM-KMP ALGORITHM FOR STUDENTS IN SOUTH SULAWESI Effendi M; Juhardi Juhardi; Muhammad Sabri Ahmad; Zainuddin Zainuddin
JIKO (Jurnal Informatika dan Komputer) Vol 8 No 1 (2025)
Publisher : Program Studi Teknik Informatika Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v8i1.8822

Abstract

The decline in the use of the Bugis language among younger generations in South Sulawesi poses a significant challenge in preserving local languages and cultures. One solution to this issue is developing a Bugis language dictionary application based on technology, which can interactively facilitate language learning. This study aims to develop a Bugis language dictionary application using the Knuth-Morris-Pratt (SM-KMP) algorithm to improve the efficiency of word searches within the dictionary. The research method involves application development with a prototype tested in South Sulawesi schools. This application is designed with features for fast and accurate word searches and interactive elements such as quizzes and educational games to enhance student motivation in learning the Bugis language. The results show that the application improved students' vocabulary comprehension by 85%, and 90% reported increased motivation to learn Bugis due to the interactive features. The application also supports preserving local culture by integrating character education that teaches ethical values and local wisdom in Bugis. In conclusion, this Bugis language dictionary application based on the SM-KMP algorithm is practical as an interactive learning tool. It holds significant potential in preserving the Bugis language and culture
AN LSTM-BASED APPROACH FOR INDONESIAN NEWS CATEGORIZATION: PERFORMANCE ANALYSIS OF HYPERPARAMETER TUNING AND PREPROCESSING Iwan La Udin; Firman Tempola; Abdul Mubarak; Muhammad Sabri Ahmad; Munazat Salmin; Saiful Do Abdullah
JIKO (Jurnal Informatika dan Komputer) Vol 8 No 3 (2025)
Publisher : Program Studi Teknik Informatika Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v8i3.10783

Abstract

News disseminated through internet-based systems or news portals is generally classified into specific categories, such as politics, sports, economy, entertainment, technology, health, and others. Currently, this categorization is performed manually, requiring a thorough reading of the entire news content. To address this inefficiency, an automatic classification system for Indonesian news articles is necessary to categorize them based on predetermined categories. This research employs a Natural Language Processing (NLP) approach and implements the Long Short-Term Memory (LSTM) architecture. The study was conducted using several testing scenarios, including (1) hyperparameter tuning of the learning rate to 0.01 and 0.001, (2) the application and omission of stemming, and (3) various dataset comparison ratios of 60:40, 70:30, 80:20, and 90:10. The evaluation utilized a dataset of 10,000 articles across 5 categories and was measured using accuracy, precision, recall, and f-measure metrics. From the three scenarios, seven training models were generated. The second model, with a learning rate of 0.001, without stemming, and a 90:10 dataset ratio, achieved the highest accuracy of 90.7%, with average precision, recall, and f-measure scores of 91%. The third and fourth models, which applied stemming, did not demonstrate a performance improvement, both yielding an accuracy of 89%. The fifth model, with a 60:40 dataset ratio, produced an accuracy of 90%, while the sixth and seventh models, with 70:30 and 80:20 ratios, resulted in accuracies of 79% and 88%, respectively.
Co-Authors Abdul Mubarak Effendi M. Iwan La Udin juhardi juhardi Munazat Salmin Saiful Do Abdullah Tempola, Firman Zainuddin Zainuddin