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All Journal Paradikma: Jurnal Pendidikan Matematika Jurnal Cendekia : Jurnal Pendidikan Matematika Archive: Jurnal Pengabdian Kepada Masyarakat Journal of Artificial Intelligence and Engineering Applications (JAIEA)
Yulita Molliq Rangkuti
Universitas Negeri Medan
Religion Agriculture, Biological Sciences & Forestry Automotive Engineering Computer Science & IT Control & Systems Engineering Education Mathematics Public Health Other

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Pengembangan Bahan Ajar Digital Berbasis RME untuk Meningkatkan Kemampuan Pemecahan Masalah Matematik dan Kemandirian Belajar Siswa SMP Gajah Mada Medan Kurnia Mildawati Gea; Yulita Molliq Rangkuti; Ani Minarni
Jurnal Cendekia : Jurnal Pendidikan Matematika Vol 6 No 2 (2022): Jurnal Cendekia: Jurnal Pendidikan Matematika Volume 6 Nomor 2 Tahun 2022
Publisher : Mathematics Education Study Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cendekia.v6i2.1602

Abstract

Tujuan penelitian ini adalah: 1) mendeskripsikan kevalidan, kepraktisan, dan keefektifan bahan ajar digital berbasis Realistic Mathematics Education (RME) yang dikembangkan untuk meningkatkan kemampuan pemecahan masalah matematik dan kemandirian belajar siswa; 2) meningkatkan kemampuan pemecahan masalah matematik dan kemandirian belajar siswa dengan menggunakan bahan ajar digital berbasis Realistic Mathematics Education (RME). Penelitian ini merupakan penelitian pengembangan. Model pengembangan yang digunakan dalam penelitian ini adalah model ADDIE dengan subjek penelitian 20 orang siswa kelas VIII-B dan 20 orang siswa kelas VIII-A di SMP Gajah Mada Medan. Objek dalam penelitian ini adalah bahan ajar digital berbasis Realistic Mathematics Education (RME) pada materi sistem persamaan linear dua variabel (SPLDV). Kevalidan bahan ajar digital yang dikembangkan ditinjau dari analisis hasil validitas bahan ajar digital oleh para validator dengan nilai rata-rata total sebesar 3,37 (kategori “valid”). Sementara itu, kepraktisan media pembelajaran dilihat dari skor observasi keterlaksanaan pembelajaran pada uji coba II yaitu sebesar 3,73 (kategori “terlaksana dengan baik”). Keefektifan bahan ajar digital ditinjau dari tiga aspek yaitu ketuntasan klasikal, skor angket kemandirian belajar, respon siswa, dan keterlibatan siswa dalam pembelajaran. Ketuntasan klasikal kemampuan pemecahan masalah matematis siswa pada uji coba II sebesar 90% (18 siswa). Berdasarkan indeks gain ternormalisasi, diperoleh bahwa pada uji coba II terjadi peningkatan kemampuan pemecahan masalah siswa sebesar 0,34 (kriteria “sedang”) dan peningkatan kemandirian belajar siswa sebesar 0,44 (kriteria “sedang”).
Pelatihan dan Pembimbingan Media Pembelajaran Berbasis Aplikasi Canva Sebagai Media Pembelajaran di Yayasan Pedidikan Nurul Hasaniah Yulita Molliq Rangkuti; Said Iskandar Al Idrus; Izwita Dewi; Nurliani Manurung; Insan Taufik; Ahmad Landong; Muhammad Noer Fadlan
Archive: Jurnal Pengabdian Kepada Masyarakat Vol. 3 No. 2 (2024): Juni 2024
Publisher : Asosiasi Pengelola Publikasi Ilmiah Perguruan Tinggi PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55506/arch.v3i2.112

Abstract

Proses pembelajaran sudah bertransformasi ke era digital 4.0. Materi pembelajaran digital diperlukan untuk meningkatkan kemampuan pemahaman dan aktivitas belajar siswa, ini merupakann urgensi sehingga kegiatan pengabdian masyarakat ini dilakukan. Tujuan adalah membuat meteri pembelajaran dengan aplikasi Canva dan pembuatan kuis interaktif mengunakan aplikasi Canva. Metode pelaksanaan dilakukan di Yayasan Pedidikan Nurul Hasaniah yang mempunyai level pendidikan dari SD hingga SMA. Kegiatan diawali dengan memberikan penjelasan pentingnya media pembelajaran, pengenalan media kuis interaktif, pengenalan canva dan implementasi pengelolaan media pembelajaran kuis interaktif. Hasil kegiatan ini menunjukkan bahwa: a) Hasil evaluasi proses melalui observasi selama kegiatan, pemahaman peserta sangat baik dan isi kegiatan dinilai baik, b) Evaluasi produk menunjukkan bahwa seluruh peserta terampil dalam membuat media Canva. c) Respon peserta pelatihan sangat positif, hal ini tercermin dari keaktifan peserta dalam menghadapi tantangan yang ada.
Development of Quantum Learning-Based Articulate Storyline Learning Media to Improve Students' Mathematical Communication Skills Mizta Dwi Hafizah Furqoni; Waminton Rajagukguk; Yulita Molliq Rangkuti
PARADIKMA: JURNAL PENDIDIKAN MATEMATIKA Vol 16, No 2 (2023): PARADIKMA JURNAL PENDIDIKAN MATEMATIKA (July - December 2023)
Publisher : Study Program of Mathematics Education of Unimed Postgraduate Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/paradikma.v16i2.48723

Abstract

The main purpose of this study is to describe the validity, practicality, and effectiveness of articulate storyline learning media based on quantum learning. This medium is specifically designed to improve students' mathematical communication skills. The research conducted is included in the development research category, with the ADDIE model as the chosen development model. The results showed that the learning media met the required validity criteria, which was shown from the analysis conducted by validators. In addition, the learning media proved to be practical, as observed during its implementation, and was considered effective in improving students' mathematical communication skills. This effectiveness is evidenced by the achievement of students' communication skills classically, and students are interested in learning media. In addition, the average N-Gain is in the medium category which indicates that the learning media is successful in improving students' mathematical communication skills.Keywords: Learning Media, Articulate Storyline, Quantum Learning, Mathematical Communication Skills
Eye Disease Classification System Based on Fundus Images Using the InceptionV3 Architecture Annisa Aulia; Hermawan Syahputra; Yulita Molliq Rangkuti; Insan Taufik; Kana Saputra S
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2263

Abstract

This study aims to develop an automated eye disease classification system based on retinal fundus images using the InceptionV3 deep learning architecture. The dataset consists of four classes: cataract, diabetic retinopathy, glaucoma, and normal, collected from public sources and clinical data. The proposed method applies several preprocessing techniques, including background segmentation, data augmentation, data normalization, and an 80:20 data split to improve model performance and generalization. Transfer learning is implemented by utilizing pretrained ImageNet weights and modifying the final layers to suit the classification task. The model is trained using the Adam optimizer with a learning rate of 0.001 and categorical cross-entropy loss function. Evaluation results show that the model achieves an accuracy of 96%, with average precision, recall, and F1-score values of 0.97, 0.96, and 0.97, respectively. The confusion matrix analysis indicates that most predictions are correctly classified, demonstrating strong performance across all classes. Furthermore, the model is successfully integrated into a web-based system that enables users to upload fundus images and obtain classification results automatically. These findings indicate that the proposed system can effectively assist in early detection of eye diseases and support clinical decision-making.
Co-Authors Ahmad Landong Ani Minarni Annisa Aulia Dewan Dinata Tarigan Hermawan Syahputra Ichwanul Muslim Karo Karo Insan Taufik Izwita Dewi Kana Saputra S Kurnia Mildawati Gea Mizta Dwi Hafizah Furqoni Muhammad Noer Fadlan Nurliani Manurung Said . Iskandar Wahyu Nur Fadillah Waminton Rajagukguk