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All Journal IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature Universa Medicina TAKSONOMI
Hendrawan, Kevin
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Education Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Medicine & Pharmacology Public Health

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Classification of diabetic retinopathy using ensemble convolutional neural network architectures Hendrawan, Kevin; Handayani, Ariesanti Tri; Andayani, Ari; Titiek, Ernawati; Gumelar, Agustinus Bimo
Universa Medicina Vol. 43 No. 2 (2024)
Publisher : Faculty of Medicine, Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18051/UnivMed.2024.v43.188-194

Abstract

Background Diabetic retinopathy (DR) constitutes a primary cause of blindness across all age groups. Ophthalmologists examine fundus images (FI) to detect and classify stages of DR. Development of deep learning can help clinicians to attain a larger volume in screening and diagnosing diabetic retinopathy, thereby decreasing the burden of visual impairment caused by DR. This study aimed to classify DR using ensemble convolutional neural networks (CNN) architectures. Methods We used data from the Indian Diabetic Retinopathy Image Dataset which consist of typical diabetic retinopathy lesions at pixel level. The dataset contains typical diabetic retinopathy structures as well as normal retinal structures and is divided into three parts: segmentation, classification, and location. There are 516 original color fundus images in the classification used as training set (413 images) and testing set (103 images). We used ensemble CNN architectures to classify diabetic retinopathy as no DR, mild non-proliferative DR (NPDR), moderate NPDR, severe NPDR and proliferative DR (PDR) based on fundus image. Results In this study we successfully created a model with ensemble CNNs to detect DR based on fundus images with area-under-the-curve, sensitivity, and specificity of 0.88, 0.89, and 0.90, respectively, which is on par with the most modern methods. Conclusion Based on the results, this model performs quite well in early detection of diabetic retinopathy and can be used to develop a more accurate model for detecting and classifying diabetic retinopathy. This model can also be used in assisting mass screening at lower cost without reducing diagnostic effectiveness.
Analisis Perspektif Mahasiswa Non Jurusan Bahasa Inggris dalam Penggunaan “Duolingo” sebagai Alat Pembelajaran Bahasa Inggris Astiantih, Susi; Haeniah, Nurul; Hendrawan, Kevin
TAKSONOMI: Jurnal Penelitian Pendidikan Dasar Vol. 4 No. 3 (2024): Taksonomi Jurnal Penelitian Pendidikan Dasar
Publisher : Program Studi Pendidikan Guru Sekolah Dasar Universitas Muhammadiyah Buton

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Abstract

Duolingo adalah platform pembelajaran bahasa populer yang telah mendapatkan daya tarik signifikan. Desainnya berfokus pada penguasaan bahasa yang lebih mudah diakses, menarik, dan efektif melalui gamifikasi dan pembelajaran yang dipersonalisasi. Tujuan penelitian ini adalah untuk menganalisis persepsi mahasiswa terhadap Duolingo sebagai alat pembelajaran untuk meningkatkan motivasi belajar mahasiswa dalam pembelajaran bahasa Inggris. Subyek dalam penelitian ini adalah mahasiswa jurusan non bahasa inggris yang berjumlah 20 orang. Teknik pengumpulannya menggunakan angket, wawancara, dan dokumentasi. Kuesioner diberikan untuk mengetahui persepsi mahasiswa dan wawancara dilakukan untuk mengetahui jawaban lebih mendalam sehingga peneliti dapat mendeskripsikan dan mempelajari secara maksimal persepsi mahasiswa terhadap aplikasi Duolingo sebagai alat evaluasi. Sedangkan dokumentasi untuk mengumpulkan dan menyimpan informasi tentang data mahasiswa. Hasil penelitian ini menunjukkan bahwa 91,25% mahasiswa tertarik menggunakan aplikasi Duolingo sebagai alat pembelajaran dikarenakan penggunaan yang mudah, tampilan yang menarik, dan pertanyaan yang bervariasi yang membuat mahasiswa ingin menggunakan Duolingo sebagai untuk meningkatkan motivasi belajar siswa.
Integration of Virtual Reality and Digital Game-Based Learning in Education: Accelerating English Language Communication Pratiwi, Alifiah; Reskiawan, Bimas; Suryadi, Ray; Andas, Netty Huzniati; Hendrawan, Kevin
IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature Vol. 13 No. 2 (2025): IDEAS: Journal on English Language Teaching and Learning, Linguistics and Lite
Publisher : Institut Agama Islam Negeri Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24256/ideas.v13i2.8030

Abstract

This study was initiated in response to the challenges faced by students who are not accustomed to practicing English speaking due to a lack of self-confidence and heightened anxiety when communicating with others or with native speakers. To address these issues, the study explores the potential of Virtual Reality (VR) technology to foster the development of students’ English communication skills within an autonomous, interactive, and engaging environment. Such an environment is expected to increase students’ learning motivation while simultaneously improving the overall quality of instruction. The primary aim of this research is to contribute to the body of knowledge by developing a prototype of a digital platform termed Metaversity, defined as a virtual learning environment that integrates the immersive features of the Metaverse ecosystem with the pedagogical foundations of Digital Game-Based Learning (DGBL). The participants of the study consisted of 30 undergraduate students from Universitas Sembilanbelas November Kolaka. Employing a Research and Development (R&D) approach, the study adopted the ADDIE model, which includes five stages: Analysis, Design, Development, Implementation, and Evaluation. The resulting learning media integrates VR, DGBL, and communication platforms such as VRChat and Discord into a cohesive system. Validation by media experts yielded an average score of 4.35 out of 5, which falls into the “highly feasible” category. Meanwhile, students’ responses reached an average of 82.5%, placing the product within the “good–very good” range. The findings provide compelling evidence that the developed medium is effective in enhancing students’ motivation, self-confidence, and English-speaking competence. Furthermore, the integration of VR and DGBL fosters active engagement, alleviates language anxiety, and creates an immersive and enjoyable learning experience. These outcomes highlight the potential of Metaversity-based platforms as innovative solutions in higher education language learning contexts.
Co-Authors Agustinus Bimo Gumelar Ari Andayani Ariesanti Tri Handayani, Ariesanti Tri Astiantih, Susi Haeniah, Nurul Netty Huzniati Andas, Netty Huzniati Pratiwi, Alifiah Ray Suryadi, Ray Reskiawan, Bimas - Titiek, Ernawati