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All Journal REiD (Research and Evaluation in Education) Jurnal Ilmiah FIFO JSAI (Journal Scientific and Applied Informatics)
Sulis Sandiwarno
Program Studi Sistem Informasi, Fakultas Ilmu Komputer, Universitas Mercu Buana
Computer Science & IT Education

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PERANCANGAN MODEL E-LEARNING BERBASIS COLLABORATIVE VIDEO CONFERENCE LEARNING GUNA MENDAPATKAN HASIL PEMBELAJARAN YANG EFEKTIF DAN EFISIEN Sulis Sandiwarno
Jurnal Ilmiah FIFO Vol 8, No 2 (2016)
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Pemanfaatan Teknologi Informasi saat ini sangatlah berkembang dengan pesat, dengan adanya Teknologi Informasi ini dapat membantu sseluruh aktifitas dan dapat menghasilkan laporan dengan cepat dan baik. Pemanfaatan Teknologi Informasi ini berperan penting juga dalam tingkat pendidikan, seperti yang kita ketahui adalah e-learning. Dengan adanya e-learning seluruh aktifitas pembelajaran dapat mudah untuk dilakukan. Dalam penelitian ini akan membahas mengenai e-learning dengan harapan dan tujuan seluruh proses pembelajaran dapat dengan mudah dilakukan oleh pengajar maupun siswa yang berada dalam lingkup proses pembelajaran. Metode yang akan dilakukan untuk mengukur tingkat kepuasaan penggunaan e-learning ini adalah dengan dengan menggunakan Collaborative Learning berbasis TAM (Technology Acceptance Model) dan Naives Bayes Classification (NBC). Diharapkan dengan adanya perancangan teknologi e-learning berbasis video conference ini seluruh proses pembelajaran menjadi efektif dan efisien
Empirical lecturers’ and students’ satisfaction assessment in e-learning systems based on the usage metrics Sulis Sandiwarno
REID (Research and Evaluation in Education) Vol 7, No 2 (2021)
Publisher : Sekolah Pascasarjana Universitas Negeri Yogyakarta & HEPI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/reid.v7i2.39642

Abstract

Nowadays, in the pandemic of COVID-19, e-learning systems have been widely used to facilitate teaching and learning processes between lecturers and students. Assessing lecturers’ and students’ satisfaction with e-learning systems has become essential in improving the quality of education for higher learning institutions. Most existing approaches have attempted to assess users’ satisfaction based on System Usability Scale (SUS). On the other hand, different studies proposed usage-based metrics (completion rate, task duration, and mouse or cursor distance) which assess users’ satisfaction based on how they use and interact with the system. However, the cursor or mouse distance metric does not consider the effectiveness of navigation in e-learning systems, and such approaches measure either lecturers’ or students’ satisfaction independently. Towards this end, we propose a lostness metric to replace the click or cursor distance metric for assessing lecturers’ and students’ satisfaction with using e-learning systems. Furthermore, to obtain a deep analysis of users’ satisfaction, we tandem the usage-based metric (i.e., completion rate, task duration, and lostness) and the SUS metric. The evaluation results indicate that the proposed approach can precisely predict users’ satisfaction with e-learning systems.
Model Sequential Resnet50 Untuk Pengenalan Tulisan Tangan Aksara Arab Sarwati Rahayu; Sulis Sandiwarno; Erwin Dwika Putra; Marissa Utami; Hadiguna Setiawan
JSAI (Journal Scientific and Applied Informatics) Vol 6 No 2 (2023): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v6i2.5379

Abstract

Research for Arabic handwriting recognition is still limited. The number of public datasets regarding Arabic script is still limited for this type of public dataset. Therefore, each study usually uses its dataset to conduct research. However, recently public datasets have become available and become research opportunities to compare methods with the same dataset. This study aimed to determine the implementation of the transfer learning model with the best accuracy for handwriting recognition in Arabic script. The results of the experiment using ResNet50 are as follows: training accuracy is 91.63%, validation accuracy is 91.82%, and the testing accuracy is 95.03%.
Komparasi Hasil Color Feature Extraction HSV, LAB dan YCrCb pda Algoritma SVM untuk Klasifikasi Spesies Burung Sarwati Rahayu; Andi Nugroho; Erwin Dwika Putra; Mariana Purba; Hadiguna Setiawan; Sulis Sandiwarno
JSAI (Journal Scientific and Applied Informatics) Vol 6 No 3 (2023): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v6i3.5920

Abstract

The classification of bird species is a problem often faced by ornithologists, and has been considered scientific research since antiquity. This study aims to evaluate the results of color feature extraction including HSV, LAB and YCrCb against the results of the SVM classification. In addition, the results of this study are useful to determine the performance of color feature extraction that is suitable for bird species classification. The dataset used was 22,617 bird species images. Based on experimental results, the effect of HSV on the SVM classification caused a decrease in accuracy by -0.33% while LAB and YCrCb on the SVM classification caused an increase in accuracy of 0.44% and 0.21%. However, the accuracy of the SVM classification does not yet have good performance so that further research will be carried out using other classifications, including convolutional neural networks and others.
Co-Authors Andi Nugroho Hadiguna Setiawan Hadiguna Setiawan Mariana Purba Putra, Erwin Dwika Sarwati Rahayu