E-learning telah menjadi tulang punggung bagi pendidikan jarak jauh di dunia khususnya dimasa pandemi Covid-19 dan masa New Normal. Hampir seluruh dunia pendidikan saat ini telah menerapkan e-learning dalam kegiatan pembelajaran. Tanpa memiliki keterampilan dasar dan pengetahuan tentang literasi digital seperti video pembelajaran maka proses pembelajaran akan menjadi tertinggal. Techonological Pedagogical Content Knowledge (TPACK) saat ini telah menjadi kompetensi yang harus dimiliki oleh guru di era globalisasi. Hasil observasi terhadap guru tingkat SMA/MA di Kabupaten Balangan menunjukkan bahwa guru belum mampu membuat video pembelajaran untuk mereka gunakan dalam pembelajaran daring, para guru umumnya menggunakan video pembelajaran yang telah ada dari beberapa sumber online untuk digunakan sebagai media untuk menjelaskan materi. Salah satu upaya yang dapat dilakukan untuk membantu guru mengatasi kendala dalam membuat video pembelajaran adalah dengan mengadakan kegiatan pelatihan dan pendampingan pengembangan video pembelajaran. Pelaksanaan kegiatan penerapan PKM ini dibagi dalam tiga tahap yaitu tahap persiapan program, implementasi progam dan evaluasi program. Setelah kegiatan ini terlihat bahwa guru sudah mampu mengoperasikan aplikasi Camtasia dan Olive dengan baik dan terstruktur meliputi cara penginstallan, memasukkan bahan ajar, editing, dan export/menyimpan video. Kegiatan pelatihan video pembelajaran menggunakan camtasia dan olive untuk optimasi pembelajaran daring ini diharapkan dapat meningkatkan skill/keterampilan guru dalam pembuatan video pembelajaran.
E-learning is an educational system that uses information technology in the learning process. One of the platforms that can be used in developing e-learning is Moodle. This research investigates the implementation of e-learning in the learning process in the Computer Education Department. The purpose of this research is to examine the use of E-learning in supporting the learning process. The respondents of this research are 130 active students of the Computer Education Department from the 2016 to 2018 Batches. The method used is a research questionnaire whose data are analyzed using the SPSS Statistics 25 program. This research shows no significant effect of student expectation on e-learning in supporting the learning process. Meanwhile, ease of e-learning, e-learning performance, and social influence for the benefit of e-learning have a significant effect on supporting the learning process and improve learning independence.
Peningkatan kualitas pembelajaran banyak ditentukan oleh pembelajaran yang dirancang dan dilaksanakan oleh guru. Guru sebagai ujung tombak dalam pelaksanan pendidikan merupakan pihak yang sangat berpengaruh dalam proses pembelajaran. Kegiatan belajar mengajar mengandung sejumlah komponen. Salah satu komponen yang mendukung pembelajaran terlaksana dengan baik adalah media pembelajaran. Media pembelajaran sebagai perantara antara pengajar dan peserta untuk memahami pembelajaran lebih efektif dan efisien. Hasil wawancara bersama guru pengajar di SMAN 8 Banjarmasin selama pandemi Covid-19, dalam pelaksanaan pembelajaran secara online peserta didik masih kesulitan dalam memahami materi karena peserta didik dituntut untuk belajar secara mandiri di rumah. Media pembelajaran dapat dikembangkan dengan aplikasi canva yang dapat diterapkan dalam pembelajaran daring. Metode atau pendekatan yang digunakan dalam kegiatan program PKM meliputi pelatihan pengembangan tentang media pembelajaran menggunakan canva untuk guru-guru yang meliputi memberikan penjelasan tentang aplikasi canva, mengenalkan pengembangan media pembelajaran menggunakan canva, diskusi dan pertukaran informasi. Hasil evaluasi menunjukkan bahwa guru sebagai peserta pelatihan telah berupaya aktif memahami konsep dan implementasi penggunaan aplikasi canva dalam pengemban media pembelajaran. Respon peserta pembuatan media pembelajaran menggunakan canva untuk seluruh komponen evaluasi memberikan respon sangat positif. Berdasarkan hasil palatihan pembuatan media pembelajaran menarik menggunakan canva untuk optimalisasi pembelajaran daring bagi guru SMA Negeri 8 Banjarmasin diperoleh simpulan pelatihan dapat meningkatkan pemahaman guru dan kemampuan guru dalam mengembuat media pemembelajaran online menggunakan canva melalui keterlibatan secara aktif dalam mendengarkan penjelasan tim pemateri, membaca materi pelatihan, mengajukan pertanyaan, menyatakan pendapat, berpartisipasi dalam membuat media pembelajaran online selama kegiatan.
After the pandemic, people began to adjust to the changes during the pandemic. The rapid progress and development of information and technology are now entering the world of education. Information technology has begun to be widely used to support the smooth running of the teaching and learning process, one of which is to support student learning outcomes. This study aimed to determine the differences in student learning outcomes in the control and experimental classes by considering students' learning motivation. This type of research is an experimental study with a 2×2 factorial design. Discrete mathematics learning outcomes for even-semester students in 2021/2022 will be grouped based on learning media (PowerPoint and Kahoot) and student motivation (high and low). To find out the differences in student learning outcomes, a 2-way ANOVA test was carried out using SPSS. The results of this study show significant differences in student learning outcomes between students with high learning motivation and those with low learning motivation. There is no significant difference in learning outcomes between Kahoot learning media and PowerPoint learning media. Then it is known that other factors affect student concentration; namely, an interaction between learning media and learning motivation influences students' learning outcomes. The Kahoot media was proven to make the learning atmosphere more fun during the learning activities. Students were more active in participating in the learning process.
Wetlands are habitats commonly used for fish cultivation. South Kalimantan is one of the provinces that has a wetland area, which is 11,707,400ha, there are 67 rivers and an estimated 200 species of fish. This shows the abundant wealth of fish treasures and economic value. The study of fish identification is an important subject for the preservation of wetland fish. In the field of artificial intelligence, identification can be done using Machine Learning (ML). There are many libraries, a collection of functions that can be used in ML development, one of which is Tensorflow. In this paper, we survey a variety of literature on the use of Tensorflow, as well as datasets, algorithms, and methods that can be used in developing wetland area fish image identification applications.The results of the literature survey show that Tensorflow can be used for the development of fish character identification applications. There are many datasets that can be used such as MNIST, Oxford-I7, Oxford-102, LHI-Animal-Faces, Taiwan marine fish, KTH-Animal, NASNet, ResNet, and MobileNet. Classification methods that can be used to classify fish images include CNN, R-CNN, DCNN, Fast R-CNN, kNN, PNN, Faster R-CNN, SVM, LR, RF, PCA and KFA. Tensorflow provides many models that can be used for image classification, including Inception-v3 and MobileNets, and supports models such as CNN, RNN, RBM, and DBN. To speed up the classification process, image dimensions can be reduced using the MDS, LLE, Isomap, and SE algorithms.
Speech impaired is the inability of someone to speak, even though speaking ability is important in order to communicate with other people. Dealing with this as someone who has speech impairments has their own way of communicating, namely by using sign language, but not everyone understands the sign language. The MFCC and Backpropagation ANN methods are implemented on a Single Board Computer (SBC) designed to overcome speech impaired communication problems. The MFCC method is used to retrieve the features of speech impairment and the Backpropagation ANN is used for sound pattern recognition.The system was trained using 750 sound samples consisting of 5 speakers, each uttering as many as 30 repetitions of the pronunciation of words (makan, kamar, kerja, harga and lapar), then tested using 125 sound samples consisting of 5 speakers, each saying 5 repetitions of words. Training and testing of Backpropagation ANN using input coefficients generated from MFCC. The results showed that the MFCC and Backpropagation ANN methods were able to identify speech words with 60% accuracy, 40% precision and 40% sensitivity.
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