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All Journal JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) EXPLORER
Suriati Suriati
Universitas Harapan Medan, Medan
Computer Science & IT Decision Sciences, Operations Research & Management

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Pengelompokkan Tingkat Pemahaman Guru PAUD Terhadap Pembelajaran Berbasis STEAM Menggunakan Metode X-Means Clustering Siti Fatimah; Suriati Suriati; Ari Usman
Explorer Vol 2 No 1 (2022): Januari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (353.325 KB) | DOI: 10.47065/explorer.v2i1.139

Abstract

In the era of the industrial revolution 4.0, quantity is not a measure of achieving early childhood outcomes, but how teachers create quality resource based inventions. To form creative and adaptive resources for technology, the teacher must changes the facilities, infrastructure and learning reconstruction. Learning that is prepared to welcome children to face the 21st century is learning based on Science, Technology, Engineering, Art, and Mathematics (STEAM). STEAM is used to consider the interconnected essence of science, technology, engineering, arts and mathematics disciplines and their significance in the long-term academic performance of children. Responding to STEAM-based learning that PAUD teachers need to incorporate in cultivating the creativity of children, it is important to know the degree to which PAUD teachers understand STEAM-based learning. This research discusses the use of the X-Means clustering algorithm as one of the data mining algorithms in grouping data on the level of comprehensions of PAUD teachers on STEAM-based learning. This research discusses the use of the X-Means Clustering algorithm as one of the data mining algorithms in grouping data on the level of comprehensions of PAUD teachers on STEAM-based learning.
Analisis Perbandingan Akurasi Pre-Trained Convolutional Neural Network Untuk Klasifikasi Kelompok Usia Pengunjung Rumah Sakit Arnes Sembiring; Sayuti Rahman; Dodi Siregar; Muhammad Zen; Suriati Suriati
Journal of Information System Research (JOSH) Vol 4 No 2 (2023): January 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v4i2.2913

Abstract

Children are not allowed to visit the hospital. Children should not visit the hospital for two reasons, namely the patient's side and the child's side. On the patient's side, patients need peace of mind during treatment and recovery. The noise generated by children makes the atmosphere not conducive and increases the patient's stress level. On the child's side, there are two factors, namely immunity, and trauma. Children have incomplete immunity so they are easily infected by viruses and bacteria. A child's immune disorder will harm the child's development. Apart from viruses and bacteria, in hospitals, there are also patients with major injuries such as those resulting from accidents. Children who see these large wounds can traumatize themselves and interfere with the child's growth and development. The age classification of visitors supports for hospital management to limit visitors based on age. Visitors categorized as children are visitors aged 12 years or younger. The method used for age group classification is the pre-trained CNN, including Alexnet, VGGNet, GoogleNet, ResNet, and AqueezeNet. We conducted a preliminary study using the All-Age-Faces (AAF) dataset as test data that represents the age of hospital visitors. The dataset is divided into two classes, namely children and adults. Based on the SqueezeNet test, it is a better method in terms of training accuracy and validation. Based on the order of accuracy validation, SqueezeNet succeeded in recognizing age groups with an accuracy of 93.09%, VGGNet 92.72%, AlexNet 91.44%, GoogleNet 90.92%, and ResNet 90.62%. This research is expected to contribute to helping control visitors to the hospital.
Co-Authors Ari Usman Arnes Sembiring Dodi Siregar Muhammad Zen Rahman, Sayuti Siti Fatimah