This study aimed to develop learning tools based on E-Learning in introductory information technology course. E-Learning, a web-based learning tool that uses classroom flipped learning models. The method used in this research was Analysis, Design, Development, Implementation, and Evaluation (ADDIE) with processed data sourced from 22 students. The effectiveness of this study was very effective because through the calculation of the Gain score it was found that the overall average value of students there was an improvement. The average increase in learning outcomes was 0.591949 with a moderate gain score acquisition criteria. Then, it was concluded that e-learning using the flipped classroom learning model was very helpful in introducing Infor-mation Technology and as an E-Learning guideline for other subjects.
Dental caries is tooth decay caused by bacterial infections. It is commonly known as cavities. This infection causes demineralization and hence destruction of the teeth. Diagnosis of dental caries is conventionally facilitated with radiographical films. This research aims to develop some algorithm of the mMG method in identifying dental caries based using digital panoramic dental x-ray images. This paper presents an algorithm of using digital panoramic dental x-ray images to detect dental caries. Type of algorithm used in this study is normal mMG, Enhancement mMG, and Smooth mMG. This study makes use of MATLAB and it performs dental caries detection in three algorithms. A dataset of 225 digital panoramic dental x-ray images in .png format is used to edge detection of the object in dental. The results are helpful to identify such caries from the tooth.
This study aims to present diagnose of melanoma skin cancer at an early stage. It applies feature extraction method of the first order for feature extraction based on texture in order to get high degree of accuracy with method of classification using artificial neural network (ANN). The method used is training and testing phases with classification of Multilayer Perceptron (MLP) neural network. The results showed that the accuracy of test image with 4 sets of training for image not suspected of melanoma and melanoma with the lowest accuracy of 80% and the highest accuracy of 88.88%, respectively. The 4 sets of training used consisted of 23 images. Of the 23 images used as a training consisted of 6 as not suspected of melanoma images and 17 as suspected melanoma images.
Penjualan merupakan sumber hidup suatu perusahaan. Memprediksi jumlah penjualan merupakan hal penting dalam menganalisis perkembangan penjualan. Analisis perkembangan penjualan ini merupakan faktor penting dalam meningkatkan penjualan. Dengan menggunakan metode Monte Carlo dapat memprediksi ketepatan terhadap data barang pada perusahaan. Hasil penelitian ini terhadap pengolahan data tahun 2016 hingga tahun 2017 memiliki akurasi 97%. Sehingga penelitian ini sangat tepat dalam memprediksi penjualan untuk masa yang akan datang.
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