Abstract
The Covid-19 pandemic has a major impact on the world of education. Government policies to implement Distance Learning (PJJ) have an impact on learning in schools. Increasing ICT competence is needed to support the smooth running of PJJ. One of them is through ICT guidance activities during the Covid-19 Pandemic. SMP Negeri 1 Lengayang carried out online and face-to-face ICT guidance activities during the Covid-19 Pandemic. However, student learning outcomes in online and face-to-face learning have not shown maximum results. Various obstacles arise that affect student learning outcomes. Teachers have difficulty measuring the level of students' understanding of ICT guidance. Predicting the level of understanding of students is important as a measure of learning success during the Covid-19 Pandemic. This study aims to predict the level of understanding of students in online and face-to-face learning during the Covid-19 period, so that it can also help schools to take the right policies to improve the quality of learning for the future. This study uses the Backpropagation method of Artificial Neural Network (ANN). ANN is a part of artificial intelligence that can be used to predict. The data that is managed is a recap of the value of student cognitive learning outcomes during ICT guidance in online and face-to-face learning during the Covid-19 Pandemic. The results of calculations using the Backpropagation method with the Matlab application produce a percentage value for the level of student understanding, so that the accuracy value in prediction is obtained. With the results of testing the predictive accuracy of the level of understanding online and face-to-face with the 3-10-1 pattern, the best accuracy value is 95%. The prediction results can measure the level of students' understanding of learning during the Covid 19 Pandemic towards ICT guidance.
Highlights
The Covid-19 pandemic has a major impact on the world of education
This study aims to predict the level of understanding of students in online and face-to-face learning during the Covid-19 period, so that it can also help schools to take the right policies to improve the quality of learning for the future
Seminar Nasional Mahasiswa Ilmu Komputer dan Aplikasinya (SENAMIKA)
Summary
Teknologi Informasi dan Komunikasi (TIK) secara luas diartikan sebagai segala kegiatan yang berkaitan dengan pemprosesan, manipulasi, pengelolaan, serta pemindahan informasi antar media [1]. TIK dalam pembelajaran dilakukan secara daring dan tatap muka Sumber data yang digunakan pada penelitian ini adalah langsung. Agar penelitian ini lebih terarah, maka dibuat pemahaman hasil belajar siswa, agar satuan pendidikan rumusan masalah dan batasan masalah yaitu dapat mengambil kebijakan yang tepat untuk bagaimanakah metode backpropagation mampu meningkatkan kualitas pembelajaran dimasa yang akan melakukan prediksi tingkat pemahaman belajar siswa datang. Pada penelitian ini menggunakan Jaringan Syaraf Tiruan (JST) metode Backpropagation, untuk memprediksi hasil tingkat pemahaman siswa dalam pembelajaran dimasa pandemi Covid-19. Dengan menerapkan metode Backpropagation diharapkan mampu memprediksi tingkat pemahaman siswa terhadap bimbingan TIK sehingga dapat dijadikan sebagai tolak ukur keberhasilan pembelajaran dan membantu sekolah untuk mengambil kebijakan yang tepat guna meningkatkan kualitas pembelajaran di masa yang akan datang. TIK.Backpropagation merupakan metode pada JST yang banyak digunakan dalam memprediksi atau peramalan. Backpropagation NeuralNetwork (BPNN) [14]
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