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
Pandemi Covid-19 membawa dampak besar di dunia pendidikan. Kebijakan Pemerintah untuk melaksankan Pembelajaran Jarak Jauh (PJJ) berdampak pada pembelajaran di Sekolah. Peningkatan kompetensi TIK sangat diperlukan untuk mendukung kelancaran PJJ. Salah satunya dengan kegiatan bimbingan TIK dimasa Pandemi Covid-19. SMP Negeri 1 Lengayang melaksanakan kegiatan bimbingan TIK secara daring dan tatap muka langsung di masa Pandemi Covid-19. Namun hasil belajar siswa dalam pembelajaran daring dan tatap muka langsung belum menunjukkan hasil yang maksimal. Berbagai kendala muncul sehingga mempengaruhi hasil belajar siswa. Guru kesulitan untuk mengukur tingkat pemahaman siswa terhadap bimbingan TIK. Prediksi tingkat pemahaman siswa penting dilakukan sebagai tolak ukur keberhasilan pembelajaran di masa Pandemi Covid-19. Penelitian ini bertujuan untuk memprediksi tingkat pemahaman siswa dalam pembelajaran daring dan tatap muka langsung dimasa pademi covid-19, sehingga dapat pula membantu pihak sekolah untuk mengambil kebijakan yang tepat untuk meningkatkan kualitas pembelajaran untuk kedepannya. Penelitian ini menggunakan Jaringan Syaraf Tiruan (JST) metode Backpropagation. JST merupakan bagian dari kecerdasan buatan yang dapat digunakan untuk memprediksi. Data yang dikelola adalah rekap nilai hasil belajar koginitif siswa pada saat bimbingan TIK dalam pembelajaran daring dan tatap muka langsung dimasa Pandemi Covid-19. Hasil dari perhitungan dengan metode Backpropagation dengan aplikasi Matlab menghasilkan nilai persentase tingkat pemahaman siswa, sehingga diperoleh nilai akurasi dalam prediksi. Dengan hasil pengujian akurasi prediksi tingkat pemahaman secara daring dan tatap muka langsung dengan pola 3-10-1 didapatkan nilai akurasi terbaik mencapai 95 %. Hasil prediksi dapat mengkur tingkat pemahaman belajar siswa dimasa Pandemi Covid 19 terhadap bimbingan TIK.
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