Pengaruh Hybrid Learning dengan Menggunakan Chatbot Berbasis AI terhadap Hasil Belajar Siswa pada Mata Pelajaran Jaringan Komputer dan Telekomunikasi - Rohmayanti Rohmayanti; Popi Dayurni; Adei Fricticarani (Intitut Agama Islam Nasional Laa Roiba Bogor, 2025)
This research is motivated by the relatively low learning outcomes of students in the Computer Networks and Telecommunications subject. Furthermore, low exam scores and low student engagement during the learning process are also contributing factors. This study aims to determine the effect of hybrid learning using an AI-based chatbot on improving student learning outcomes in the Computer Networks and Telecommunications subject and to determine the extent of this effect. This study employed a quantitative method, analyzing the data obtained using statistical formulas to draw conclusions. This study employed a correlational research design. Correlational research designs are able to identify relationships between independent variables and the dependent variable and determine the extent to which the independent variable can predict the dependent variable. The results of this study indicate that the use of hybrid learning using an AI-based chatbot has a positive impact on student learning outcomes in the Computer Networks and Telecommunications subject. This is demonstrated by simple linear regression analysis with a significance value (Sig.) of 0.000, less than <0.05. Therefore, it can be concluded that H0 is rejected and Ha is accepted. The use of hybrid learning using AI-based chatbots has an impact on improving student learning outcomes in the subject of computer networks and telecommunications, with the RSquare value of 0.660. This value indicates that the impact of hybrid learning using AI-based chatbots (X) on improving student learning outcomes in the subject of computer networks and telecommunications (Y) is 66%, while 34% of cognitive development is influenced by other variables not examined. The interpretation of the coefficient of determination (R2) shows that the value of 66% is considered strong.