Implementasi Support Vector Machine untuk Kendali Lampu Ruangan - Adam, Chairul; Hidayati, Rahmi; Suhardi, Suhardi (Universitas Budi Darma, 2024)
The use of lights in daily activities is a necessity for everyone. Lights are useful as lighting when the room has minimal light, so lights are needed in the room in the house. If there are many rooms in a house, there are also many lights used. Often users forget to turn on and off the lights in each room if done manually. An automatic control is needed to make it easier for users to turn on and off lights according to user habits. Support Vector Machine is used in this in this study to classify the condition of lights based on user habits when turning on and off the lights. User habit data used for 15 days with a total of 620 data. Testing was carried out for 3 days with a total of 72 data. The results of system testing obtained the accuracy value of kitchen lights by 87.50%, accuracy of main room lights by 95.83%, accuracy of second room lights by 91.67%, accuracy of living room lights by 95.83%, accuracy of terrace lights by 95.83%, and accuracy of toilet lights by 94.44%.