The increasing prevalence of non-communicable diseases such as obesity and diabetes mellitus has become a major public health concern in Indonesia. Uncontrolled food consumption is one of the primary contributing factors to these issues. Therefore, a system is needed to help individuals monitor their calorie intake more effectively. This study aims to develop a food calorie detection system using the Single Shot Multibox Detector (SSD) method. The model is applied to identify and classify food objects with high accuracy. Calorie estimation is performed based on predefined fixed portion rules. The results indicate that the developed system can recognize various types of food in real-time with optimal performance. The implementation of this system is expected to raise public awareness of healthy eating habits and support efforts to prevent non-communicable diseases in Indonesia.