Measurement values using weight sensors are inherently contaminated by noise generated from electrical sources, thermal dynamics, mechanical vibration, and environmental conditions. In this paper, we present a method of correcting the accuracy of the sensors by using filtering algorithms. Two well-known methods in electrical engineering, namely, low-pass filtering and the Kalman algorithm, are applied to correct the real-time measured weight under various temperatures to determine moisture content during the food drying process. From an experiment using pineapples as the food material, the results showed the effectiveness of the application even if it has a simple design and is easy to implement. For small and medium enterprises (SMEs), the method and demonstration shown in this paper can be adopted and the proposed system is scalable for designing weight sensor systems operating in a thermal drying cabinet.