Development of a Load Cell-Based System for LPG Consumption and Cost Estimation - Muhammad Ikhsan (Program Studi Teknik Elektro Fakultas Teknik Universitas Iskandarmuda Jl. Kampus Unida No.15, Surien, Kec. Meuraxa, Kota Banda Aceh, Aceh 23234 Propinsi Aceh, Indonesia, 2026)
Liquefied Petroleum Gas (LPG) is widely used in households and small-scale commercial activities due to its practicality and combustion efficiency. However, users often experience difficulties in accurately determining the remaining gas quantity and estimating the associated operational costs. This study proposes a load cell-based LPG monitoring system capable of measuring the remaining LPG mass and estimating gas consumption costs in real time. The proposed system integrates a load cell sensor, HX711 signal conditioning module, Arduino Uno microcontroller, DS1307 Real-Time Clock (RTC), LCD display, and user input interface. The monitoring algorithm calculates the remaining gas mass, gas percentage, and operational cost based on the observed rate of mass reduction over time. To improve measurement stability, a one-dimensional Kalman Filter is implemented to suppress sensor noise and short-term fluctuations. System validation was conducted through simulation using the Wokwi environment, where LPG consumption behavior was represented by predefined mass datasets with Gaussian noise characteristics of μ = 0 kg and σ = 0.001 kg. The simulation considered three consumption scenarios with rates of 0.15 kg/h, 0.25 kg/h, and 0.10 kg/h, corresponding to theoretical operational costs of 62.5 Rp/h, 104.2 Rp/h, and 41.7 Rp/h, respectively. The results demonstrate that the proposed system successfully tracks LPG mass variations and accurately identifies changes in consumption patterns. Furthermore, the Kalman Filter effectively reduces measurement fluctuations while maintaining responsiveness to actual load variations, resulting in smoother and more reliable cost estimation. The proposed monitoring approach provides a practical solution for real-time LPG consumption monitoring and operational cost awareness, particularly for household and small-business applications.