<![CDATA[The demand for electrical energy in the education sector continues to increase along with the growing use of electrical equipment, laboratories, and academic activities. Politeknik Negeri Medan, as a vocational education institution, has relatively high electrical energy consumption; therefore, a more efficient and environmentally friendly alternative energy source is required. This study aims to analyze and optimize a rooftop Solar Power Plant (SPP) system using MATLAB based on building load profiles and solar irradiance intensity in Medan City. The research method was carried out through the collection of building electrical load profile data, solar irradiance data, and rooftop area measurements. Simulation and optimization of the rooftop photovoltaic system were conducted using MATLAB to analyze system capacity, number of solar panels, energy performance, system efficiency, solar panel distribution, and potential electrical energy savings. The results showed that the total electrical energy demand of the Politeknik Negeri Medan building was 5,410 kWh/day with a total installed power of 1,352.57 kW. Based on the simulation results, the optimum photovoltaic system capacity was 1,516.25 kWp with 2,757 solar panels of 550 Wp capacity each. The photovoltaic system was able to generate relatively stable electrical energy throughout the year, with solar irradiance having a significant influence on the system output energy. The analysis also showed that the effective rooftop area of 11,601.61 m² was sufficient for solar panel installation requiring an area of 8,491 m². In addition, the photovoltaic system has the potential to reduce electricity costs by approximately IDR 2.81 billion per year. This study demonstrates that the implementation of a rooftop photovoltaic system using MATLAB at Politeknik Negeri Medan is feasible from technical, economic, and environmental perspectives. The use of MATLAB improves the quality of photovoltaic system analysis through detailed and systematic energy performance simulations and solar panel configuration optimization]]>
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