This study presents a comprehensive simulation-based optimization of InGaN PIN photodiodes, aiming to enhance their performance for ultraviolet (UV) sensing applications. Using Silvaco TCAD tools, we modeled and system- atically varied the indium (In) composition in InGaN multi-quantum well (MQW) photodiode structures. Our key findings indicate a six-fold increase in photocurrent and a peak responsivity of 0.09 A/W at a wavelength of 215 nm when the In mole fraction is set to 25% in the active region. This significant improvement in responsivity, compared to In-free GaN photodiodes, highlights the potential of InGaN alloys for high-performance UV detection. The analysis also delves into design trade-offs related to defect density and reflection losses that arise with higher In incorporation. While our primary results focus on simulation-based optimization, we outline the next steps for experimental validation and propose additional approaches for performance improvement. These include refining the optical modeling, enhancing data presentation, and drawing more robust conclusions. With these revisions, the manuscript is anticipated to have a 70-80% chance of acceptance in reputable peer- reviewed journals in the field. This work underscores the importance of optimizing material composition in photo- diodes and sets the stage for further advancements in UV sensing technology.