Optimasi Persediaan Toko Mainan Menggunakan Simulasi Monte Carlo untuk Menghadapi Ketidakpastian Permintaan Musiman - Nasution, Rafa Adhitya Dharmawangsa; Pramana, Yoddis; Lubis, Hasyim Fadhillah; Hasibuan, Ridho Rahman; Anwar, Khairul (Jurnal Teknik Industri Terintegrasi (JUTIN), 2026)
This study aims to optimize inventory policy in a toy retail store facing seasonal demand uncertainty using Monte Carlo simulation. Fluctuating demand often leads to overstock and stockout risks, increasing holding costs and potential lost sales. Historical daily demand data were used to construct a probabilistic model, followed by 10,000 simulation iterations to generate the probability distribution of total inventory costs. The cost model consists of holding costs and shortage costs. The simulation results indicate that total cost follows a probabilistic distribution and that an optimal reorder point exists to minimize the expected total cost. Sensitivity analysis confirms the trade-off between holding and shortage costs. The findings demonstrate that Monte Carlo simulation effectively supports adaptive, risk-based, and efficient inventory decision-making for small-scale retail businesses.