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This study aims to analyze the optimization of seaweed seedling inventory management using the Economic Order Quantity (EOQ) method to enhance cost efficiency for farmers in Tarakan City. The research employs a quantitative descriptive approach, integrating EOQ with forecasting techniques (Moving Average and Exponential Smoothing) to predict raw material needs accurately. Data were processed using Microsoft Excel and POM-QM for Windows to ensure precision. The results indicate that EOQ yields an optimal order quantity of 878 ropes per order, with a frequency of 6 orders per year, a reorder point of 16 ropes, and a total inventory cost (TIC) of IDR 842,681. Compared to traditional methods (TIC IDR 2,132,083), EOQ reduces costs by 60.5%. Forecasting analysis reveals that Exponential Smoothing (MAPE 19.67%) outperforms Moving Average (MAPE 22.5%) in accuracy. These findings highlight EOQ’s effectiveness in minimizing waste, preventing stockouts, and improving productivity. The study provides practical insights for coastal small-scale farmers and policymakers in the marine sector.

In determining sales targets, each Dealer determines sales targets only based on previous sales, without any fixed calculation method. The aim of this research is to find a calculation method that is considered closest, so that it can be used to determine sales targets for the next period. The sample studied was sales of automatic motorbikes in October, November and December for the 2022 period, using actual company sales data as a reference as a comparison. The research results show that the Least Square Method can be implemented as a fixed calculation to determine sales targets for Honda brand motorbikes, with an average MAPE value of 5.3% or an accuracy value of 94.7%.