Strategi Ekonomi Dalam Mengatasi Keterbatasan Data Untuk Meningkatkan Proses Prediksi Penjualan TV

This study represents a pivotal step in reshaping the landscape of TV sales forecasting by embracing the prowess of sophisticated data science methodologies—specifically, regression analysis, time series forecasting, clustering, and reinforcement learning. The overarching goal is to delineate the multifaceted intricacies influencing TV sales dynamics, discern intricate market patterns, segment consumer preferences comprehensively, and refine sales approaches with precision. Through a meticulous examination of an expansive historical TV sales dataset, this research meticulously applies these innovative methodologies, culminating in a significant augmentation in the accuracy and reliability of future sales prognostications. These outcomes illuminate the extraordinary potential of these methodologies in circumventing prevailing data limitations, thereby offering actionable insights indispensable for businesses navigating the intricacies of forecasting TV sales in a dynamic market landscape. The adept application of advanced data science techniques not only confronts prevailing constraints but also illuminates their transformative capacity to significantly elevate predictive precision and strategic decision-making paradigms in the realm of TV sales.