Strategi Ekonomi dalam Mengatasi Keterbatasan Data untuk Meningkatkan Proses Prediksi Penjualan TV
Indonesia
Abstract
This study is an important step in reshaping the TV sales forecasting landscape by embracing the power of advanced data science methodologies - specifically, regression analysis, time series forecasting, clustering and reinforcement learning. The ultimate goal is to delineate the multifaceted intricacies affecting TV sales dynamics, discern complex market patterns, comprehensively segment consumer preferences, and fine-tune sales approaches with precision. Through careful examination of a vast historical dataset of TV sales, the research meticulously applied the literature study methodology, culminating in a significant improvement in the accuracy and reliability of future sales predictions. These results demonstrate the tremendous potential of this methodology in overcoming the limitations of existing data, thus offering indispensable actionable insights for businesses navigating the intricacies of TV sales forecasting in a dynamic market landscape. The application of advanced data science techniques not only confronts existing constraints, but also illuminates their transformative capacity to significantly improve prediction accuracy and strategic decision-making paradigms in the field of TV sales.
Keywords: TV Sales Forecasting, Data Analysis, Market
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