This study aims to analyze the dynamics of the shipping market cycle in Kendari City using historical data to understand the pattern, duration, and factors that influence market fluctuations. This topic is important as the shipping market cycle has a significant impact on the performance of the shipping industry and regional economy, yet empirical studies at the local level are limited. The method used is a quantitative design with time series analysis and Hidden Markov Model (HMM) to identify market regimes and cycle transitions. Data were collected from tariff records and shipment volumes from 2008 to 2023. The results reveal the existence of market cycles with an average duration of 9 years consisting of boom, transition, and bust phases, and show the significant influence of fuel prices and the impact of the COVID-19 pandemic on market dynamics. The findings support business cycle theory and expand the understanding of shipping market volatility in the local context. The research conclusions emphasize the importance of adaptive strategies and risk management to deal with complex market fluctuations and provide a basis for policy making that supports the sustainability of the shipping industry in Kendari. The research also recommends the development of prediction models using real-time data and machine learning techniques for more accurate cycle analysis in the future.
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