Today’s internet technologies support everything that human do. By using integrated technologies the things that connected to internet can provide data. The Internet of Things (IoT) is the new paradigm in provide the data without human communicated. The IoT system support machine to machine communication that can be used to develop smart services that can generate a lot of data. This exponential data can support a decision making. The decision making system depend on availability and reliability of data. This study focus to how the Internet of Thing support decision making system. With a survey of literature to understand the trends, models and factors of decision making in IoT based on previous research. This survey following step by conduct the research question (RQ), then search and observation the previous research from database journal. Based on reviewing 26 articles, this study conclude that the trends of decision making in IoT are implemented on Manufacturing and Industry, Healthcare, Agriculture and Transportation. Besides that the decision model that can support by IoT used Fog Computing, Fuzzy, Game Theoritic, Clustering Based on Multimodal Data Correlation, etc. Meanwhile the decision making factors that influenced by IoT like Latency, data-driven, security, data reliability and accurate. The integrated of model and point of interest on decision making in IoT should be improved. It will be the opportunities and challenge in IoT to support decision making in future.
Ship health checks must be carried out which function to provide a sailing permit. The implementation of ship health checks is carried out in collaboration with the ministry of health and transportation. The implementation of the activity, commonly known as Port Health Quarantine Clearance (PHQC) requires time to check and the ship makes a payment check to be able to issue a sailing permit. The problem that arises in the field is that the ship delays PHQC payments and then impacts on the buildup of ships in the port, besides that officers also need longer time to process the issuance of sailing permits. This of course has an impact on other port services such as dwelling time and scheduled departures that can be delayed. In overcoming this problem, an in-depth study is needed to analyze the trend of late payment of ship health checks, what variables influence it and how treatment is done to overcome these problems. Using logistic regression and decision tree with Classification and Regression Tree algorithm , a model is then developed that determines the variables that affect the delay of the ship making PHQC payments.
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