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EMERGENCY UNIT PREDICTION BASED ON USER INPUT USING NAIVE BAYES ALGORITHM

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dc.contributor.author Sudarmi, Ichsanul Kamil
dc.date.accessioned 2024-10-08T07:15:08Z
dc.date.available 2024-10-08T07:15:08Z
dc.date.issued 2023
dc.identifier.uri http://repository.president.ac.id/xmlui/handle/123456789/11859
dc.description.abstract The Emergency Response App is a powerful software application designed to simplify the emergency response process and increase the efficiency of emergency service units such as Ambulance, Police, and Fire services. This application aims to provide a centralized platform for managing emergency events, dispatching appropriate units, and facilitating a quick and effective response to critical situations. One of the main functions of this application is its ability to collect incident details, such as location, and type of emergency, through an easy-to-use interface. This information is then sent to a central system, where it is processed and analyzed to determine the most suitable response unit. By automating the incident reporting process, emergency services can significantly reduce response times and allocate resources more efficiently. Additionally, the app uses advanced algorithms, including the Naive Bayes algorithm, to analyze event data and predict the right units to ship based on historical patterns and situational factors. Security and confidentiality are especially important in applications that deal with emergency situations. The Emergency Response app implements strong security measures to protect sensitive data and ensure compliance with privacy regulations. User authentication and authorization mechanisms are implemented to limit access to only authorized personnel, thereby preventing unauthorized individuals from modifying critical information. In conclusion, the Emergency Response App is revolutionizing the way emergency services operate by providing a centralized and efficient platform for managing emergency events. With incident reporting, unit allocation, real-time tracking, and data analysis features, this app empowers emergency response teams to provide fast and effective assistance in critical situations. By harnessing the power of technology, Emergency Response Apps contribute to saving lives and keeping communities safe by increasing the effectiveness of the overall emergency response system. en_US
dc.language.iso en_US en_US
dc.publisher President University en_US
dc.relation.ispartofseries Information Technologies;001201900001
dc.title EMERGENCY UNIT PREDICTION BASED ON USER INPUT USING NAIVE BAYES ALGORITHM en_US
dc.type Thesis en_US


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