DESIGNING PUBLIC FACILITIES DAMAGE REPORTING APPLICATIONS USING THE K-MEANS CLUSTERING ALGORITHM

RIKA SALJUNI, MUHAMMAD SHOLAHUDDIN, FANEMA PUTRA HARTARET HAREFA, THINES RAMAN (2022) DESIGNING PUBLIC FACILITIES DAMAGE REPORTING APPLICATIONS USING THE K-MEANS CLUSTERING ALGORITHM , SKRIPSI, UNIVERSITAS PRIMA INDONESIA

ABSTRAK

Public facilities are facilities provided for public purposes such as roads, street lighting, bus stops, sidewalks, and pedestrian bridges. The facilities provide convenience for the community so they must be maintained properly. Pedestrian facilities function to separate pedestrians from vehicle traffic lanes to ensure pedestrian safety and smooth traffic. Data mining is a process of dredging or collecting important information from large data. The data mining process often uses statistical, mathematical methods, to utilize artificial intelligence technology. One method of clustering that is more popular than other clustering algorithms is K-means since the simplicity of the algorithm and its efficiency. The simplicity of the algorithm makes the K-means algorithm applicable in various fields, such as research conducted by previous studies.

An application to classify damage to public facilities based on facilities made using the K-Means Clustering method in knowing the type of damage case to public facilities. Applications to classify a case of damage to public facilities based on this type of damage are made to add new datasets so the data used can still be used if there is additional data. By applying K-Means Clustering to the application to classify a case of damage to public facilities based on this facility, it can help the community in classifying the types of damage to public facilities from damaged facilities.

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