ROAD IMPROVEMENT DECISION SUPPORT SYSTEM BASED ON ROAD DAMAGE SEVERE ANALYSIS

• Main Author: Dewisari Tasya, Wita
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/68929
• Institution: Institut Teknologi Bandung

The severity of road damage needs to be known in making decisions when road repairs will be carried out. The severity of the damage is seen from the extent of the damage area on the road. Area measurement by making assumptions when marking road damage is considered ineffective and inaccurate. By using artificial intelligence, the severity of road damage can be measured automatically and decisions can be made more quickly. Measurement of the severity of road damage can be made using a program that compares the pixel size of the detected damage and the comparison of the size of the real object. The system helps enter a severity measure and finally maps out how severe the damage was. The severity of road damage that has been combined with the classification of road damage can be integrated into a decision support system. The value of the pavement condition index (IKP) can be calculated from the identified damage. With a more accurate IKP, it is possible to prioritize road damage that needs to be addressed within the existing budget constraints.