The relationship model between road surface roughness and functional condition values of the road surface using IKP method and IRI with roadroid application

Abstract

Pavement damage in road infrastructure is influenced by complex factors, particularly intense traffic and excessive loads, leading to quality decline and rapid deterioration. Evaluating road surface conditions is critical for making accurate maintenance decisions, and it needs both visual inspection and in-depth analysis. Early detection of possible faults is critical for avoiding severe harm and improving urban traffic management. Indeks Kondisi Perkerasan (IKP) and International Roughness Index (IRI) are two methodologies used in this study. Roadroid, an Android app, simplifies road roughness measurement and provides a low-cost alternative. With Indonesia's enormous road network, efficiency is critical. The study investigates the relationship between Android app data and visual evaluations. The advantages include more precise forecasting for road management and more timely and effective maintenance planning. The research results indicate that the Indeks Kondisi Perkerasan (IKP) for the AMD Lintas Timur Pandeglang road shows the highest percentage at 35% in the excellent rating, 23% in the very poor rating, 20% in the fair rating, 10% in the good and poor ratings, and 2% in the failed rating. The International Roughness Index (IRI) values yielded 72% in good condition, 20% in fair condition, 5% in severe damage condition, and 3% in slight damage condition. The equation obtained from both methods is: IKP = -0,824IRI^2 + 6,064IRI + 61,658 with R^2 = 0,245.