Using Euclidean Distance and Haversine Method For Early Warning of Highway Damage Application in Maros District Android-based
Rismayani(a*), Fahmi Satriawan Taslim(b), Reski Ariani(b)

a)Software Engineering Department, STMIK Dipanegara Makassar, Perintis Kemerdekaan Km.9 Street Makassar, Indonesia
rismayani[at]dipanegara.ac.id
b)Informathic Engineering Department, STMIK Dipanegara Makassar, Perintis Kemerdekaan Km.9 Street Makassar, Indonesia

Abstract

The highway in Maros district is part of the Trans Sulawesi route that connects three regions namely Makassar City, Pangkep district and Bone ditrict. The Trans Sulawesi route in the Maros district there were several points that were damage due to damage to road materials during the rainy season, this makes road users who use motorized vehicles instead of two wheels often have accidents. Based on data from the Maros Traffic Police in 2018-2019 the number of road accidents was 188 cases, 35% of which were due to road damage. The problem in this research is how to design an application android-based that can provide early warning about road damage in Maros district so that it can reduce road accident cases due to road damage and how to apply the Euclidean Distance and Haversine method for early warning of highway damage in the Maros district. The method used is Euclidean Distance and Haversine to calculate two points of distance between the rider and the point of damage to the road. The results of this study are the application of early warning of road damage in Maros district, this can help road users, especially riders in getting preliminary information about the state of the road to be traversed so that data drivers are more careful, based on functional testing for road damage early warning applications declared valid, hen based on the results of a questionnaire obtained from 50 respondent consisting of riders to find out the benefits of the application obtained 87.3% of the results declared very useful, 11.2% useful, 1.5% quite useful and 0% useless.

Keywords: Euclidean Distance, Haversine, Early Warning, Highway Demage, Android

Topic: Computer Science