Abstract
Combining the search method for fire suppression routes with ant colony algorithms and methods of analyzing twitter events on the highway is the basis of the problems to be studied. The results of the twitter data feature extraction are classified with Support Vector Machine after it is implemented in the Simple Additive Weighting method in calculating path weights with criteria of distance, congestion, multiple branching, and many holes. Line weights are also used as initial pheromone values. The C-means method is used to group the weights of each path and distance so that the path with the lowest weight and the shortest distance that will be simulated using the Ant Colony. The validation results with cross fold on SVM with linear kernels produce the greatest accuracy value is 97.93% for training data distribution: test data 6: 4. The simulation of the selection of the damkar car path from Feather to Pleburan with Ant Colony obtained 50 seconds of computation time, whereas with Ant Colony with Clustering the computation time was 15, resulting in a reduction in computing of 35. Ant colony with MinMax optimization gives the best computation time of 14.47 seconds with 100 iterations and 10 nodes.
Highlights
Highway is one of the infrastructures that connects one place to another
It was concluded that the use of the Support Vector Machine (SVM) method gave the best results compared to other methods, namely the accuracy of up to 82.2% [11]
From the discussion described in the previous chapter, a conclusion can be drawn about the Ant Colony Clustering algorithm by weighting Simple Additive Weighting (SAW) on the twitter data The extraction of 207 data twiter features taken from May 2, 2019 to June 30, 2019 with the #lalinSMG hastag is the most "smooth" with 111 tweets
Summary
Highway is one of the infrastructures that connects one place to another. In the current modern era with the high demand for roads and the large number of road users, highway management is needed to respond and detect quickly and precisely the dynamic phenomena that occur [1]. One of the traffic management arrangements is the management of fire engine routes This management system must be able to present the fastest route from the location of the pool of fire engines based on distance, congestion value, number of road holes and branching, so that the calculation of the weight value is needed to obtain the optimal solution [4]. Ant colony with clustering algorithm is used to get the optimal path with twitter data in realtime traffic conditions and displayed with a mobile-based interface
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