Designing Location Aware Active Atm Recommender For Banking Service

Card banking customer in Ethiopia faces the problem of identifying nearby active ATM service.rnResearch shows that more than 50% of card banking customers are unsatisfied with the existingrncard banking service at their respective banks in Ethiopia. The aim of this study is to explore andrndesign location aware active ATM recommender for banking service. To this end, the study firstrndid an experiment to construct a predictive model for determining active ATM. This is followedrnby identifying nearby active ATM and presenting the optimal path from customer current positionrnto nearest active ATM.rnFor active ATM prediction J48 and PART algorithms are experimented. In this experiment 44,105rninstances with 8 attributes employed and WEKA tool is also used to construct a prediction model.rnFor determining nearest active ATMs, Euclidean, City-block and Haversine algorithms with 13rnrecords were employed. Also the experiment is conducted using GoogleMaps tool. Forrndetermining the optimal path Dijkstra’s, A*, and BFS algorithms and 54,654 instances were used.rnTo carry out this experiment GoogleMaps tool has been used. For developing a prototypernapplication java program and MySQL tools has been used.rnThe experimental result for predicting active ATMs shows that J48 decision tree has betterrnaccuracy i.e. 99.81 compared to PART rule induction algorithm. The experiment result forrndetermining nearest active ATMs shows that City-block has better performance than Euclidean,rnand Haversine algorithms. The experiment result for determining the optimal path shows that BFSrnhas better performance than Dijkstra’s, and A* algorithms.rnFinally, we design a prototype for recommending nearby active ATMs using J48 model, Cityblockrnand BFS algorithms. Accordingly, the prototype recommends the nearest active ATMs withrnthe optimal path as per the user preference (ATM type and radius) and other related nearest activernATMs which is different than the user preference. User acceptance test result shows that, thernprototype system save time for the customer. As a result, the customers are satisfied by thernprototype system. This study has limitation with respect to user need in how much effort therncustomer wants to get ATM service and studying this issue enhance customer satisfaction.

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