Abstract
Dictionary of medicine in the form of a thick book has many disadvantages, one of which is impractical. This is the reason for Indonesian developers to create drugs e-Dictionary. But the drugs e-Dictionary that has been developed is still in the form of a letter index so that users must search the terms one by one in sequential order. This has become so inefficient and ineffective that it is necessary to add a search function and query suggestion feature to the drug e-dictionary. The purpose of this study is to build a query suggestion facility on drugs e-Dictionary using the Levenshtein Distance algorithm. The stages of this research consist of the Development of web-based drugs e-Dictionary, Implementation of the Levenshtein Distance Algorithm, Query Suggestion Testing, and Usage. Based on the results of the implementation of the Levenshtein Distance algorithm and test results, Drugs e-Dictionary can evaluate words that are not in the database. The query suggestion function works by producing the closest word output contained in the database.
Highlights
The decision to use a drug always raise concern on the benefits and risks so that a Pharmacist needs a drug dictionary to search for previously unknown terms of medicine [1]
It turns out to have drawbacks, such as it is too heavy to be carried so that it is not practically handy. This is one of many reasons for Indonesian developers to compete in creating an electronic dictionary of drugs or what we know as the term drug e-dictionary
The drug e-dictionary search function needs to be optimized with the addition of the Query Suggestion facility
Summary
The decision to use a drug (medication drug) always raise concern on the benefits and risks so that a Pharmacist needs a drug dictionary to search for previously unknown terms of medicine [1]. It turns out to have drawbacks, such as it is too heavy to be carried so that it is not practically handy. This is one of many reasons for Indonesian developers to compete in creating an electronic dictionary of drugs or what we know as the term drug e-dictionary. It makes users have to search for words or terms one by one in a sequential fashion. This has become so inefficient and ineffective that it is necessary to add a search function to the drug e-dictionary. The search function on drugs e-dictionary is very important because it can be used as a shortcut when searching words or terms needed so that users can search for words effectively and efficiently [2][3]
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