Graph-QL (Query Language) is a new concept in the Application Programming Interface (API). Graph-QL was developed by Facebook which is implemented on the server-side. Although it is a query language, Graph-QL is not directly related to the database, in other words, Graph-QL is not limited to certain databases, either SQL or NoSQL. The position of Graph-QL is on the client and server-side that access an API. One of the objectives of developing this query language is to facilitate data communication between the backend and frontend / mobile applications. For this reason, this paper will examine the responsibility of Graph-QL in terms of response time and response size in the development of an integrated competency certification test system based on web service and compared with efficiency and flexibility using the REST API. From the test results, it was found that Graph-QL provided some advantages compare to REST API. It give more flexibility for the clients to access the data and solve the most typical problem that was over or under fetching cause by fixed data given by REST API endpoints.
Web service is a method of connecting servers and client applications. There are several types of technology in developing a web service, such as REST and Graph-QL. Graph-QL is an alternative technology created by Facebook to correct REST technology's shortcomings, especially in the data presentation section. Graph-QL provides an alternative where the client application can determine for them what data is needed. This paper analyzes the performance of the two technologies to determine which technology is suitable for their needs. The analysis carried out is to compare the response speed and data efficiency to optimize the available bandwidth. The development model uses the waterfall model, which consists of research, design, implementation, and testing. As a test object, two Node-JS based applications were developed with the Express Framework, which applied REST and Graph-QL concepts on each test object. The results obtained are that REST has better performance than Graph-QL in its response speed. On the other hand, Graph-QL also excels in data presentation by client application requests to optimize the available bandwidth.
Integrated System for Online Competency Certification Test (SITUK) is an application used to carry out the assessment process (competency certification) at LSP (Lembaga Sertifikasi Profesional) UPN (University of Pembangunan Nasional) “Veteran” Jawa Timur, each of which is followed by approximately five hundred (500) assessments. Thus the data stored is quite a lot, so to find data using a search system. Often, errors occur in entering keywords that are not standard spelling or typos. For example, the keyword "simple," even though the default spelling is "simple." Of course, the admin will get incomplete information, and even the admin fails to get information that matches the entered keywords. To overcome the problems experienced in conducting data searches on the SITUK application, we need a string search approach method to maximize the search results. One of the algorithms used is Levenshtein which can calculate the distance of difference between two strings. Implementation of the Levenshtein algorithm on the data search system in the SITUK application has been able to overcome the problem of misspelling keywords with the mechanism of adding, inserting, and deleting characters.
Landslide is one of the disasters that often occurs in several areas in Indonesia, especially in hilly areas, valleys, and volcanoes. Soil conditions in some parts of Indonesia are classified as prone to landslides. The latest data from the Central Statistics Agency related to landslides in 2018 occurred as many as 10,246 events with the highest incidence on the island of Java IoT-based ground motion monitoring using fuzzy logic is a tool that is able to detect ground movements that can trigger landslides. The manufacture of this tool is based on the ig-norance of the community in predicting the occurrence of landslides. To avoid this, an early warning tool is needed in the delivery of information that is easily understood by anyone, especially the public. This tool consists of a Microcontroller, Weather Sensor, Rain Sensor, Ground Movement Sensor, and GSM Shield as well as programs to make it hap-pen. This system was created to provide information to the public directly in land-slide-prone areas. With this early warning system, it is hoped that people who are in landslide-prone loca-tions will know more quickly and can monitor the condition of landslide-prone areas so that they will be more alert to possible dangers that come suddenly, especially fatalities, can be minimized. Through this tool can also be known when the weather is cloudy, raining as well as movement or signs of ground movement, can be monitored and monitored automatically. directly by everyone from mobile phones through "SIPEGERTA" Land Movement System in Wonosalam District, Jombang Regency
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.