Pembangunan Web Service Data Masyarakat Menggunakan REST API dengan Access Token

Computability evaluation of RESTful API using Primitive Recursive Function

REpresentational State Transfer (REST) is considered as one standard software architectural style to build web APIs that can integrate software systems over the internet. However, while connecting systems, RESTful APIs might also break the dependent applications that rely on their services when they introduce breaking changes, e.g., an older version of the API is no longer supported. To warn developers promptly and thus prevent critical impact on downstream applications, a deprecated-removed model should be followed, and deprecation-related information such as alternative approaches should also be listed. While API deprecation analysis as a theme is not new, most existing work focuses on non-web APIs, such as the ones provided by Java and Android.To investigate RESTful API deprecation, we propose a framework called RADA (RESTful API Deprecation Analyzer). RADA is capable of automatically identifying deprecated API elements and analyzing impacted operations from an OpenAPI specification, a machine-readable profile for describing RESTful web service. We apply RADA on 2,224 OpenAPI specifications of 1,368 RESTful APIs collected from APIs.guru, the largest directory of OpenAPI specifications. Based on the data mined by RADA, we perform an empirical study to investigate how the deprecated-removed protocol is followed in RESTful APIs and characterize practices in RESTful API deprecation. The results of our study reveal several severe deprecation-related problems in existing RESTful APIs. Our implementation of RADA and detailed empirical results are publicly available for future intelligent tools that could automatically identify and migrate usage of deprecated RESTful API operations in client code.

Big Data App is a developed framework that we made based on our previous project research and we have uploaded it on github, which is developing lightweight serverless both on Windows and Linux OS with the term of EdUBig as Open Source Hadoop Distribution. In this study, the focus is on solving problems related to difficulties in building a frontend and backend model of a Big Data application which by default only runs scripts through consoles in the terminal. This will be quite a tribulation for the end users when the Big Data application has been released and mass produced to general users (end users) and at the same time how the end users test the performance of the Map Reduce Naive Bayes algorithm used in several datasets. In accordance to these problems, we created the Big Data App framework to make the end users, especially developers, feel easier to build a Big Data application by integrating the frontend using the Web App from Django framework and Mobile App Native, while for the backend, we use Django framework that is able to communicate directly with the script either hadoop batch, streaming processing or spark streaming very easily and also to use the script for pig, hive, web hdfs, sqoop, oozie, etc. the making of which is extremely fast with reliable results. Based on the test results, a very significant result in the ease of data computation processing by the end users and the final results showing the highest classification accuracy of 88.3576% was obtained.Keywords: big data, map reduce of naive bayes, serverless, web and mobile app, restful api, django framework

In the era of information technology and now this is where almost everyone has a computer, laptop or smart phone to make the wearer more closely with the technology compared to print media such as books and newspapers. The use of print media to convey information've felt less able to deliver to the general public. What's more, especially to the people that a lot of busyness and career. While there are some important things to be delivered, for example supporting maternal health information to pregnant women, especially pregnant mothers candidate's first child. The solution to overcome this is done this research is intended to design media information supporting multimedia-based maternal health. Multimedia is one right way to simplify the delivery of information in the form of visual and audio. The existence of multimedia has changed the way humans interact with computers and smart phones is through media images, text, audio, animation and video images that interact and integrate with each other. Submission information can be better due to the multimedia are capable of producing media becomes more interesting and lively. Black box testing is performed to determine the performance of applications and correspondence between inputs and outputs so that the data is displayed in accordance with the input data in the application view.

In this era of information technology, there is a huge and excessive amount of fully distributed, structured and unstructured data which is usually referred as 'Big Data'. This data cannot be easily and directly used for business purposes due to its excessiveness nature. Therefore, it is required to intelligently process this large amount of data to extract desired information and examine pattern to make decisions and predictions for certain business objectives. In this context, Model Driven Engineering (MDE) techniques are frequently applied for Big Data analytics. This paper investigates the latest models, approaches and tools for Big Data analytics using model driven approaches. Particularly, a Systematic Literature Review (SLR) is performed to select and analyze 24 researches published during 2010 to 2017. This leads to identify 18 models, 13 tools, and 10 approaches for big data analytics using model driven approaches. The findings of this SLR are highly valuable for the researchers, students and practitioners of the domain.

REST APIs have become key components of web services. However, they often contain logic flaws resulting in server side errors or security vulnerabilities. HTTP requests are used as test cases to find and mitigate such issues. Existing methods to modify requests, including those using deep learning, suffer from limited performance and precision, relying on undirected search or making limited usage of the contextual information. In this paper we propose APIRL, a fully automated deep reinforcement learning tool for testing REST APIs. A key novelty of our approach is the use of feedback from a transformer module pre-trained on JSON-structured data, akin to that used in API responses. This allows APIRL to learn the subtleties relating to test outcomes, and generalise to unseen API endpoints. We show APIRL can find significantly more bugs than the state-of-the-art in real world REST APIs while minimising the number of required test cases. We also study how reward functions, and other key design choices, affect learnt policies with a thorough ablation study.

RESTful APIs are a type of web service that are widely used in industry. In the past few years, a lot of effort in the research community has been spent in designing novel techniques to automatically fuzz those APIs to find faults in them. Many real faults were automatically found in a large variety of RESTful APIs. However, usually the analyzed fuzzers treat the APIs as black-box, and no analysis of what is actually covered in these systems is done. Therefore, although these fuzzers are clearly useful for practitioners, we do not know their current limitations and actual effectiveness. Solving this is a necessary step to be able to design better, more efficient, and effective techniques. To address this issue, in this article we compare seven state-of-the-art fuzzers on 18 open source—1 industrial and 1 artificial—RESTful APIs. We then analyze the source code for which parts of these APIs the fuzzers fail to generate tests. This analysis points to clear limitations of these current fuzzers, listing concrete follow-up challenges for the research community.

Pandih Batu 1 Public High School, is one of the State Senior High Schools in Pandih Batu District, Pulang Pisau Regency, Central Kalimantan, to be precise on Jl. Pemdinding Desa Pangkoh Hulu. So far, the activities carried out by the OSIS as well as extracurricular activities at Pandih Batu 1 Public High School are still managed manually, such as in the election of new OSIS chair candidates at Pandih Batu 1 Public High School still using conventional methods, namely direct voting, do not take advantage of information technology. In overcoming these problems, the author intends to build an information system for the management of the Pandih Batu 1 State Senior High School student council called SI-OSIS. The title that will be raised by the author in this final project research is "Design and Build a Website Management of Student Council Information Systems and Extracurriculars at Pandih Batu 1 Public High School" with the hope that it will become a new tool and alternative that can facilitate the management of Pandih Batu 1 Public High School Student Council to become more sophisticated in the era of information technology that has been digitized so that students at SMA Negeri 1 Pandih Batu are not left behind with current information technology developments. The data collection methods used by the author are observation, interviews, and library research. Pandih Batu 1 Public High School, is one of the State Senior High Schools in Pandih Batu District, Pulang Pisau Regency, Central Kalimantan, to be precise on Jl. Pemdinding Desa Pangkoh Hulu. So far, the activities carried out by the OSIS as well as extracurricular activities at Pandih Batu 1 Public High School are still managed manually, such as in the election of new OSIS chair candidates at Pandih Batu 1 Public High School still using conventional methods, namely direct voting, do not take advantage of information technology. In overcoming these problems, the author intends to build an information system for the management of the Pandih Batu 1 State Senior High School student council called SI-OSIS. The title that will be raised by the author in this final project research is "Design and Build a Website Management of Student Council Information Systems and Extracurriculars at Pandih Batu 1 Public High School" with the hope that it will become a new tool and alternative that can facilitate the management of Pandih Batu 1 Public High School Student Council to become more sophisticated in the era of information technology that has been digitized so that students at SMA Negeri 1 Pandih Batu are not left behind with current information technology developments. The data collection methods used by the author are observation, interviews, and library research.

In the era of information technology, the approach of teaching Arabic language teachers in developing speaking skills must change. Currently, the traditional methods used in teaching speaking skills in Arabic are considered outdated and less developed compared to modern techniques used in teaching other languages. Arabic language teachers should take advantage of available technology, such as the internet, to make the process of learning speaking skills more engaging, creative, and motivating. The use of the internet in teaching speaking skills is considered an important step in developing the learning process. Teachers can utilize various internet resources to present interactive and engaging lessons that stimulate student participation and enhance their understanding of the topics discussed. Multimedia resources such as instructional videos and interactive resources on the internet can be used to expand students' understanding and stimulate them to learn more effectively. Study results indicate that speaking skill learning methods and internet-based media have a significant impact on improving students' speaking skills. These modern methods can make the learning process more effective and suitable for students' needs in the era of information technology.

Abstract.Utilization of information technology in the field of public transportation has been proven in improving the quality of public transportation services. The availability of information technology that supports public transportation in Malang city is still limited. An effort is required to encourage the availability of information technology that support public transportation in Malang city. This research attempts to propose a draft proposal of REST API designed for supporting information about public transportation services in Malang city. The result of this research showed that the REST API should provide a search facility to find proper service mode of transportation, cost estimation, time estimation, calling or booking a public transportation, a list of all the modes of transportation that exist, as well as detailed information on a mode of transport in which includes the name of public transportation, index of comfortability, index of security, index of safety, index of privacy, index of availability, index of accessibility index, and route.Keywords: Transportation, Public Transportation, API, REST, Service-Oriented Architecture, Web Service.

This paper focuses on the design and implementation of a distributed, highly scalable, and fault-tolerant anti-fraud service accessible via REST API. Web service works in near real-time and employs machine learning algorithms for predictive analytics. Our goal is to develop an affordable anti-fraud service, which provides a possibility for participating parties (i.e. merchants, aggregating agents, payment systems, and banks) to reduce the risks of fraudulent payments over their sites. We explore a number of approaches resulting in a significant reduction of hardware and software costs as well as the size of the team working on the project.

Access to data plays a major role in designing and performing efficient data computation and analyses in a distributed environment. Existing approaches access data via a variety of methods and offer various benefits and drawbacks based on the use case. Our original use case was the computational analysis of environmental sequence data, or metagenomics. Unlike other workflows that often reduce the dataset size dramatically within the first few processing steps, owing to biologially-motivated data compression. Metagenomic data compresses poorly, and so metagenomic workflows add to the size of the data set along the processing pipeline. Thus, wide-area, high-throughput access to the data is essential. To address this problem, we developed Shock, a data store for files, their associated metadata, and indexes that allow Shock to provide different views into the data. Shock comprises three major components: a web service that provides a RESTful API, backend data storage for files, and storage for object metadata. Shock has proven to be a stable data store for MG-RAST, an application that served over 40,000 users in 2014 on a server that houses more than 3 million data objects. Moreover, Shock provides both subselection and high-performance file transfer capabilities that serve most usages.

The interaction of distributed applications raises an integration problem that needs to be solved. Current integration technologies, such as Web Services and RESTful APIs, solve the interoperability problem but usually entail more coupling than required by the interacting applications. This is caused by sharing data schemas between applications, even if not all features of those schemas are actually exercised. The fundamental problem of application integration is therefore how to provide at most the minimum coupling possible while ensuring at least the minimum interoperability requirements. This article proposes compliance and conformance as the concepts to achieve this goal, by sharing only the subset of the features of the data schema that are actually used.

To face the worldwide competition and meet the recent requirements in the new information technologies era, digitalization and adoption of new information techniques have become a must for all transport and logistics companies and organizations to improve their activities. This digital transformation of transport and logistics sectors is giving birth to huge and increasingly growing sets of voluminous data with high velocity and varied data sources, also known as Big Data. With new manipulation and management infrastructures, as well as more real-time analysis and techniques, these enormous datasets can be efficiently harvested to carry out valuable operational improvements and create new business values in the transport and logistics domains. This paper provides a review of the Big Data in the transport and logistic fields, discusses the current research challenges and identifies some of the promising directions for future research.

Massive amounts of building operational data are collected and stored in modern buildings, which provide rich information for in-depth investigation and assessment of actual building operational performance. However, the current utilization of big building operational data is far from being effective due to the gaps between building engineering and advanced big data analytics. Data mining is a promising technology for extracting previously unknown yet potentially useful insights from big data. This paper aims to explore the potential application of advanced data mining techniques for effective utilization of big building operational data. A case study of mining the operational data of an educational building for performance improvement is presented. Decision tree, clustering analysis, and association rule mining are adopted to analyze the operational data. The results show that useful knowledge can be extracted for identifying typical building operation patterns, detecting operation deficiencies, and spotting energy conservation opportunities. Practical application:The current utilization of big building operational data in the building industry is rather limited due to the lack in experience of using advanced big data analytics. This study presents a data mining-based method for analyzing massive building operational data. The case study results validate the efficiency and effectiveness of the method proposed. It can help building professionals to discover valuable insights into building operation patterns and thereby developing strategies for improving building energy efficiency. The method can be fully realized using the open-source software R, which provides great flexibilities in its integration with building automation systems.