Integration between Moodle and Academic Information System using Restful API for Online Learning

Prasetyo, Novian Adi; Saintika, Yudha

doi:10.26555/jiteki.v7i2.21816

Cited by 4 publications

(4 citation statements)

References 25 publications

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“…Penelitian ini akan mengeksplorasi implementasi sistem reminder jadwal pada eLearning Moodle berbasis API menggunakan framework Flutter. Dengan mengintegrasikan API Moodle [11] ke dalam aplikasi Flutter, pengguna akan dapat mengakses jadwal kuliah dan tugas mereka secara langsung melalui aplikasi mobile. Pengguna juga akan menerima pengingat jadwal yang relevan melalui notifikasi aplikasi atau pesan WhatsApp [12] [13].…”

Section: Pendahuluanunclassified

Implementasi Sistem Reminder Jadwal pada eLearning Moodle Berbasis API Menggunakan Framework Flutter

Putra

Kurniawan

2023

J. Appl. Comput. Sci. Technol.

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This research aims to develop a Flutter-based mobile application that provides users with information regarding class schedules and assignments. The application includes a reminder feature that sends notifications about lectures and assignments through WhatsApp and in-app notifications. The development methodology employed is the waterfall model, while testing utilizes black-box testing and Firebase Test Lab. The test results demonstrate the successful development of the application. Additionally, this application facilitates efficient and easy access to class schedules and assignments. It is expected to enhance users' academic performance and be applicable across various educational institutions. Overall, the development of this application offers users the advantage of effectively and efficiently managing study time and completing tasks, thereby contributing to the improvement of educational quality within institutions.

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Section: Pendahuluanunclassified

Implementasi Sistem Reminder Jadwal pada eLearning Moodle Berbasis API Menggunakan Framework Flutter

Putra

Kurniawan

2023

J. Appl. Comput. Sci. Technol.

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“…The appropriate solution will be to make a system to take attendance automatically using passive radio frequency identification (RFID) technology. The student will have an RFID tag unique to him/her; this RFID tag will function as an ID for each student (6). Using this method to take attendance will help to save time and ensure the safety of students during school hours, it is also more precise (7) than using the current methods.…”

Section: Introductionmentioning

confidence: 99%

An RFID-based smart school attendance and monitoring system

Farag

2023

BJCICN

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In this paper, a smart attendance system for students attending school is proposed. The proposed attendance system is based on radio frequency identification (RFID) technology to facilitate automation and convenience. The proposed RFID attendance system (RFID-AS) should be used by school administration to ensure safety for students, as well as for grading and evaluation purposes. After careful study, passive RFID technology is selected to be used by the proposed system because of its reasonable cost. The main components of the system are an RFID tag, an RFID reader, Visual Studio [eXpressApp Framework (XAF) tool], and SQL Server to compare the data from the RFID tag with the students’ database to record attendance automatically. A graphical user interface (GUI) is developed using Visual Studio (XAF tool) to allow parents and school faculty to log in and browse the students’ records. Students will pass the classroom door, which will have an integrated RFID reader device to read their RFID. The paper discusses the design of the solution as well as the testing scenarios

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“…Unfortunately, database access is usually restricted to privileged users. Some MIS provides API (Application Programming Interface) to allow users to gather data easily [6,7], but this practice is still not commonly used and many consider this equivalent to database access and thus restrict it for privileged users only. Hence, most users only have one option left, to extract data manually from the MIS, or through the PDF files outputted by the MIS.…”

Section: Introductionmentioning

confidence: 99%

Automatic Data Extraction Utilizing Structural Similarity From A Set of Portable Document Format (PDF) Files

Satria,

Primanita

2023

SJIA

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Instead of storing data in databases, common computer-aided office workers often choose to keep data related to their work in the form of document or report files that they can conveniently and comfortably access with popular off-the-shelf softwares, such as in Portable Document Format (PDF) format files. Their workplaces may actually use databases but they usually do not possess the privilege nor the proficiency to fully utilize them. Said workplaces likely have front-end systems such as Management Information System (MIS) from where workers get their data containing reports or documents.These documents are meant for immediate or presentational uses but workers often keep these files for the data inside which may come to be useful later on. This way, they can manipulate and combine data from one or more report files to suit their work needs, on the occasions that their MIS were not able to fulfill such needs. To do this, workers need to extract data from the report files. However, the files also contain formatting and other contents such as organization banners, signature placeholders, and so on. Extracting data from these files is not easy and workers are often forced to use repeated copy and paste actions to get the data they want. This is not only tedious but also time-consuming and prone to errors. Automatic data extraction is not new, many existing solutions are available but they typically require human guidance to help the data extraction before it can become truly automatic. They may also require certain expertise which can make workers hesitant to use them in the first place. A particular function of an MIS can produce many report files, each containing distinct data, but still structurally similar. If we target all PDF files that come from such same source, in this paper we demonstrated that by exploiting the similarity it is possible to create a fully automatic data extraction system that requires no human guidance. First, a model is generated by analyzing a small sample of PDFs and then the model is used to extract data from all PDF files in the set. Our experiments show that the system can quickly achieve 100% accuracy rate with very few sample files. Though there are occasions where data inside all the PDFs are not sufficiently distinct from each other resulting in lower than 100% accuracy, this can be easily detected and fixed with slight human intervention. In these cases, total no human intervention may not be possible but the amount needed can be significantly reduced.

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Integration between Moodle and Academic Information System using Restful API for Online Learning

Cited by 4 publications

References 25 publications

Implementasi Sistem Reminder Jadwal pada eLearning Moodle Berbasis API Menggunakan Framework Flutter

Implementasi Sistem Reminder Jadwal pada eLearning Moodle Berbasis API Menggunakan Framework Flutter

An RFID-based smart school attendance and monitoring system

Automatic Data Extraction Utilizing Structural Similarity From A Set of Portable Document Format (PDF) Files

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