New Adaptive Intelligence Method for Personalized Adaptive Laboratories

Wahyono, Irawan Dwi; Fadlika, Irham; Asfani, Khoirudin; Putranto, Hari; Hammad, Jehad; Sunarti,

doi:10.1109/iceeie47180.2019.8981477

Cited by 18 publications

(8 citation statements)

References 15 publications

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“…The next test in this study is testing the material on the virtual content. The material contained in virtual content is basic learning of Chinese folklore [11][12]. Tests are carried out on material experts, namely lecturers in virtual content.…”

Section: Experimental Results From Learning Media Expertsmentioning

confidence: 99%

Implementation of Chinese Folklore Virtual Content Using an Expert System

Sunarti

Widyatmoko

Rizman

et al. 2021

KSS

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The COVID-19 pandemic has led to increased use of information technology in all community activities, especially in the field of education. One technology used for learning is the virtual laboratory with online learning media. The use of virtual laboratories in Revolution 4.0 was very effective, especially in the current COVID-19 pandemic. Usually, virtual laboratories do not provide feedback to users, especially on how to develop their skills. This study developed a virtual laboratory with personalized Chinese folklore content using artificial intelligence. The ability and willingness of the user are processed by artificial intelligence to determine the model, media and material that the user wants. When tested, this virtual laboratory’s personalization methods obtained an accuracy value of 89.2% according to the users. Keywords: virtual content, Chinese folklore, expert system

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Section: Experimental Results From Learning Media Expertsmentioning

confidence: 99%

Implementation of Chinese Folklore Virtual Content Using an Expert System

Sunarti

Widyatmoko

Rizman

et al. 2021

KSS

Self Cite

View full text Add to dashboard Cite

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“…The model of making an open online course uses the Dick and Carey model [13] and is carried out by following ten procedural steps that refer to the recommendations of Borg and Gall [14][15][16]starting from collecting the data needed for assessment to produce the product being tested and disseminated to users. In practice, there are ten steps or steps that must be performed on the R&D method [17][18][19][20][21], including:…”

Section: Methodsmentioning

confidence: 99%

Smart Online Courses Using Computational Intelligence

Wahyono

Saryono

Asfani

et al. 2020

Int. J. Interact. Mob. Technol.

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Computer network security has become an important issue in recent decades, the government and several international organizations have invested in professional education and training for computer network security. In addition, with the increasing incidence of computer network security crimes, the government and several organizations have taken precautions by providing training to students about computer network security. Some parties develop learning models that are suitable for students and find appropriate learning methods to produce professionals in the field of computer network security that is more effective. The purpose of this study is to design a framework-based Learning system in the form of an Adaptive Online Open Course in Computer System Security Subjects for Information Technology (IT) students. The benefits of this framework are to enhance students' skills and abilities in industrial-based computer network security, startup companies and the ability to complete CTF competitions in IT network security. The framework designed is Adaptive in which students learn according to the interests and topics of Computer Network Security. Interest-based on students in completing the pretest per topic. Testing in this study is testing the impact and improvement of students' learning abilities and skills on Computer Security and Security System Competence testing in a small group consisting of 20 students by seeing the success of completing 3 CTF Topics with each topic totaling 100 computer network security problems in the CTF competition, the average validation result was 83.01% and the CTF exam passing rate was 93%

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“…For example, many learning media use videos like YouTube channels, all videos receive comments from viewers. These comments are used as input for video owners to create other videos with good content [5][6][7]. Other comments are visible in the online learning materials, as there is a comment function.…”

Section: Introductionmentioning

confidence: 99%

Emotion Detection based on Column Comments in Material of Online Learning using Artificial Intelligence

Wahyono

Saryono

Putranto

et al. 2022

Int. J. Interact. Mob. Technol.

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many universities use online learning as media learning that each material of media which includes videos, textual content, or audio may be given remarks from college students. The lecture desires to recognize approximately the feelings of college students which include happy, disappointed, or unhappy when they accessed the media and instructors get an assessment of pleasant from their media. This study constructed a utility cellular for the detection of emotion from column remarks in the media online. The mobile application makes use of synthetic intelligence to type textual content from remarks and to decide the emotion of college students. The mobile application on a cellular device. The set of rules with inside the utility is k-Nearest Neighbour for the textual content mining feature in this study. The information of trying out these studies is commenting on YouTube channels and online studying which include SIPEJAR The result of trying it out is that the common accuracy is 0,697, the value of recall is 0.5595, and the common precision is 0, 4421 and the accuracy for the utility of this mobile app is 70% for detection emotion-primarily based totally on a column of remark in the media online.

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New Adaptive Intelligence Method for Personalized Adaptive Laboratories

Cited by 18 publications

References 15 publications

Implementation of Chinese Folklore Virtual Content Using an Expert System

Implementation of Chinese Folklore Virtual Content Using an Expert System

Smart Online Courses Using Computational Intelligence

Emotion Detection based on Column Comments in Material of Online Learning using Artificial Intelligence

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