Performance Discovery in Ubiquitous Networks

Wahyono, Irawan Dwi; Taufani, Agusta Rakhmat; Fadlika, Irham; Elmunsyah, Hakkun; Kusumo, Gradiyanto Radityo

doi:10.1109/isemantic.2018.8549791

Cited by 15 publications

(3 citation statements)

References 15 publications

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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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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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“…Artificial intelligence in virtual laboratories is used for students to be able to choose according to the wishes of practicum material that is by their abilities for all material in a virtual laboratory. One of the artificial intelligence algorithms that suit students' desires and abilities is the Expert System algorithm [11][12][13][14][15][16][17]. The expert system in the virtual laboratory functions to classify students' abilities in practicum material.…”

Section: Introductionmentioning

confidence: 99%

Development of a Personalized Virtual Laboratory Using Artificial Intelligent

Wahyono¹,

Putranto²,

Saryono³

et al. 2020

Proceedings of the International Conference on Learning Innovation 2019 (ICLI 2019)

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The development of learning technology in industry 4.0 in the last few years was growing rapidly one of which was a virtual application. One of the virtual learning applications developed was a virtual laboratory. The use of virtual laboratories in Revolution 4.0 was very useful especially educational institutions that did not have enough space and equipment. Virtual laboratory research had been carried out in recent years. The development of virtual laboratories developed was the media, models, and materials in virtual laboratories. The existing virtual laboratory was one-way learning. Virtual laboratories had no feedback with users especially the desires and abilities of users in virtual laboratories. Laboratory learning based on user desires and abilities as needed. This learning model was known as personalization. This research developed a virtual laboratory that was personalized by utilizing artificial intelligence. The ability and will of the user were processed by artificial intelligence to determine the model, media, and materials suitable for the user. The results of testing in this virtual laboratory obtained accuracy values according to users based on personalized obtained at 90.8%.

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“…Events that contain tracking information can be used to describe the entity's situation. Entities can be people, places, or objects that are considered relevant for interactions between users and applications [8][9][10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Preliminary study of wireless balloon network using adaptive position tracking technology for post disaster event

Wahyono¹,

Fadlika²,

Afandi³

et al. 2019

TELKOMNIKA

Self Cite

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Limited resources in post-disaster areas, one of which is a communication where coordination needed for aid distribution in disaster areas. Wireless balloon technology as a solution for use in post-disaster areas. Bandwidth limitations and high delay in communication systems on wireless balloons create limitations in aid coordination, especially mobile device tracking on BPBD volunteers or officers. This research develops an effective communication system at the wireless balloon to track personal device officers in disaster areas that use cellular devices. This mobile device tracking system utilizes a wireless balloon using a publish-subscribe system on their mobile devices, namely volunteers as publishers and those responsible for disasters or communities as subscribers. To overcome the limitations of communication resources on cellular devices and wireless balloons using the Adaptive method on publish-subscribe called UM-Disaster. The results of this study, the UM-Disaster system for multi-cell tracking has an average efficiency of 40-63% for bandwidth and processor use on mobile devices at 51-70%.

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Performance Discovery in Ubiquitous Networks

Cited by 15 publications

References 15 publications

Smart Online Courses Using Computational Intelligence

Smart Online Courses Using Computational Intelligence

Development of a Personalized Virtual Laboratory Using Artificial Intelligent

Preliminary study of wireless balloon network using adaptive position tracking technology for post disaster event

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