International Journal of artificial intelligence research (IJAIR)
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iLearning Model Approach in Creating Blockchain Based Higher Education Trust
No full textToday, higher education presents challenges in terms of educational and industrial collaboration. Both theoretical and practical, formal and informal are also part of the application of blockchain in education. Moreover, the assessment is still quite difficult to do to measure the skill level of students so that they can compete for jobs in the future With the problem of the academic curriculum that still uses writing media on paper, problems often arise regarding the validity of reliable document validation. So it is necessary to compare the knowledge obtained to match their abilities. From these problems, the goal was created to improve the higher education curriculum in order to find a revolutionary solution for document validation beliefs. Evaluation of the iLearning learning system combined with blockchain technology (ledger) has the benefit of being able to support these problems. By using Blockchain technology, a new learning model innovation is created in the form of the SCi-B (Student-Centered iLearning Blockchain) framework. SCi-B is a new innovation in the learning model where all activities use Blockchain so that its existence is able to manage and store all transactions, competencies, and teaching that can provide intensive assessments through digital certificates for the academic world and the world of work. So that SCi-B has a significant impact on the confidence in the results that have been obtained. This paper aims to answer the challenges of the world of education which is currently getting wider, more open, and everywhere. The model in the SCi-B framework of this paper can be used for all training institutions because this model can adapt to the specific professional needs of the job sector. This model has been validated by the existence of a web application whose use is very satisfying
TWO BUY AND SELL IN ONE BUY AND SELL : HADITH PERSPECTIVE
Get PDFThis article discusses the Hadith narrated by Hannad bin As Sariy bin Mush’ab about Two Buy and Sell in One Buy and Sell in Ṣunan al-Tirmidzi. This article was written using the Takhrīj al-Ḥadīts method. The data source is in the form of a narration of the Hadith in Ṣunan al-Tirmidzi about Two Buy and Sell in One Buy and Sell. The type of data is in the form of hadith text in Ṣunan al-Tirmidzi about Two Buy and Sell in One Buy and Sell complete sanad and matn. The data collection technique is done by tracing the Hadith narration about Two Buy and Sell in One Buy and Sell  in Ṣunan al-Tirmidzi. The data analysis technique was carried out by applying the Sharḥ al-Ḥadīth method, both in the sanad and matn aspects. This article reveals that the hadith narrated by Hannad bin As Sariy bin Mush’ab about Two Buy and Sell in One Buy and Sell in Ṣunan al-Tirmidzi relates to the concept of Hybrid Contract in Sharia Bank
IoT-Based Guppy Aquaculture Monitoring System Using C 4.5 Method on Thingspeak Platform
Get PDFMonitoring water media in Guppy fish farming is a major problem that must be solved. monitoring is carried out to obtain a decision whether the media is suitable or not suitable for getting good guppy fish.This study aims to extract knowledge in order to make decisions on the quality of Guppy fish water media through data obtained from the IoT system.The main contribution of this research is the effort to obtain new knowledge from data collected through IoT systems. New knowledge is obtained from water quality parameter data acquired by sensors of temperature, water level and pH. data from the sensor is sent to the Thingspeak cloud application via the microcontroller module. Data from the cloud is extracted into new knowledge in the form of decision-making rules for the quality of Guppy fish water media. To validate the method used, an analysis was performed using a confusion matrix in the rapidminer application. tested for the C 4.5 method and the Naive Bayes methodThe results obtained the same high accuracy of 100 percent. It is possible that this IoT system can be applied in a larger scope, for example monitoring the aquariums of various Guppy fish farming communities in a city, so that real time data on the quality of Guppy fish is obtained within the scope of Smart City
Building Empowered Online Communities: A Case Study on Brand Community in social media
Get PDFThe digital revolution has reshaped the dynamics of consumer-brand interactions, placing online brand communities at the forefront of engagement strategies. This comprehensive discourse synthesizes discussions surrounding a collection of research papers that illuminate the nuanced dimensions of these digital communities. Delving into diverse themes, from empowerment and gamification to values alignment and cross-cultural dynamics, this exploration unravels the intricate fabric of online brand communities. Through a meticulous analysis of these papers, the abstract underlines the resonance of themes across studies, offering insights into the manifold ways brands and consumers interact in the digital ecosystem. Moreover, it highlights the practical implications these insights bear for managerial practices and steering strategies that harness the potential of online brand communities. Additionally, these abstracts underscore the contributions made to theoretical foundations, enriching our understanding of contemporary consumer-brand relationships
Student Opinions on the Use of High-Tech Mobile Devices in the Design of Digital Games for Learning
No full textSchools have adopted digital technologies as a strategy for learning and teaching activities because it offers opportunities for scaffolding. This strategy has been implemented in conjunction with creative activities. In addition, activities based on digital games, known as digital game-based learning (DGBL), and various mobile technologies, have been piloted in schools over the past few years to develop innovative learning. The purpose of this research is to investigate how children's collaborative interactions develop while participating in activities requiring them to solve problems utilizing intelligent and mobile technology. Our research combines theoretical viewpoints on joint participation, affordances, and a sense of community in the context of collaborative interactions. This is done with a contextual perspective on learning as its starting point. The following are some of the questions posed in this research: (1) How do children's digital game design activities drive and support collaborative interactions while they are engaged in problem-solving activities? Furthermore, (2) How do children's ideas for designing digital games manifest themselves during activities involving the design of games that involve innovative mobile technology? The study is based on a case where a creative workshop was held with 22 Swedish third-grade children aged 9 to 10 years old who participated in game design activities in a pedagogical lab. When the children worked together to solve the problem of designing and producing a joint digital game idea using mobile technology, a sense of community emerged due to their efforts. The study's results were analyzed using a thematic approach, which revealed that the children used different orientations in their collaborative interactions. Based on this, we argue that it is crucial to be aware of the pedagogical context when preparing for educational activities that involve innovative mobile technology. This is because the pedagogical context is the aspect of the design that creates meaningful collaborative interactions, and it is only then that innovative mobile technology becomes smart. These findings have significant ramifications for the methodological field of incorporating cutting-edge mobile technology into various types of educational setting
Smart Contract Blockchain Application Design Based on The Distribution of Product Return Transaction Data
No full textIn 2020, there will be 1% bulk sugar product returns. Direct return to warehouse; it is not known how much and what kind of sugar was returned. Changes in the number of uncontrolled product availability occur in the logistics sector. We designed a sugar volume return mechanism to verify the identity of the buyer, the amount and time of the transaction, using the steps of investigation, analysis, and system design that can implement. The application is based on the truffle test framework and smart contracts on the Ropsten test network on the Ethereum Metamask platform wallet, localhost memory, and a decentralized web-based dashboard. Input data on the smart contract so that during the Ropsten net test process, it will generate blocks, hash codes, and contract hashes as transaction details. It also displays a summary report and a blockchain transaction dashboard. How much volume will increase or decrease due to returns, buyers, type of sugar commodity, time, and volume of sugar during data transactions is known. The features developed for smart contracts are private, semi-public transactions with consensus proof of work as validation and verification of the success of transaction data records
Digital Forensic Process via Parallel Data Acquisition Technic: Experimental Case Study
No full textDigital Forensics (DF) is an essential tool for solving cases of crimes committed. Based on the type of action performed, DF is classified into static forensics and live forensics. The limitations of static forensics in this method are that data collection is carried out on permanent storage media, while processes in the running system are not obtained. On the other hand, live forensics provides an opportunity to perform data retrieval on the ongoing process. Generally, live forensics is used to acquire Volatile Memory (RAM) data but can be extended on mobile devices, internet/LAN networks, and cloud systems. Browsing in private mode leaves no traces and information about what the user has done during the browsing session. This feature is often used by criminals to hide the crimes committed or at least to slow down the forensic process. To overcome this problem, it is important to do forensics on RAM and Network Forensics to obtain evidence of these crimes. This study aims to conduct DF to obtain potential evidence in criminal cases of misuse of private browsing. The evidence is expected to be used as evidence in court. The parties involved in the crime can be prosecuted in court through such evidence. This research offers Digital Forensics Process Via Parallel Data Acquisition Technic. Parallel data acquisition is a method for retrieving data on a computer or other smart device when the computer or other smart device is on through two different data sources. The first source is RAM and the second is Network Traffic. A case study on a criminal case of misuse of private browsing with Digital Forensics Process Via Parallel Data Acquisition Technic was able to obtain evidence in the form of the website visited, URL, traffic timestamp performed, source address, destination address, transmission protocol, length (size of the packet transmitted), source last node mac address, destination last node mac address, source port, destination port, and detail information. The evidence is expected to be used to reconstruct a crime of misuse of private browsing
Classification of Electroencephalogram Signal Sleeping Condition Output EEG Digital Tools Laboratory Clinical Neurophysiology Immanuel Hospital with Support Vector Machine
No full textSleep Disorders like insomnia is one of the main health problems. Sleep deficiencies can increase the risk of diabetes, hypertension and cognitive disorders and behavior. The brain produces electrical signals, when someone is doing any activity such as moving, waking up, sleeping, etc. This electrical signal can be recorded using an electroencephalogram (EEG). In this study, brain signals are read with EEG Digital Laboratory of Clinical Neurophysiology Imanuel Hospital. The EEG signal results will be classified using Machine Learning Support Vector Machine (SVM). EEG signal data was obtained from Immanuel Hospital in Bandung. Conditions to be classified are the condition of waking, drowsiness (stage-1), and sleep (stage-2). Extraction of features using discrete wavelet transform Daubechies DB4. The decomposition level used in this study is Level-1 and Level-2. Based on the tests that have been carried out, the best parameter values obtained are C 10, Gamma 1, and Kernel Poly. Based on these parameters, the accuracy value was 78.8% for level-1, and 76.6% for level-2
Determination Potential Experts by Application The Apriori Algorithm and the K-Means Algorithm
Get PDFExperts are people who have special expertise who provide services based on their expertise. The company has experts in handling projects that will be carried out for the progress of the company. The importance of the quality of experts in the company can improve the quality of human resources. The Apriori algorithm is a data mining method that has the aim of looking for association patterns based on the project being carried out so that they can be identified by experts who are often used in handling projects. Furthermore, a data mining approach is needed to classify experts with the K-means algorithm used. This study combines the Apriori and K-means algorithms, by grouping experts based on the handling of the project they are working on
K-Means and K-NN Methods For Determining Student Interest
Get PDFPutra Indonesia University 'YPTK' Padang's Department of Information Systems, Faculty of Computing Science has three specializations, namely Information Technology Management, Business Information Systems, and Industrial Information Systems. In the fifth semester, the acquisition of specializations takes place. In the next semester, the selection of specialist programs will be determined. The option of the degree is adapted to students' needs and capacities. The acquisition of results generated in the previous semester can be seen. The objective of this survey is to provide students with suggestions for the collection of degrees. The study was performed using K-Means and K-Nearest Neighbor methods to obtain the classification of students and the correlation between recent cases and past cases. This analysis uses 13 characteristics, of which 12 are predictors and 1 is the option. The test results can be used as a way to suggest the student preferences based on preset attributes through the K-Means and K-NN methods