International Journal of artificial intelligence research (IJAIR)
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IBC Tracer: Web-Based Application for Online Tracing the Spread of Covid-19 in Indonesia Using BFS Algorithm
Get PDFIn the case of handling the Covid-19 pandemic in Indonesia, there is a 3T (Testing, Tracing, Treatment) movement promoted by the government to reduce the impact of the spread and transmission of Covid-19. For tracing, there are currently no Information Technology-based applications or services that can assist the public in simulating the tracing of the spread of Covid-19 from one location to another location and providing disaster mitigation education to users through suggestions provided by the application after the tracking process. For this reason, this study was designed and implemented using a web-based Artificial Intelligence (Breadth-First Search) algorithm called Indonesia BFS Covid-19 (IBC). This research uses Design Science Research Methodology (DSRM) and tested using BlackBox Testing. From the testing results, it is concluded that the application can simulate the process of tracing the spread of Covid-19 in Indonesia well based on the starting point and destination, and users can gain an understanding of disaster mitigation education from the advice given by the post-tracing application, as part of 3T, to help decide the impact of the spread of Covid-19 in Indonesia
Mi-Botway: a Deep Learning-based Intelligent University Enquiries Chatbot
Get PDFIntelligent systems for universities that are powered by artificial intelligence have been developed on a large scale to help people with various tasks. The chatbot concept is nothing new in today's society, which is developing with the latest technology. Students or prospective students often need actual information, such as asking customer service about the university, especially during the current pandemic, when it is difficult to hold a personal meeting in person. Chatbots utilized functionally as lecture schedule information, student grades information, also with some additional features for Muslim prayer schedules and weather forecast information. This conversation bot was developed with a deep learning model adopted by an artificial intelligence model that replicates human intelligence with a specific training scheme. The deep learning implemented is based on RNN which has a special memory storage scheme for deep learning models, in particular in this conversation bot using GRU which is integrated into RASA chatbot framework. GRU is also known as Gated Recurrent Unit, which effectively stores a portion of the memory that is needed, but removes the part that is not necessary. This chatbot is represented by a web application platform created by React JavaScript, and has 0.99 Average Precision Score
A Novel Approach for Recognition and Identification of Low-Level Flight Military Aircraft using Naive Bayes Classifier and Information Fusion
Get PDFA problem that has been faced by the Radar is if the aircraft flies at low level or near to the surface so its coming in the aerial-surveillance airspace cannot be detected and endangers the air sovereignty. The aircraft can be recognized and identified by carrying out a technique called Visual Aircraft Recognition (VACR) using a binocular. This technique requires military personnel that has capability carrying out the air surveillance from the ground. Surveillance is a time-consuming and tiring task so it can cause fatigue and impact to the results of the recognition and identification. To cope with this problem, we have designed and implemented a novel recognition and identification method using the combination of Naive Bayes Classifier (NBC) and information fusion. By using a dataset that consists of 45 military aircrafts, 35 civilian aircrafts, 40 military helicopters, and 35 civilian helicopters with 80:20 dataset distribution for the training scheme and the validation one, we obtained the recognition accuracy of 87.1%. We also found that the recognition and identification process can be speeded up 1.2 seconds when using information fusion
Google Form-assisted Consumer Service Quality Instrument: Exploration Factor Analysis (EFA)
No full textThe aim of this article is to use exploratory factor analysis to create a consumer service quality instrument with the help of google form that meets the criteria of valid, reliable, and high fit model. This is a quantitative study that the survey method. A cross-sectional survey was used as the research design. The study's sample size was 200 people who were chosen at random using a simple random sampling technique. A consumer service quality questionnaire was used as the instrument. This instrument was analyzed using Exploratory Factor Analysis techniques. The results revealed that the customer service quality instrument model based on the EFA analysis was already in the fit criteria, that each item had a loading factor greater than 0.05 in addition to item A1, and that the instrument indicator items were declared valid in general. According to the results of the reliability test, the instrument is in the very reliable category
Framework Authentication e-document using Blockchain Technology on the Government system
No full textAs a sophisticated platform, namely Blockchain, which has 3 (three) potentials to change the governance system which is still considered traditional, solve the problem of principal agents, and minimize the crime of document falsification. However, in the government sector, the documents used can be insecure and lead to document falsification. Blockchain is becoming increasingly significant in document services and beyond until questions arise about the authenticity and security of manuscripts and documents in the government sector. So, Go-Chain (Government Blockchain) it is necessary to authenticate documents using Blockchain to minimize document forgery. By utilizing the potential of Blockchain technology, this research aims to maximize government e-documents in a modern and secure manner. Propose a Blockchain-based document framework method that is applied with a literature review study—in addition to ensuring the speed of system execution by utilizing DAO (Decentralized Autonomous Organization) and Smart Contracts. The result is that modern and safe government e-documents in document verification can significantly maintain transparency and increase trust in public services
Explicit Equations for Estimating Resistance to Flow in Open Channel with Moveable Bed Based on Artificial Neural Networks Procedure
Get PDFThe resistance to flow in an open channel is associated with the value of the Darcy-Weisbach friction factor f. For natural channels with a movable bed, the f value depends on the grain size of the bed materials and the bedforms, such as ripple, dune, or anti-dune. The total resistance to flow is the sum of the resistance due to grain roughness and bedform. Several researchers have proposed several graphs to determine the friction factor value due to the bedforms. Still, using these graphs requires graphical interpolation, which is inconvenient and difficult to apply to the flow and sediment transport calculation. This study proposes two explicit equations, ANN models 1 and 2, to compute the friction factor due to the bedform based on artificial neural networks (ANN) procedure. The data used to build the equations were obtained by digitizing the graph proposed by Alan and Kennedy. The explicit ANN equations are in the form of a series of hyperbolic tangent functions. The resulting equations can predict the friction factor value due to bedform satisfactorily
The Symmetrical and Asymmetrical Relationship of Technology Acceptance Model (TAM) on Consumer Emotional Value, and Service Innovation in Supporting Consumer Purchase Decisions
Get PDFThis study aims to determine the symmetrical and asymmetrical relationships between technology, acceptance model (TAM), and consumer emotional value and service innovation in supporting consumer purchase decisions. This research approach uses quantitative research. The primary data sources used in this study are preliminary data obtained from questionnaires and secondary data. This research was conducted in the city of Makassar. The population in this study is based on the infinite population, with a sample of 231 respondents spread across various provinces in Indonesia. Data analysis used validity, reliability, R-square, F-square, direct effect, and partial least square (PLS) hypothesis submission. The results of this study indicate that the Technology Acceptance Model (TAM) variable has a positive and significant effect on the Emotional Value and Service Innovation variables. Likewise, the Technology Acceptance Model (TAM) variable positively and significantly impacts the Consumer Purchase Decision variable by making the Emotional Value variable and Service Innovation intervene. The results of this study also show that the Technology Acceptance Model (TAM) variable has no positive and insignificant effect on the Consumer Purchase Decision variable
Assessment of Body-worn Cameras Implementation Potential in Indonesia: A Systematic Literature Review
Get PDFMany studies have researched the application of BWCs or Body-Worn Cameras in various countries that have implemented the use of BWCs on law enforcement officers. Previous research has measured how effective the implementation of body cameras is in helping law enforcement accountability and transparency, what problems may arise, and how the public perceives the use of BWCs by law enforcement. This study conducts a methodological literature review on previous research sources that have discussed the implementation of BWCs in various countries with varied research methods, resulting in various conclusions. The main study of this study aims to determine the challenges and solutions for implementing BWCs by police officers and the public awareness of BWCs. The approach used is an updated guideline on PRISMA statement 2020 by compiling 13 main studies from 276 search results, starting from 2017 to 2022, that include problems and solutions for implementing BWCs and measuring people’s perceptions of BWCs usage. It was found in this study that some of the challenges in implementing BWCs by law enforcers are trust, racism, privacy concerns, cost, and IT capacity. Meanwhile, public perception is divided into two groups: those who support and do not support it. Several supporting factors to consider are that BWCs influence police behavior, accountability, legitimacy, transparency, and procedural justice
Defining Common Inter-Session and Inter-Subject EEG Channels Using Spatial Selection Method
No full textRedundancy of information on brain signals can lead to reduce brain-computer interface (BCI) performance in applications. To overcome this, EEG channel selection is performed to reduce and/or eliminate a number of channels with irrelevant information. In the previous studies, there is energy calculation methods that have been proposed to perform EEG channel selection to improve BCI performance in classifying the brain command of motor imagery stimulation. In this study, channel selection scheme on motor movement signal will be experimented by using spatial selection method. This study performs the common active channel mechanism that divided into two parts: 1) common active channels between sessions, which known as common Inter-session channels and common active channels. These two techniques can be used by all subjects to interpret motor movement type known as common Inter-subject channels. In order to validate the performance of the proposed framework, CSP (common spatial pattern) is used as a feature extraction method and k-NN with k = 3 as the classification method. The obtained results shows that the proposed channel selection technique is able to choose common active channels in five combination numbers on Inter-sessions and Inter-subjects of the acquired EEG signals. Both types of common active channels are proven to improve BCI performance with an accuracy increase of up to 66%
Unsupervised Machine Learning Using Fp-Growth in Service and Maintenance Of Asset Management
No full textPreventive maintenance is one of effort in manufacturer industry to maintain an infrastructure that has an important thing in the industry. One of module that was provided from this system, like service and maintenance or Work Order (WO). This module has behavior data like brain jobs in human beings. Where is the data that record in memory used to learn to get a solution in the next experienced because the data WO be saved like data in the market basket analysis. The transaction data may be repeated in the next problem. So this data is interesting to be processed to get the best solution by involved it as machine learning like the recommended solution in the brain of human beings. This research will be focused on using fp-growth association rule as unsupervised machine learning to process data as a recommended solution for the technician. A different method like previous research using apriori algorithm. This research has a goal to prove the effect of minimum support with the result of decision support in fp-growth algorithm. The study shows the best condition of the result in this method is between 0.002 until 0.004 for minimum support, because the best precision ,recall, and accuration value more than 50% in that range of minimum support