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International Journal of Artificial Intelligence Research

IJAIR
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Published by STMIK Dharma Wacana

ISSN : - EISSN : 25797298 DOI : -

Core Subject : Science, Engineering,

Computer Science & IT Electrical & Electronics Engineering

International Journal Of Artificial Intelligence Research (IJAIR) is a peer-reviewed open-access journal. The journal invites scientists and engineers throughout the world to exchange and disseminate theoretical and practice-oriented topics of Artificial intelligent Research which covers four (4) majors areas of research that includes 1) Machine Learning and Soft Computing, 2) Data Mining & Big Data Analytics, 3) Computer Vision and Pattern Recognition, and 4) Automated reasoning. Submitted papers must be written in English for initial review stage by editors and further review process by minimum two international reviewers.

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Articles 16 Documents

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Search results for , issue "Vol 6, No 2 (2022): Desember 2022" : 16 Documents clear

IBC Tracer: Web-Based Application for Online Tracing the Spread of Covid-19 in Indonesia Using BFS Algorithm Pratama, I Putu Agus Eka
International Journal of Artificial Intelligence Research Vol 6, No 2 (2022): Desember 2022
Publisher : Universitas Dharma Wacana

In 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.

A Novel Approach for Recognition and Identification of Low-Level Flight Military Aircraft using Naive Bayes Classifier and Information Fusion Arwin Datumaya Wahyudi Sumari; Afifah Millatina Nugraheni; Yoppy Yunhasnawa
International Journal of Artificial Intelligence Research Vol 6, No 2 (2022): Desember 2022
Publisher : STMIK Dharma Wacana

A 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.

Smart Contract Blockchain Application Design Based on The Distribution of Product Return Transaction Data Ekawati, Ratna; Arkeman, Yandra; Suprihatinr, Suprihatinr
International Journal of Artificial Intelligence Research Vol 6, No 2 (2022): Desember 2022
Publisher : Universitas Dharma Wacana

In 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.

A Mobile Deep Learning Model on Covid-19 CT-Scan Classification Susanto, Prastyo Eko; Kurniawardhan, Arrie; Fudholi, Dhomas Hatta; Rahmadi, Ridho
International Journal of Artificial Intelligence Research Vol 6, No 2 (2022): Desember 2022
Publisher : Universitas Dharma Wacana

COVID-19 pandemic is currently happening in the world. Previous studies have been done to diagnose COVID-19 by identifying CT-scan images through the development of the novel Joint Classification and Segmentation System models that work in real-time. In this study, the author focuses on a different motivation and innovation focused on the development of mobile deep learning. Mobile Net, a deep learning model as a method for classifying the disease COVID-19, is used as the base model. It has a good level of efficiency and reliability to be implemented on devices that have small memory and CPU specifications, such as mobile phones. The used data in this study is a CT-scan image of the lungs with a horizontal slice that has been classified as positive or negative for COVID-19. To give a broader analysis, the author compares and evaluates the model against other architectures, such as MobileNetV3 Large, MobileNetV3 Small, MobilenetV2, ResNet101, and EfficientNetB0. In terms of the developed mobile architecture model, the classification of COVID-19 using MobileNetV2 obtained the best result with 0.81 accuracy.

iLearning Model Approach in Creating Blockchain Based Higher Education Trust Anwar, Aang Solahudin; Rahardja, Untung; Prawiyogi, Anggy Giri; Santoso, Nuke Puji Lestari; maulana, sabda
International Journal of Artificial Intelligence Research Vol 6, No 2 (2022): Desember 2022
Publisher : Universitas Dharma Wacana

Today, 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.Â Evaluation of the iLearning learning system combined with blockchain technology (ledger) has the benefit of being able to support these problems.Â 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.Â 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.

Journal Unique Visitors Forecasting Based on Multivariate Attributes Using CNN Dewandra, Aderyan Reynaldi Fahrezza; Wibawa, Aji Prasetya; Pujianto, Utomo; Utama, Agung Bella Putra; Nafalski, Andrew
International Journal of Artificial Intelligence Research Vol 6, No 2 (2022): Desember 2022
Publisher : Universitas Dharma Wacana

Forecasting is needed in various problems, one of which is forecasting electronic journals unique visitors. Although forecasting cannot produce very accurate predictions, using the proper method can reduce forecasting errors. In this research, forecasting is done using the Deep Learning method, which is often used to process two-dimensional data, namely convolutional neural network (CNN). One-dimensional CNN comes with 1D feature extraction suitable for forecasting 1D time-series problems. This study aims to determine the best architecture and increase the number of hidden layers and neurons on CNN forecasting results. In various architectural scenarios, CNN performance was measured using the root mean squared error (RMSE). Based on the study results, the best results were obtained with an RMSE value of 2.314 using an architecture of 2 hidden layers and 64 neurons in Model 1. Meanwhile, the significant effect of increasing the number of hidden layers on the RMSE value was only found in Model 1 using 64 or 256 neurons.

Defining Common Inter-Session and Inter-Subject EEG Channels Using Spatial Selection Method Fauzi, Hilman; Komura, Tadayasu; Kyoso, Masaki; Shapiai, Mohd. Ibrahim; Mumtaz, Yasmin
International Journal of Artificial Intelligence Research Vol 6, No 2 (2022): Desember 2022
Publisher : Universitas Dharma Wacana

Redundancy 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%.

Framework Authentication e-document using Blockchain Technology on the Government system Isyak Meirobie; Agustinus Purna Irawan; Husni Teja Sukmana; Diana Putri Lazirkha; Nuke Puji Lestari Santoso
International Journal of Artificial Intelligence Research Vol 6, No 2 (2022): Desember 2022
Publisher : International Journal of Artificial Intelligence Research

As 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.

Face Detection Analysis of Digital Photos Using Mean Filtering Method Sunardi, Sunardi; Yudhana, Anton; Wijaya, Setiawan Ardi
International Journal of Artificial Intelligence Research Vol 6, No 2 (2022): Desember 2022
Publisher : Universitas Dharma Wacana

Face detection in digital photos aims to get the face area in the digital photo. Usually, a lot of noise occurred when detecting faces in digital photos. This study applies the mean filtering method to improve digital photos by reducing noise. The accuracy of the mean filtering method is calculated using a confusion matrix, while the ability of this method is measured using the parameters of Mean Square Error (MSE) and Peak Noise to Signal Ratio (PNSR). Viola-Jones method was used to detect faces in this research. This method was chosen because it is one of the face detection procedures with high accuracy and good computational ability. Testing the mean filtering method obtained the lowest MSE of 9.33, while the highest PNSR of 14.37. The accuracy obtained by the mean filtering method using confusion is 90%. Based on these results, it can be concluded that the mean filtering method is feasible to be used in the case of face detection in digital photos.

Mobile Forensic Investigation of Fake News Cases on Instagram Applications with Digital Forensics Research Workshop Framework Riadi, Imam; Herman, Herman; Rafiq, Irhash Ainur
International Journal of Artificial Intelligence Research Vol 6, No 2 (2022): Desember 2022
Publisher : Universitas Dharma Wacana

The number of digital crimes or cybercrimes today continues to increase every year, and lately a lot of it happens on social media like Instagram. The social behavior of today's people who communicate more through social media encourages the perpetrators of these digital crimes. Instagram is a social media that is often found content that contains elements of pornography, hoax news, hate speech, etc. This research is aimed at processing digital evidence of cases of the spread of hoax news on the Instagram application. This research follows the framework of the Digital Forensics Research Workshop (DFRWS) with six stages, namely identification, preservation, collection, examination, analysis, and presentation. The process of obtaining digital evidence is assisted by the application of Axiom Magnet and Cellebrite UFED. Digital evidence sought from the smartphone device of the suspected hoax news disseminator seized following the case scenario consists of 8 variables in the form of accounts, emails, images, videos, URLs, times, IP address, and location. The results of this research with the help of the application of Magnet Axiom digital proof obtained 87.5% and the Cellebrite UFED application of 68.75%. The results of this study show that Magnet Axiom has better performance than MOBILedit Forensics.

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Home Page

OAI Link

Editorial Team

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Journal Mail Official internationaljournalair@gmail.com

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Contact Name
Heri Nurdiyanto

Contact Email
Heri Nurdiyanto

Phone
-

Journal Mail Official
internationaljournalair@gmail.com

Editorial Address
-

Location
Kota metro,

Lampung

INDONESIA