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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 15 Documents

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Search results for , issue "Vol 6, No 1 (2022): June 2022" : 15 Documents clear

Determination Potential Experts by Application The Apriori Algorithm and the K-Means Algorithm Sovia, Rini; Defit, Sarjon; Fatimah, Noor
International Journal of Artificial Intelligence Research Vol 6, No 1 (2022): June 2022
Publisher : Universitas Dharma Wacana

Experts are people who have special expertise who provide services based on their expertise.Â The company has experts in handling projects that will be carried out for the progress of the company.Â The importance of the quality of experts in the company can improve the quality of human resources.Â 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.Â Furthermore, a data mining approach is needed to classify experts with the K-means algorithm used.Â This study combines theÂ AprioriÂ and K-means algorithms, by grouping experts based on the handling of the project they are working on.

The Development of Hand Gestures Recognition Research: A Review Aziz, Achmad Noer; Kurniawardhani, Arrie
International Journal of Artificial Intelligence Research Vol 6, No 1 (2022): June 2022
Publisher : Universitas Dharma Wacana

This paper contains a review of the literature published in the last 5 years that discusses the topic of hand gesture recognition. The focus in this paper leads the reader to see the development of research over the years in hand gesture recognition, in particular that discusses about performance, methods, and datasets used in hand gesture recognition. From this paper, hopefully it can attract researchersâ€™ interest to develop technology more deeply, especially in the field of hand gesture recognition. Hand gestures are not only used as a medium of communication for people with disabilities. Hand gestures can also be used to interact with a computer without any special devices with the technology that is available today.

Mi-Botway: a Deep Learning-based Intelligent University Enquiries Chatbot Windiatmoko, Yurio; Hidayatullah, Ahmad Fathan; Fudholi, Dhomas Hatta; Rahmadi, Ridho
International Journal of Artificial Intelligence Research Vol 6, No 1 (2022): June 2022
Publisher : Universitas Dharma Wacana

Intelligent 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.

K-Means and K-NN Methods For Determining Student Interest Guslendra, Guslendra; Defit, Sarjon; Bastola, Ramesh
International Journal of Artificial Intelligence Research Vol 6, No 1 (2022): June 2022
Publisher : Universitas Dharma Wacana

Putra 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.

Analysis of Learning Algorithms for Multilayer Neural Networks Harahap, Muhammad Khoiruddin; Pramono, Eko; Novita, Hilda Yulia; Maharina, Maharina; Sasongko, Dimas; Zonyfar, Candra
International Journal of Artificial Intelligence Research Vol 6, No 1 (2022): June 2022
Publisher : Universitas Dharma Wacana

The modern stage of development of science and technology is characterized by a rapid increase in the complexity of the created technical systems. The management of such systems requires the development of new management methods, since the modification and improvement of traditional management techniques does not always ensure the fulfillment of stringent requirements for management quality indicators. Classical control methods are mainly based on the theory of linear systems, while most real objects are non-linear. The problem of the synthesis of control systems under conditions of uncertainty is currently one of the central problems in the modern theory of automatic control. The complexity of the control object itself, structural, parametric and information uncertainties in the description of the control object, and the complexity of control problems, the multi criteria of optimization problems, the lack of possible analytical solutions, the need to take into account all the properties of disturbances, etc. The solution to this problem requires a search for alternative approaches to the design of control systems, one of which involves the introduction of neural network systems. Neural network control systems are a high-tech direction of control theory and belong to the class of nonlinear dynamic systems. High performance due to parallelization of input information in combination with the ability to train neural networks makes this technology very attractive for creating control devices in automatic systems. Neural networks can be used to build regulating and switching devices, reference, adaptive, nominal and inverse-dynamic models of objects, on the basis of which objects are studied, analysis of the influence of disturbances acting on an object, determination of the optimal control law, search or calculating the optimal program for changing the impact when changing the values of the parameters of the object and the characteristics of the input data. In addition, neural networks can be used to identify objects, predict the state of objects, recognize, cluster, classify, analyze a large amount of data arriving at high speed from a large number of devices and sensors, and the like. The ability to learn according to a given principle of functioning allows creating automated control systems that are optimal in terms of speed, energy consumption, etc. Naturally, in this case, it is possible to implement several principles of functioning and the transition from one to another. They are a universal tool for modeling multidimensional nonlinear objects and finding solutions to ill-posed problems.

Explicit Equations for Estimating Resistance to Flow in Open Channel with Moveable Bed Based on Artificial Neural Networks Procedure Cahyono, Muhammad -
International Journal of Artificial Intelligence Research Vol 6, No 1 (2022): June 2022
Publisher : Universitas Dharma Wacana

The 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.

Face Recognition Using Machine Learning Algorithm Based on Raspberry Pi 4b Sunardi, Sunardi; Fadlil, Abdul; Prayogi, Denis
International Journal of Artificial Intelligence Research Vol 6, No 1 (2022): June 2022
Publisher : Universitas Dharma Wacana

Machine learning is one of artificial intelligence that is used to solve various problems, one of which is classification. Classification can separate a set of objects based on certain characteristics. This study discusses the classification of objects in the form of facial images with the aim of the system being able to recognize a person's face to access a room for security reasons. The application of machine learning using the support vector machine algorithm with the support vector classifier technique is implemented on a raspberry pi-based security device. Â The results of training using this algorithm produce a model with 99% accuracy in 0.10 seconds based on testing data of 525 face images. The model evaluation got 99% precision, 99% recall, and 99% f1-score. Testing the model made from the training process using the raspberry pi model 4b is can recognize facial images in real-time. Â If the security device detects someone at the door and then recognizes the face image then room access will be granted and an alarm is activated indicating the door is open.

Fuzzy subtractive clustering (FSC) with exponential membership function for heart failure disease clustering Annisa Eka Haryati; sugiyarto - surono; Tommy Tanu Wijaya; Goh Khang Wen; Aris Thobirin
International Journal of Artificial Intelligence Research Vol 6, No 1 (2022): June 2022
Publisher : STMIK Dharma Wacana

Objective: Fuzzy clustering algorithm is a partition method used to assign objects from a data set to a cluster by marking the average location. Furthermore, Fuzzy Subtractive Clustering (FSC) with hamming distance and exponential membership function is used to analyze the cluster center of a data point. Therefore, the purpose of this research is to determine the number of clusters with the best quality by comparing the Partition Coefficient (PC) values for each number produced. Methods: The data set which is heart failure patient data is 150 data obtained from UCI Machine Learning. The data consists of 11 variables, including age , anemia , creatinine phosphokinase , diabetes ejection fraction , high blood pressure , platelets , serum creatinine , serum sodium , gender , and smoke . It simulated and processed using Fuzzy Subtractive Clustering Algorithm, Jupyter Notebook Software with Python programming language. Result: The results showed that the most optimal number of clusters is 3, which are selected based on the largest PC value. Conclusion: Based on the results obtained, the highest P value is in cluster 3, therefore heart failure can be grouped into 3, namely low, moderate, severe.

Assessment of Body-worn Cameras Implementation Potential in Indonesia: A Systematic Literature Review Putra, Mirza Triyuna; Yazid, Setiadi
International Journal of Artificial Intelligence Research Vol 6, No 1 (2022): June 2022
Publisher : Universitas Dharma Wacana

Many 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 peopleâ€™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.

AUGMENTED REALITY- BASED DOJO SAFETY HANDBOOK Ismara, Ketut Ima; Kamil, Hasan Rahmat; Prianto, Eko; Damarwan, Eko Swi
International Journal of Artificial Intelligence Research Vol 6, No 1 (2022): June 2022
Publisher : Universitas Dharma Wacana

Study this aim to (1) Produce learning media in the form of textbooks entitled Augmented Reality-Based Safety Dojo Guidebook for Vocational subjects, (2) Knowing appropriateness from learning media in the form of textbooks , (3) knowing rating and feedback student related textbooks in the form of Book Guidelines Safety Dojo AR based .Type Study this including in Research and Development ( RnD ) research with use ADDIE approach which includes Analysis, Design, Development, Implementation, Evaluation stages .Study this conducted at SMK Hamong Putra Pakem . Then validation from product book this done by expert respective materials and media experts each totaling 2 people. Material expert involving 1 person from a vocational school teacher and 1 lecturer major electro, while from media expert involves 2 lecturers from major UNY electronics . For testing product done by students Class X and XI Department of Electrical Power Installation Engineering at SMK Hamong Putra Pakem as many as 40 students . This research instrument is in the form of a printed questionnaire which is then distributed to respondents, and through direct interviews. Whereas for the data obtained in the form of qualitative and quantitative data which are then analyzed with analysis validity reliability .Study this produce : (1) Learning Media in the form of a textbook with the title "AR-Based Dojo Safety Manual", (2) eligibility from learning media this rated from aspect Theory got results with value 87.50% with category very deserve and media aspect get results with value 78.57% with category worth , (3) Assessment from students regarding the feasibility of learning media in the form of textbooks obtained a score of 85.17% so that it is included in the very feasible category.

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Contact Name
Heri Nurdiyanto

Contact Email
Heri Nurdiyanto

Phone
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Journal Mail Official
internationaljournalair@gmail.com

Editorial Address
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Location
Kota metro,

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INDONESIA