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International Journal Artificial Intelligent and Informatics

IJARLIT
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Published by Research and Social Study Institute

ISSN : - EISSN : 2622626X DOI : https://doi.org/10.33292/ijarlit.v2i2.36

Core Subject : Science,

Computer Science & IT

The journal scopes include (but are not limited to) the followings: Computer Science: Artificial Intelligence, Data Mining, Database, Data Warehouse, Big Data, Machine Learning, Operating System, Algorithm Computer Engineering: Computer Architecture, Computer Network, Computer Security, Embedded system, Cloud Computing, Internet of Thing, Robotics, Computer Hardware Information Technology: Information System, Internet & Mobile Computing, Geographical Information System Visualization: Virtual Reality, Augmented Reality, Multimedia, Computer Vision, Computer Graphics, Pattern & Speech Recognition, image processing Social Informatics: ICT interaction with society, ICT application in social science, ICT as a social research tool, ICT education

Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)

Articles 29 Documents

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An instruction detection system with Support Vector Machine, Cuckoo-Genetic algorithm and principal component analysis F. Nayebi; M.Noorimehr M.Noorimehr
International Journal Artificial Intelligent and Informatics Vol. 3 No. 1 (2022)
Publisher : Research and Social Study Institute (ReSSI)

Nowadays, with the abundant growth of internet users, attacks on computer systems have dramatically increased. This condition might increase the risk of security for Internet users or networks systems. Thus, Intrusion Detection Systems (IDS) is used for detection, identification and diagnosis of security issues on computer networks .As a data mining technique, Support Vector Machine (SVM) is considered in the design and implementation of IDS.SVM’s performance is influenced by its parameters and its input feature space respectively. So, in order to reach and achieve a reasonable efficiency of SVM, two values should be optimized: values of parameters for better accuracy, and set of input feature for shorter training time. In this paper, we used Principal Component Analysis (PCA) for feature extraction and dimension reduction of input data and the Cuckoo-Genetic algorithm, as a meta-heuristic optimization technique, to determine the optimum parameters of SVM for classification of normal and malicious data. The practical results, by using proposed method on NSL-KDD dataset, indicates that the proposed method reached a better detection rate Compared to genetic and cuckoo.

Secure medical image steganography based on Discrete Wavelet Transformation and ElGamal encryption algorithm S. Jeevitha; N.Amutha Prabha N.Amutha Prabha
International Journal Artificial Intelligent and Informatics Vol. 3 No. 1 (2022)
Publisher : Research and Social Study Institute (ReSSI)

The latest development in computing methodologies and related steganography based applications had created a novel practice such as telemedicine where patient diagnosis images or allied information can be used diagnosis practices that are located in remote areas. In order to provide accurate and effective telemedicine the flawless or seamless biomedical information is required from patient. With respect to this the medical data may remain prone to get corrupted by hackers or might get manipulated when transmitted through an insecure channel. The cryptosystems which are available are not efficient enough to solve the above mentioned issues. Hence, in this research work a much efficient and effective image steganography technique has been proposed in order to hide the confidential and important image information. We have incorporated Discrete Wavelet Transformation (DWT) technique instead of wavelet transform techniques to embed the secret message in the required cover images. Also, to assure continuous communication through insecure channel, a new model called ElGamal encryption cryptosystem model has been implemented which contains the steganography scheme which has been proposed and developed. To maintain the content of Region of Interest (ROI), Region of Non- Interest (RONI) is used to embed the secret information. The overall performance analysis reveals that the DWT with ElGamal encryption provides more efficient and also have high embedding capacity, imperceptibility when compared to other methods like Hamming code, Syndrome-Trellis Code (STC) and Rivest-Shamir- Adleman (RSA) based methods.

A Study on Compressive Sensing based Clustering algorithms in Wireless Sensor Networks for reduced data transmissions Shaamili Varsa G V Shaamili Varsa G V; Basavaraj S Mathpati
International Journal Artificial Intelligent and Informatics Vol. 3 No. 1 (2022)
Publisher : Research and Social Study Institute (ReSSI)

Energy Efficiency plays a vital role in Wireless Sensor Networks (WSN) because of the limited battery power of nodes. Data Aggregation techniques help in reducing the redundant data transmissions which results in reduced energy consumption. Compressive Sensing (CS) is one of the effective signal processing techniques which helps in reducing the number of transmissions resulting in improved energy efficiency. Clustering is also a proven method of energy efficient data transmission. Employing the CS technique in cluster based WSN gains advantages of both and the outcome of which is further reduction in energy consumption. In this paper, a review of algorithms which employ CS in cluster based WSN is made and explanation of the same is given in brief. Some algorithms employ plain-CS and some employ hybrid-CS techniques. Using the sparse representation of the data vector in some orthonormal basis, even with smaller number of measurements, the data can be reconstructed accurately. First, we have given the details of compressive sensing and the possible sparse transforms, measurement matrices and data reconstruction algorithms. Then, recent works which exploit CS in clustering algorithms are discussed and comparison of the same is provided.

Securing a mobile ad hoc NETwork against the man in the middle attack Ryma Abass; Aimable Habyarimana; Karim Tamine
International Journal Artificial Intelligent and Informatics Vol. 3 No. 1 (2022)
Publisher : Research and Social Study Institute (ReSSI)

Mobile Ad hoc NETworks (MANET) are a special kind of wireless net- works where there is neither centralized authority nor pre-existing infrastructure. Hence, in such situation, authenticating nodes becomes a challenging task. This is even more true that some nodes may be tempted by spoofing other nodes identity in order to gain some rights and privileges. In such context, a protocol based on keys exchange such as Diffie-Hellman can be used. However, even such protocol is vulnerable to impersonation attack e.g. the Man in the Middle (MIM) attack. The main objective of this work is then, to evaluate the impact of a MIM attack on the context of MANET and to propose a security solution to such situation. This is done by (1) estimating the needed ratio of attackers to achieve a MIM attack in a given MANET and (2) proposing a security process based on the well known Diffie-Helman protocol.

Multi-layer encryption algorithm for data integrity in cloud computing Arwa Zabian; Shakir Mrayyen; Abram Magdy Jonan; Tareq Al−Shaikh; Mohammed tthazi Al − khaiyat
International Journal Artificial Intelligent and Informatics Vol. 3 No. 2 (2022)
Publisher : Research and Social Study Institute (ReSSI)

The Internet revolution has changed all aspects of our life, accessing and surfing the Internet is becoming as necessity in our life to obtain any kind of information needed, that produces a huge quantity of data available any time, any where. The greater the facilities, less our data privacy. For that maintaining data confidentiality and integrity in the Internet and cloud world is a primary requirement to continue working and using these facilities. In this paper, we propose a security mechanism that makes accessing the data from unauthorized persons more complex. Our mechanism easy to implement and understand but is complex to decrypt because it works in three levels in each level is used a new encryption key generated randomly and in each level is used a different encryption algorithm. Our results show that the encryption/decryption process time is increased linearly with the text size for the authorized persons and is increased exponentially for unauthorized persons.

Analysis of Data Transmission using one modified neural networks Inna Kal’chuk; Serhii Laptiev; Tetiana Laptievа
International Journal Artificial Intelligent and Informatics Vol. 3 No. 2 (2022)
Publisher : Research and Social Study Institute (ReSSI)

The traditional neural networks cannot provide modern mapping capability which is most important for analysis of data transmission nowadays. Therefore, Sigma-Pi-Sigma neural networks (SPSNNs) are good tool for this operation because of easy architecture. Application of integrated learning approach for neural networks, which uses sigma-pi-sigma neurons, helps us to complete their task for small period of time. It’s very necessary for neurons to find the solution of the problem. A final result of our results can be used in order to find the routes of “safety”, which we can indicate by position and state of cable lines or ties. For correct analysis and accurate results, we use pulse refectory method with using special device in order to get waveform, which introduce the connection problem. So, Sigma-Pi-Sigma neural network model is used for exact interpretation of altering probe signal. It is crucial that we also used rectangular methods of summation of Fourier series firstly. Therefore, it is main novelty of our investigation.

On the adaption of data mining technology to categorize cancer diseases Manal Al-Dafas; Ammar Albujeer; Shaymaa Abed Hussien; Raed Khalid Ibrahim
International Journal Artificial Intelligent and Informatics Vol. 3 No. 2 (2022)
Publisher : Research and Social Study Institute (ReSSI)

Along with data mining, tools and software have emerged to aid in mining the vast and growing amount of data to access knowledge in databases. These tools facilitate work on most scientific disciplines, including sciences, Libraries and information. Accordingly, Data mining became an effective technique for obtaining knowledge to achieve the basic goal of discovering hidden facts that are contained in databases through the use of multiple technologies that include artificial intelligence, statistical analyzes, techniques and data modeling etc. Medical data mining is considered one of the most important tools used in the field of medicine, especially in exploring and knowing health conditions according to records of former patients. In addition, data mining helps not only in categorizing cancer but also in taking the necessary measures. With the spread of cancer at high rates around the world, the need to develop smart methods that have the ability to predict the disease appeared. Applications of data mining techniques spread as human attempts to control this deadly disease, with the aim of awareness, early detection and reduction of treatment costs. This prompted the researcher's curiosity to know the ability of data mining to categorize cancer. This work aims at reviewing ways to solve one of the problems that doctors suffer from, which is the problem of diagnosing diseases that lead to death, including cancer, as there is huge information that has not been used. Therefore, this work tries to solve this problem using data mining technology in addition to helping doctors make the right decision. The study reached several conclusions, namely the fact that the studies presented in the paper demonstrated the effective role of data mining techniques in reducing medical errors in terms of their ability to predict and accurately diagnose the disease, as well as the effectiveness of the algorithms of the data mining technique in predicting the presence of the disease at an early stage. Thus, we found that the clinical field needs to expand research, foster new kinds of calculations, and apply them practically speaking to create the best and most precise outcomes and even to supplant or surpass specialists' performance at this level..

The role of data mining in diagnosing the diseases: A case study of detecting the thyroid disease Nariman Khaled Hambeishi; Shaymaa Abed Hussein; Waleed Khalid AlAzzawi
International Journal Artificial Intelligent and Informatics Vol. 3 No. 2 (2022)
Publisher : Research and Social Study Institute (ReSSI)

One of the most important tools used in the field of medicine is to search for data, especially in the field of exploration and knowledge of the prevailing health conditions, research into diseases and patient behavior in society, as well as contribute to knowing the effect of drugs and drugs on patients according to previous patient records. Data mining also helps to identify diseases spread in a specific area, which helps to take the necessary measures and awareness to control this disease, and works to develop and update the field of medicine and medicines and increase their spread. Efficiency and processing capacity. Data mining techniques are a recent method in the medical field, and have become increasingly reliable in diagnosing diseases especially in diagnosing and detecting thyroid diseases. Since such techniques help to properly analyze and accurately predict the disease, they contribute to helping physicians, providing appropriate medical care, and reducing the incidence or development of side effects of the disease. Today, data mining techniques are important in the medical field as they help detect diseases and epidemics that are spreading around the world. The purpose of this paper is to know the role of data mining techniques in the diagnosis of thyroid disease through the survey of a number of relevant studies. The critical appraisal tool of previous studies in this area has been used. The study has also found the importance of early diagnosis of thyroid diseases, providing proper treatment for patients. It also agreed on the importance of data mining tools such as neural networks, Machine and decision tree learning and their disease diagnosis potential. The paper recommends the need for extensive systematic reviews of studies on the use of data mining techniques in the diagnosis of thyroid diseases. Also, we concluded that Prospecting tools in medical devices have had an enormous and important impact on the health care industry and the country. It should be remembered that the medical data that began to multiply in a large amount must be contained herein a lot of useful information that greatly affects the improvement of the level of medical services and detection in Characteristics of many diseases and epidemics and find solutions to many difficult diseases.

Data mining with its role in marketing, sales support and customer identification data analysis Mohammed Bin Ali Al Atif; Ahmed H. Shakir; Ahmed Kateb Jumaah Al Nussairi; Jamal Mohammed; Ali Saad Alwan Almusawi
International Journal Artificial Intelligent and Informatics Vol. 3 No. 2 (2022)
Publisher : Research and Social Study Institute (ReSSI)

In the current times, large amounts of data are collected in databases in various fields for exapmple the retail market, banking, and medical care. However, for users, complete information is not necessarily helpful. Along these lines, separate helpful data from a lot of information. This valuable information extraction measure is called information mining or information disclosure and information measure (KDD). The entire course of finding and deciphering designs from information incorporates many advances, like choice, pre-preparing, change, information extraction and translation. Information mining supports venture promoting. Also nowadays, it is no longer possible for a company to succeed without relying on data-driven statistics to understand the needs of customers in this rapidly evolving world. Henceforth, there has become an urgent need to analyze data in order to develop products based on customer needs and desires. Companies can no longer be satisfied with just advertising campaigns to attract or retain customers. Data analysis also helps to reshape relationships and interactions with customers, and to market products more effectively, which leads to stimulating and increasing sales. This article aimed not only at identifying the role of data analysis and its use in the field of marketing and sales, but also at revealing the extent of the impact of data analysis and exploration on marketing and sales. It also showed that the forces of competition that pervade the business world are the ones that exert pressure over the market operating companies to work efficiently and effectively to maintain and increase their market share, and then achieve profitability and therefore the benefit of shareholders. To achieve the study objectives, the researcher used the descriptive method and a critical review of the theoretical literature and previous studies related to the topic. The study found that data analysis technology plays an essential role for every element of customer relationship management. Through data analysis applications, the project can transform the vast number of records in its clients' database into an integrated picture of its clients. The study also recommended companies that deal with huge amounts of data to use data mining techniques because of their analytical capabilities that help the company convert its customers’ data into useful information to be used in making relationship management decisions with them.

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Editorial Address Prenggan, Kotagede, Kota Yogyakarta, Daerah Istimewa Yogyakarta 55172, Indonesia

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Contact Name
-

Contact Email
journal.ijarlit@gmail.com

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-

Journal Mail Official
journal.ijarlit@gmail.com

Editorial Address
Prenggan, Kotagede, Kota Yogyakarta, Daerah Istimewa Yogyakarta 55172, Indonesia

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA