cover
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota yogyakarta,
Daerah istimewa yogyakarta
INDONESIA
International Journal of Informatics and Communication Technology (IJ-ICT)
ISSN : 22528776     EISSN : 27222616     DOI : -
Core Subject : Science,
International Journal of Informatics and Communication Technology (IJ-ICT) is a common platform for publishing quality research paper as well as other intellectual outputs. This Journal is published by Institute of Advanced Engineering and Science (IAES) whose aims is to promote the dissemination of scientific knowledge and technology on the Information and Communication Technology areas, in front of international audience of scientific community, to encourage the progress and innovation of the technology for human life and also to be a best platform for proliferation of ideas and thought for all scientists, regardless of their locations or nationalities. The journal covers all areas of Informatics and Communication Technology (ICT) focuses on integrating hardware and software solutions for the storage, retrieval, sharing and manipulation management, analysis, visualization, interpretation and it applications for human services programs and practices, publishing refereed original research articles and technical notes. It is designed to serve researchers, developers, managers, strategic planners, graduate students and others interested in state-of-the art research activities in ICT.
Arjuna Subject : -
Articles 462 Documents
Analyzing performance of deep learning models under the presence of distortions in identifying plant leaf disease Neha Sandotra; Palak Mahajan; Pawanesh Abrol; Parveen Kumar Lehana
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 12, No 2: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v12i2.pp115-126

Abstract

Convolutional neural networks (CNN) trained using deep learning (DL) have advanced dramatically in recent years. Researchers from a variety of fields have been motivated by the success of CNNs in computer vision to develop better CNN models for use in other visually-rich settings. Successes in image classification and research have been achieved in a wide variety of domains throughout the past year. Among the many popularized image classification techniques, the detection of plant leaf diseases has received extensive research. As a result of the nature of the procedure, image quality is often degraded and distortions are introduced during the capturing of the image. In this study, we look into how various CNN models are affected by distortions. Corn-maze leaf photos from the 4,188-image corn or maize leaf Dataset (split into four categories) are under consideration. To evaluate how well they handle noise and blur, researchers have deployed pre-trained deep CNN models like visual geometry group (VGG), InceptionV3, ResNet50, and EfficientNetB0. Classification accuracy and metrics like as recall and f1-score are used to evaluate CNN performance.
Artificial intelligence based prediction on lung cancer risk factors using deep learning Muhammad Sohaib; Mary Adewunmi
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 12, No 2: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v12i2.pp188-194

Abstract

In this proposed work, we identified the significant research issues on lung cancer risk factors. Capturing and defining symptoms at an early stage is one of the most difficult phases for patients. Based on the history of patients records, we reviewed a number of current research studies on lung cancer and its various stages. We identified that lung cancer is one of the significant research issues in predicting the early stages of cancer disease. This research aimed to develop a model that can detect lung cancer with a remarkably high level of accuracy using the deep learning approach (convolution neural network). This method considers and resolves significant gaps in previous studies. We compare the accuracy levels and loss values of our model with VGG16, InceptionV3, and Resnet50. We found that our model achieved an accuracy of 94% and a minimum loss of 0.1%. Hence physicians can use our convolution neural network models for predicting lung cancer risk factors in the real world. Moreover, this investigation reveals that squamous cell carcinoma, normal, adenocarcinoma, and large cell carcinoma are the most significant risk factors. In addition, the remaining attributes are also crucial for achieving the best performance.
Architectural pattern for service collaboration Agon Memeti; Betim Cico
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 12, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v12i1.pp12-22

Abstract

The aim of this paper is to propose a modeling framework, tailored to build efficient, elastic and autonomous applications from tasks and services. It includes integrated services to develop the software products, reusing on demand in-house services with specific requirements and flexible the representational state transfer (REST) services. The idea is to decouple authorization for reduced service dependency and to provide a possibility for developing the whole application by increasing the existing application flexibility. Based on the fact that there are different web application platforms that serve to offer services to users but they are not integrated; we propose a framework with high flexibility degree, especially integrating the most used services such: e-learning, administrative, and library services, as University services are concern.
Statistical analysis of an orographic rainfall for eight north-east region of India with special focus over Sikkim Pooja Verma; Amrita Biswas; Swastika Chakraborty
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i3.pp185-192

Abstract

Autoregressive integrated moving average (ARIMA) models are used to predict the rain rate for orographic rainfall over a long period of time, from 1980 to 2018. As the orographic rainfall may cause landslides and other natural disaster issues. So, this study is very important for the analysis of rainfall prediction. In this research, statistical calculations have been done based on the rainfall data for twelve regions of India (Cherrapunji, Darjeeling, Dawki, Ghum, Itanagar, Kanchenjunga, Mizoram, Nagaland, Pakyong, Saser Kangri, Slot Kangri, and Tripura) from the eight states, i.e., Sikkim, Meghalaya, West Bengal, Ladakh (Union Territory of India), Arunachal Pradesh, Mizoram, Tripura, and Nagaland) with varying altitudes. The model's output is assessed using several error calculations. The model's performance is represented by the fit value, which is reliable for the north-east region of India with increasing altitude. The statistical dependability of the rainfall prediction is shown by the parameters. The lowest value of root mean square error (RMSE) indicates better prediction for orographic rainfall
Subarrays of phased-array antennas for multiple-input multiple-output radar applications Syahfrizal Tahcfulloh; Muttaqin Hardiwansyah
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i3.pp218-228

Abstract

The subarray MIMO radar (SMIMO) is a multiple-input multiple-output (MIMO) radar with elements in the form of a sub-array that acts as a phased array (PAR), so it combines at the same time the key advantage of the PAR radar, which is high directional gain to increase target range, and the key advantage of the MIMO radar, i.e., high diversity gains to increase the maximum number of detected targets. Different schemes for the number of antenna elements in the transceiver zones, such as uniform and/or variable, overlapped and non-overlapped, significantly determine the performance of radars as virtual arrays (VARs), the maximum number of detected targets, the accuracy of target angle, detection resolution, SNR detection, and detection probability. Performance is also compared with the PAR, the MIMO, and the phased MIMO radars (PMIMO). The SMIMO radar offers great versatility for radar applications, being able to adapt to different shapes of the multiple targets to be detected and their environment. For example, for a transmit-receive with an antenna element number, i.e., M=N=8, the range of the number of detected targets for the SMIMO radar is flexible compared to the other radars. On the other hand, the proposed radar's signal-to-noise ratio (SNR) detection performance and detection probability (K=5, L=3) are both 1,999 and above 90%, which are better than other radars.
Single line noise cancellation using derivative of normalized least mean square algorithm Rathnakara Srinivasa Pandit; Udayashankara Veerappa
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 12, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v12i1.pp38-45

Abstract

Suppression of noise in noisy speech signal is required in many speech enhancement applications like signal recording and transmission from one place to other. In this paper a novel single line noise cancellation system is proposed using derivative of normalized least mean spare algorithm. The proposed system has two phases. The first phase is generation of secondary reference signal from incoming primary signal itself at initial silence period and pause between two words, which is essential while adaptive filter using as noise canceller. Second phase is noise cancellation using proposed modified error data normalized step size (EDNSS) algorithm. The performance of the proposed algorithm is compared with normalized least mean square (NLMS) algorithm and original EDNSS algorithm using standard IEEE sentence (SP23) of Noizeus data base with different types of real-world noise at different level of signal to noise ratio (SNR). The output of proposed, NLMS and EDNSS algorithm are measured with output SNR, excessive mean square error (EMSE) and misadjustment (M). The results clearly illustrates that the proposed algorithm gives improved result over conventional NLMS and EDNSS algorithm. The speed of convergence is also maintained as same conventional NLMS algorithm.
Real-time Wi-Fi network performance evaluation Juwita Mohd Sultan; Izzah Artikah Osmadi; Zahariah Manap
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i3.pp193-205

Abstract

The most critical parameters that indicate the Wi-Fi network are throughput, delay, latency, and packet loss since they provide significant benefits, especially to the end-user. This research aims to investigate Wi-Fi performance in an indoor environment for light-of-sight (LOS) and non-light-of-sight (NLOS) conditions. The effect of the surrounding obstacles and distance has also been reported in the paper. The parameters measured are packet loss, the packet sent, the packet received, throughput, and latency. Site measurement is done to obtain real-time and optimum results. The measured parameters are then validated using the EMCO ping monitor 8 software. The comparison results between the measurement and the simulation are well presented in this paper. Additionally, the measurement distance is done up to 30 meters and the results are reported in the paper as well. The results indicate that the throughput value decreases with an increasing distance, where the lowest throughput value is 24.64 Mbps and the highest throughput value is 70.83 Mbps. Next, the maximum latency value from the measurement is 79 ms, while the lowest latency value is 56.09 ms. Finally, this research verified that obstacles and distances are among the contributing factors affecting the throughput and latency performance of the Wi-Fi network.
Automated detection of fake news Eslam Fayez; Amal Elsayed Aboutabl; Sarah N. Abdulkader
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 12, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v12i1.pp79-84

Abstract

During the last decade, the social media has been regarded as a rich dominant source of information and news. Its unsupervised nature leads to the emergence and spread of fake news. Fake news detection has gained a great importance posing many challenges to the research community. One of the main challenges is the detection accuracy which is highly affected by the chosen and extracted features and the used classification algorithm. In this paper, we propose a context-based solution that relies on account features and random forest classifier to detect fake news. It achieves the precision of 99.8%. The system accuracy has been compared to other commonly used classifiers such as decision tree classifier, Gaussian Naïve Bayes and neural network which give precision of 98.4%, 92.6%, and 62.7% respectively. The experiments’ accuracy results show the possibility of distinguishing fake news and giving credibility scores for social media news with a relatively high performance.
Blockchain based secure energy marketplace scheme to motivate peer to peer microgrids Muhammad Awais; Qamar Abbas; Shehbaz Tariq; Sayyaf Haider Warraich
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i3.pp177-184

Abstract

In the past few years, the trend of microgrids has been increasing very fast to reduce peak-hour costs. However, in these systems, third parties are still involved in selling surplus energy. This raises the cost of energy, and such systems have numerous operational and security barriers. These issues can be solved by the decentralized distributed system of microgrids, where a consumer can locally sell their surplus energy to another consumer. To deploy such a system, one must consider security barriers for the transaction of energy. This paper proposes a solution to these problems by devising a scheme as a marketplace where users interact with each other to buy and sell energy at better rates and get energy-generating resources on lease so that users do not have to worry about capital investment. An agreement between the owner of resources and the consumer is recorded on blockchain-based smart contracts. In this paper, a survey of well-known decentralized energy solutions is conducted. This paper also proposes an extra layer of security to leverage a shielded execution environment so that information about energy generated, utilized, and shared cannot be changed by consumers and third parties even if the system is compromised.
Microstrip patch antenna review on various parameters, methods and its applications Kannadhasan Suriyan; Nagarajan Ramaingam
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 12, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v12i1.pp32-37

Abstract

The implementations of the microstrip patch antenna for wireless local area network (WLAN) and worldwide interoperability for microwave access (WiMAX) are analyzed in the literature in this research. Dual or multiband antenna has played a significant part in meeting the expectations of wireless service in this quickly developing world of wireless communication. Basically, a transitory guide, an antenna is a device that emits or absorbs radio waves. Numerous benefits exist for microstrip patch antennas, including affordability, portability, simplicity of construction, and compatibility with integrated circuits. This has several important uses in the military, radar, mobile communications, global positioning system (GPS), remote sensing, and more. In mobile devices like portable computers and smartphones, WLAN and WiMAX are often used.