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International Journal of Informatics and Communication Technology (IJ-ICT)
Published by Institute of Advanced Engineering and Science
ISSN : 22528776     EISSN : 27222616     DOI : -
Core Subject : Science,
Computer Science & IT
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 35 Documents
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Search results for , issue "Vol 14, No 1: April 2025" : 35 Documents clear
Strategic Deployment of EV Charging Infrastructure: An In-Depth Exploration of Optimal Location Selection and CC-CV Charging Strategies Mishra, Debani Prasad; Nayak, Pranav Swaroop; Kumar, Aman; Salkuti, Surender Reddy
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 14, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v14i1.pp259-267

Abstract

The continued expansion of the electric vehicle (EV) market necessitates strategic planning for the placement of charging stations to ensure efficient access and utilization of electric infrastructure. This paper presents a comprehensive review of the critical factors in optimizing the selection of EV charging station locations, along with the implementation of Constant Current-Constant Voltage (CC-CV) charging models. The study addresses the challenges and opportunities in identifying the most effective locations for charging stations to accommodate the growing demand for sustainable transportation. Furthermore, it examines the benefits of adopting CC-CV charging models to improve the charging process, achieving a balance between charging speed and battery longevity. Through this analysis, the review aims to provide valuable insights to stakeholders involved in the development and expansion of EV charging infrastructure, thereby supporting the transition to a more sustainable and extensive electric mobility ecosystem.
Enhanced pulse shaping filters for minimizing interference in GFDM signals for 5G cellular networks Tadikamalla, Sairam Vamsi; Mohanta, Harish Chandra; Terlapu, Sudheer Kumar; Mandhapati, Vamshi Krishna
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 14, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v14i1.pp153-163

Abstract

The imminent rise of 5th generation (5G) wireless standards heralds a pivotal era in cellular communication. Among the challenges faced, selecting an optimal multiple access technique stands out as crucial for achieving the desired blend of low latency, high data rates, and throughput. Generalized frequency division multiplexing (GFDM) emerges as a promising can-didate meeting 5G requirements. This study introduces two innovative pulse shaping filters (PSFs) the better than raised cosine filter (BRCF) and modified bartlett hanning filter (MBHF) paired with various modulation schemes such as binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), and quadrature amplitude modulation (QAM) to assess GFDM signal performance. Considering its spectrum efficiency, QAM modulation emerges as the preferred choice. Performance evaluation of the PSFs entails analyzing symbol error rate (SER) against signal to noise ratio (SNR) across different modulation schemes.
A system architecture for mixed reality systems in vocational schools in Indonesia Suryodiningrat, Satrio Pradono; Prabowo, Harjanto; Ramadhan, Arief; Santoso, Harry Budi
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 14, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v14i1.pp207-215

Abstract

In Indonesia, vocational schools are less favored compared to K -12 schools. Unfortunately, graduates from vocational schools do not fulfill the minimum requirements set by industries, particularly in the current era of industry revolution 5.0. This revolution aims to establish society 5.0, where humans and robots collaborate closely to achieve improved work outcomes. One technique to enhance the proficiency of graduates and prepare them for the workforce is by implementing a mixed-reality system. that will effectively address a multitude of issues and significantly enhance the caliber of graduates and before the implementation of mixed reality (MR) systems, it is necessary to create system architecture diagrams to ensures that the system can be utilized not only in specific schools but also in any vocational school in Indonesia. This study comprises 5 participants, including experts from both the professional and academic fields, who possess extensive knowledge in the domains of metaverse, MR systems, and information systems. The methodology employed in this study draws inspiration from James Martin’s rapid application development (RAD). The result of this study is a validated system architectural diagram, endorsed by experts, which depicts a metaverse-based MR system designed specifically for vocational schools in Indonesia
Srvycite: a hybrid scientific article recommendation system R, Sivasankari; Dhilipan, J
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 14, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v14i1.pp216-228

Abstract

A recommendation system is becoming part of every work done today to reduce the effort of work done by the users in searching for items in need by recommending new items that may be useful. This theme has also been used in research article recommendation systems for recommending articles of interest to researchers from a bulk of digital research documents spread across different databases on the internet. To ease the task of this article recommendation process, we have proposed a novel approach, Srvycite, by utilizing the survey article citation network along with the original research article network. The purpose of utilizing the survey article citation network is to detect the most influential articles that are considered to be important by other researchers in the same field. The Srvycite approach utilizes the text and meta features of articles to recommend papers. To preprocess the text features utilized, we have employed Word2Vec and bidirectional encoder representations from transformers (BERT) for vectorization. Then citation graph and survey citation graphs are generated to find the most influential nodes. The weighted text similarity score is finally computed by combining the cited by values and the text similarity score from the citation and survey citation graph to list articles as recommendations for the user. This system is proven to increase the accuracy of the article recommendation by 3.8 and 2.1 in the case of the precision and recall measures for performance evaluation.
Pilot study on deploying a wireless sensor-based virtual-key access and lock system for home and industrial frontiers Eboka, Andrew Okonji; Aghware, Fidelis Obukohwo; Okpor, Margaret Dumebi; Odiakaose, Christopher Chukufunaya; Okpako, Ejaita Abugor; Ojugo, Arnold Adimabua; Ako, Rita Erhovwo; Binitie, Amaka Patience; Onyemenem, Innocent Sunny; Ejeh, Patrick Ogholuwarami; Geteloma, Victor Ochuko
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 14, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v14i1.pp287-297

Abstract

The rise in data processing activities vis-à-vis the consequent rise in adoption and adaptation of information and communication tech related approaches to resolve societal challenges has become both critical and imperative. Virtualization have become the order of the day to bridge various lapses of human mundane tasks and endeavors. Its positive impacts on society cannot be underestimated. This study advances a virtual wireless sensor-based key-card access system with cost-effective solution to manage access to restricted areas within a facility. We seek to integrate virtual key card access, web-access control, solenoid lock integration, and ESP32- controller to create a dependable internet of things (IoT)-enabled access control system. Results show system benefit includes improved security, improved convenience, privacy, efficiency with real-time control capabilities that will allows building administrators to track and manage access to the facility remotely.
Real time hand gesture detection by using convolutional neural network for in-vehicle infortainment systems Yaakob Wan Bejuri, Wan Mohd; Asmai, Siti Azira; Ikram, Raja Rina Raja; Rahim, Nur Raidah; Khambari, Najwan; Azmi, Mohd Sanusi; Sholva, Yus
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 14, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v14i1.pp42-49

Abstract

Nowadays, a variety of technologies on autonomous vehicles have been extensively developed, including in-vehicle infotainment (IVI). It have been noted as one of the key services in the automobile industry. In the near future, people will be able to watch some virtual reality (VR) movies through the streaming service provided in the vehicle. However, a person sometime not tend to be joy while watching espcially when the remote controller or audio sensory controller lack of battery or too far from IVI panel. Thus, the purpose of this research is to design a scheme of real time hand gesture detection for in-vehicle infotainment system, in order to create human computer experience. In this research, the image of human palm hand will be taken by using camera for recognize the hand gesture action. This proposed scheme will recognize human gesture and convert to be computer intruction, that can be understood by IVI device. As a result, it show our proposed scheme can be the most consistent in term of accuracy and loss compared to others method. Overall, this research represents a significant step toward improving better user experience. Furthermore, the proposed scheme is anticipated to contribute significantly to the IVI field, benefiting both academia and societal outcomes.
Predictive model for converting leads into repeat order customer using machine learning Maured, Deryan Everestha; Kusuma, Gede Putra
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 14, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v14i1.pp20-30

Abstract

In the competitive business landscape, customer relationship management (CRM) is pivotal for managing customer relationships. Lead generation and customer retention are critical aspects of CRM as they contribute to sustaining business growth and profitability. Also, identifying and converting leads into repeat customers is essential for optimizing revenue and minimizing promotional costs. This study focuses on developing a predictive model using machine learning techniques to convert leads into repeat order customers in conventional businesses. Leveraging data from a motorcycle distribution company in Jakarta and Tangerang, the study compares the performance of various models for predicting repeat orders. This includes individual models like DeepFM, random forest, and gradient boosting decision tree models. Additionally, it explores the effectiveness of stacking these models using logistic regression as a meta-learner. Furthermore, the study implements backward feature elimination for feature selection and hyperband for hyperparameter tuning to enhance model performance. The results indicate that Stacking model using base model default configuration stands out as the most robust, achieving the highest scores in accuracy (0.95), area under the curve receiver-operating characteristic curve (AUC-ROC) (0.67), log loss (0.19), weighted average precision (0.95), weighted average recall (0.95), and weighted average F1- score (0.92), effectively handling the imbalanced dataset.
Conceptualization of IoT architectures Paolone, Gaetanino; Paesani, Romolo; Camplone, Jacopo; Piazza, Andrea; Di Felice, Paolino
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 14, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v14i1.pp334-346

Abstract

Although there is a large interest about internet of things (IoT) architectures, still there is no consensus on their conceptualization in the extant literature. This lack of information in conceptualization is problematic because it hampers the deep understanding of the appeared proposals, as well as the adoption of a shared workflow by the involved architects of these systems. Thus, a concise and agreed-upon conceptualization of IoT architectures is called for. This paper aims at giving a contribution on the topic. We start by reviewing the available standards, then, in light of their suggestions, a workflow to be followed in the definition of the architecture descriptions (ADs) of IoT systems is detailed and, in addition, a sample case study, which implements that workflow, is proposed. The contributions are sufficiently abstract to be applicable also to the description of the architecture of artificial intelligence of things (AIoT) systems.
Efficient blockchain based solution for secure medical record management Mishra, Debani Prasad; Rajeev, B; Mallick, Soubhagya Ranjan; Lenka, Rakesh Kumar; Salkuti, Surender Reddy
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 14, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v14i1.pp59-67

Abstract

Electronic medical records (EMRs) have become a key player in the healthcare ecosystem contributing to the assessment of ailments, the choice of the treatment avenue, and the delivery of services. However, there is consideration of EMR storage whereby centralized storage leads to increased security and privacy issues in the patient’s record. In this paper, we proposed a blockchain and interplanetary file system (IPFS) based prototype model for EMR management. It provides a smart contract-enabled decentralized storage platform where healthcare data security, availability, and access management are prioritized. This model also employs cryptographic techniques to protect sensitive healthcare data. Finally, the model is evaluated in a realistic scenario. The experimental results demonstrate that compared to the current systems, the proposed prototype model outperforms them in terms of efficiency, privacy, and security.
Prediction of international rice production using long short-term memory and machine learning models Arya, Suraj; Anju, Anju; Ramli, Nor Azuana
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 14, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v14i1.pp164-173

Abstract

Rice, a staple food source globally, is in high demand and production across the world. Its consumption varies in different countries, with each nation having its unique way of incorporating rice into its diet. Recognizing the global nature of rice, its production is a crucial aspect of ensuring its availability, agriculture forecasting, economic stability, and food security. By predicting its production, we can develop a global plan for its production and stock, thereby preventing issues like famine. This paper proposes machine learning (ML) and deep learning (DL) models like linear regression, ridge regression, random forest (RF), adaptive boosting (AdaBoost), categorical boosting (CatBoost), extreme gradient boosting (XGBoost), gradient boosting, decision tree, and long short-term memory (LSTM) to predict international rice production. A total of nine ML and one DL models are trained and tested on the international dataset, which contains the rice production details of 192 countries over the last 62 years. Notably, linear regression and the LSTM algorithm predict rice production with the highest percentage of R-squared (R2 ), 98.40% and 98.19%, respectively. These predictions and the developed models can play a vital role in resolving crop-related international problems, uniting the global agricultural community in a common cause.

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