Wednesday, November 30, 2022

Journal of Information and Communication Technology (JICT) Vol.21, No.4, October 2022

 
USER EXPERIENCE DIMENSIONS FOR E-PROCUREMENT: A SYSTEMATIC REVIEW
Nor Laily Hashim, Norhanisha Yusof, Azham Hussain & Marhaiza Ibrahim
 
CONSTRUCTION OF AIR POLLUTION INDEX WITH THE INCLUSION OF AGGREGATED WEIGHTS OF THE POLLUTANTS
Nur Syamimi Muhamad Fauzi, Maznah Mat Kasim & Nor Hasliza Mat Desa

 

 
USER EXPERIENCE DIMENSIONS FOR E-PROCUREMENT: A SYSTEMATIC REVIEW
*1Nor Laily Hashim, 1Norhanisha Yusof, 1Azham Hussain & 2Marhaiza Ibrahim
1School of Computing, Universiti Utara Malaysia, Malaysia
2Tunku Puteri Intan Safinaz School of Accountancy, Universiti Utara Malaysia, Malaysia 
laily@uum.edu.my; norhanishayusof.education@gmail.com; azham.h@uum.edu.my; marhaiza@uum.edu.my
*Corresponding author
 
 
ABSTRACTThe use of e-procurement is needed for business transactions, especially regarding procurement activities. However, system users always demand and expect to use the system without problems. Existing studies on e-procurement do not focus on user experience (UX). Only a few studies have identified dimensions for UX evaluation; however, they are for e-government online services and construction. Identifying the UX dimensions for e-procurement is important for measuring user experience to provide better services. Therefore, this study attempted to investigate and determine the dimensions of user experience for e-procurement. The method for selecting articles was adopted from the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). The study analysed the data using thematic analysis based on the Systems and software Quality Requirements and Evaluation (SQuaRE) standards, such as ISO 25022:2016 and ISO 25023:2016, as guidance. The findings showed that among the most used UX dimensions in the e-procurement literature were satisfaction, security, transparency, efficiency, and reliability. Other UX-related dimensions identified from the review were usability, compatibility, effectiveness, performance efficiency, functional suitability, attractiveness, explainability, fairness, and visibility. The study was conducted to identify the UX dimensions for e-procurement from literature studies by organising them using ISO 25022:2016 and ISO 25023:2016 standards. This study could serve as a guideline for designers, developers, and researchers to develop an e-procurement system by referring to the proposed UX dimensions to produce a positive user experience. Moreover, the findings are beneficial to practitioners on software quality attributes.
 
Keywords: User experience, UX, UX dimension, E-procurement, Systematic review
 
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CONSTRUCTION OF AIR POLLUTION INDEX WITH THE INCLUSION OF AGGREGATED WEIGHTS OF THE POLLUTANTS
*1 Nur Syamimi Muhamad Fauzi, 2 Maznah Mat Kasim & 3 Nor Hasliza Mat Desa
1,2 Department of Decision Science, School of Quantitative Sciences, Universiti Utara Malaysia, 06010 UUM Sintok, Kedah, Malaysia.
3Department of Statistics, School of Quantitative Sciences, Universiti Utara Malaysia, 06010 UUM Sintok, Kedah, Malaysia
*nur_syamimi6@ahsgs.uum.edu.my; maznah@uum.edu.my; nliza@uum.edu.my
*Corresponding author 
 
 
ABSTRACT
 
The ambient air quality measurement in Malaysia is described as Air Pollution Index (API). Basically the existing API for a given period of time is defined as the maximum value of the sub-index values of six pollutants. Although research has shown that long and short term exposure to air suspended toxicants has a different toxicological impact on human, the API still considers these pollutants as having equal hazardous impacts on human. Hence, this paper aims to propose a new API that includes weights representing different hazardous levels of these pollutants in its calculation. Based on secondary data of six pollutants’ readings for sixteen states of Malaysia for year 2018, the aggregated weights were computed by combining both weights obtained from the subjective experts’ opinions and the objective data-driven methods, which balanced both perspectives of evaluations. The results show that the particulate matter with aerodynamic diameter less than 2.5 micrometre (PM2.5) found to be the most hazardous pollutant since its aggregated weight value is the highest and the distributions of the API readings for all sixteen states were found to be normal. The highest and lowest API readings took place on the 14th of August and 10 of March 2018 respectively. It is argued that the new API readings are more accurate and give a better picture about the occurrence of air pollution in Malaysia in particular. This study provides a new insight in constructing API specifically and contributes a more comprehensive and precise air quality measurements to be analysed by the responsible authorities in their efforts towards healthy environment.
 
Keywords: Aggregated weights, Air pollution, Hazardous levels, Objective weighting method, Subjective weighting method
 
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TOPSIS-BASED REGRESSION ALGORITHMS EVALUATION
Ahmad Adel Abu-Shareha
Department of Computer Science, Faculty of Information Technology, Al-Ahliyya Amman University, Amman, Jordan
a.abushareha@ammanu.edu.jo
 
 
ABSTRACT
 
This paper developed a multi-criteria decision-making approach using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to benchmark the regression alternatives. Regression is used in diverse fields to predict consumer behavior, analyze business profitability, assess risk, analyze automobile engine performance, predict biological system behavior, and analyze weather data. Each of these applications has its own set of concerns, resulting in various metrics utilizations or those of similar measures but with diverse preferences. Multi-criteria decision-making analyzes, compares, and ranks a set of alternatives utilizing mathematical and logical processes with a complicated and contradictory set of criteria. The developed approach established the weights, which were the core of the evaluation process, to various values to mimic and address the regression’s utilization in multiple applications with different concerns and using distinct datasets. The alternative judgment identified positive and negative ideal alternatives in the alternative space. The compared regression alternatives were scored and ranked based on their distance from these alternatives. The results showed that different preferences led to varying algorithm rankings, but top-ranked algorithms were distinguished using a specific dataset. Following that, using three datasets, namely Combined Cycle Power Plant, Real Estate, and Concrete, Voting using multiple classifiers (k-means-based classifiers) was the top-ranked in the Combined Cycle Power Plant and Real Estate datasets. In contrast, Decision Stump was the top-ranked in the Concrete dataset.
 
Keywords: Multi-criteria decision making, Regression, TOPSIS.
 
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THE COMPARISON BETWEEN STANDARDIZED MORTALITY RATIO, POISSON-GAMMA AND STOCHASTIC SIC MODEL FOR PNEUMONIA DISEASE MAPPING IN MALAYSIA
*1Ijlal Mohd Diah & 1,2Nazrina Aziz
1Department of Mathematics and Statistics, School of Quantitative Sciences, Universiti Utara Malaysia, Malaysia
2Institute of Strategic Industrial Decision Modelling (ISIDM), Universiti Utara Malaysia, Malaysia
 ijlal_ti_mohd@ahsgs.uum.edu.my,  nazrina@uum.edu.my
*Corresponding author
 
 
ABSTRACT
 
Pneumonia is one of the primary causes of death from infectious diseases. Traditionally, its spread has been tracked based on the total number of cases reported, with no concern for geographical distribution. Disease mapping is among the ways public health and the government can monitor diseases as a preventative strategy. Clear pictures of the risk areas can be seen using this method. Relative risk estimation is a significant part of disease mapping that needs to be considered when studying disease occurrence. This paper aimed to estimate the relative risk values for pneumonia based on three models and compare the results. The approaches used in this study were Standardized Morbidity Ratio (SMR), Poisson-gamma, and discrete time-space stochastic Susceptible-Infected-Carriers (SIC) models, which were applied in estimating the relative risk values. Results showed that Kuala Lumpur was classified as a very low-risk area for pneumonia incidence when using the SMR and Poisson-gamma models. In contrast, Selangor was identified as a very low-risk area when using the discrete time-space stochastic SIC model. Putrajaya was categorised as a very high-risk area in the results of all three types of methods. In conclusion, this stochastic SIC model demonstrated better performance than the conventional models.
 
Keywords: disease mapping, Poisson-gamma, pneumonia, SIC model, SMR.
 
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A META-HEURISTIC ALGORITHM FOR THE MINIMAL HIGH-QUALITY FEATURE EXTRACTION OF ONLINE REVIEWS
1*Harnani Mat Zin, 2Norwati Mustapha, 2Masrah Azrifah Azmi Murad, & 2Nurfadhlina Mohd Sharef
1Computing Department, Faculty of Computing, Arts & Creative Industry, Universiti Pendidikan Sultan Idris, Malaysia
2Department of Computer Science, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Malaysia
harnani@fskik.upsi.edu.my;  norwati@fsktm.upsi.edu.my;  masrah@fsktm.upm.edu.my;  nurfadhlina@fsktm.upm.edu.my
*Corresponding author
 
 
ABSTRACT
 
Feature extraction and selection are critical in sentiment analysis (SA) to extract and select only the appropriate features by removing those deemed redundant. As such, the successful implementation of this process leads to better classification accuracy. Inevitably, selecting high-quality minimal features can be challenging given the inherent complication in dealing with over-fitting issues. Most of the current studies used a heuristic method to perform the classification process that will result in selecting and examining only a single feature subset, while ignoring the other subsets that might give better results. This study explored the effect of using the meta-heuristic method together with the ensemble classification method in the sentiment classification of online reviews. Adding to that point, the extraction and selection of relevant features used feature ranking, hyper-parameter optimization, crossover, and mutation, while the classification process utilized the ensemble classifier. The proposed method was tested on the polarity movie review dataset v2.0 and product review dataset (books, electronics, kitchen, and music). The test results indicated that the proposed method significantly improved the classification results by 94%, which far exceeded the existing method. Therefore, the proposed feature extraction and selection method can help in improving the performance of SA in online reviews and, at the same time, reduce the number of extracted features. 
 
Keywords: feature extraction, feature selection, online reviews, meta-heuristics, sentiment analysis.
 
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GUARANTEEING PERFORMANCE IN A FAULT TOLERANT ARCHITECTURE SOLUTION USING SOFTWARE AGENT’S COORDINATION
Festus Oliha
Department of Computer Science, University of Benin, Nigeria
oliha_festus@uniben.edu
 
 
ABSTRACT
 
Performance is a critical attribute in evaluating the quality and dependability of service-oriented systems dependent on fault-tolerant architectures. Fault-tolerant architectures have been implemented with redundant techniques to ensure fault-tolerant services. However, replica-related overhead burdens fault-tolerant techniques with associated performance degradation in service delivery, and this consequentially discourages service consumers with discredits for service providers. In this paper, a fault-tolerant approach that adopts replication and diversity was employed on agent-oriented coordination toward guaranteeing the performance of the proposed fault-tolerant architecture solution under a large-scale service request load. In addition, the resultant architecture solution was simulated with Apache JMeter for performance evaluation considering the performability in the absence and presence of a fault load. The simulation experiments and results revealed the architecture’s efficiency in fault tolerance via the timely coordination of logical and replica-related activities by software agents. Noteworthily, the continued service availability and performance were guaranteed for the architecture solution with a significant rate of regularity in the absence and presence of a replica-related fault. Therefore, this study’s performance evaluation methods and results could serve as a veritable milestone for building fault-tolerant service systems with appreciable performability and contribute to the service-oriented fields where performance is inevitable.
 
Keywords: web services, service-oriented systems, fault-tolerant architecture, fault tolerance, performance, software agents, replication, diversity, computational intelligence.
 
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PROBABILISTIC MULTI-TIERED GREY WOLF OPTIMIZER-BASED ROUTING FOR SUSTAINABLE SENSOR NETWORKS
*1Vasudha Bahl & 2Anoop Kumar
1,2Department of Computer Science Engineering, Banasthali Vidyapith, India
vasudhabahl@mait.ac.inanupbhola@banasthali.in
*Corresponding author
 
 
ABSTRACT
 
Wireless sensor networks have a wide range of applications, so developing an energy-efficient methodology for the estimation of cluster heads (CHs) to ensure efficient data transmission has become highly relevant. Meta-heuristic strategies for optimal CHs are current investigation inclination.  As the network grows the conventional optimization strategies turn out to be unsuccessful and the outcomes of hybridizing brings performance enhancement in WSN. So, Probabilistic Multi-tiered GWO is implemented on an upgraded Grey Wolf Optimizer for optimum CH selection. It uses fitness value to strengthen GWO's search for the best solution, resulting in even dispersal of CHs. Communication routes are updated based on routes to the CHs and base station to lessen energy consumption by a layered-based routing scheme. The grey wolf's governance enhances the network's ability. The distributed nodes' geographical territory is categorized as 4-tiers. CH is chosen grounded on the objective value that requires fewer difficult control factors than existing techniques. Simulations show suggested technique can extend the network's stability- time by 31.5% compared to hetDEEC-3, DDRI-LEACH, Novel-LEACH POS, DBSCDS-GWO, and P-SEP.
 
Keywords: Cluster Head, Energy Optimization, Grey Wolf Optimization, Cluster Head selection, Wireless Sensor Network Lifespan.
 
 
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