Quality Of Service For Applications Research Articles

Defining Service Quality of BRI Merchant Application Using Importance Performance Analysis

The COVID-19 pandemic has changed people's habits worldwide, accelerating the adoption of cashless payment transactions, especially in Indonesia. This situation allows Financial Technology companies and Conventional Banks to increase competition. This thesis focuses on the Digital Payments Industry in Indonesia, emphasizing the Merchant Acceptance Business, which has a crucial role as a catalyst for Cashless Payments. This research is based on previous studies regarding service quality, business model canvas, and the importance of performance analysis of the BRI Merchant Application. This research aims to define a service quality strategy for BRI merchant applications through a critical performance analysis approach. The study found that the quality of BRI merchant application services consists of changing merchant data, adding EDC, Checking transactions, reconciling Payments, filing complaints, and monitoring complaints.

A Queue Monitoring System in OpenFlow Software Defined Networks

Real-time trac characteristic is dierent and it is very sensitive to delay. To meet trac specications in real time, monitoring systems are used as an important part of networking. Many monitoring systems are deployed to have an update view of the network QoS parameters and performance. Most of these systems are implemented to measure QoS parameters in links. Here, in this paper, a system for monitoring queues in each link by means of Software Defined Networks is proposed. The monitoring system is implemented by extending Floodlight controller, which uses OpenFlow as southbound protocol. The controller has a centralized view of the network. By the help of OpenFlow it also can provide flow level statistics. Using these advantages, the proposed system can monitor delay and available bandwidth of a queue on a link or path. Despite of monitoring systems in traditional networks, the proposed monitoring system makes a low overhead in network thanks to OpenFlow protocol messages. It is also integrated into the network controller, which enables QoS and trac engineering applications to use the system's reports for automatic trac management and QoS setup. The experimental results show a 99% accuracy of the proposed system for monitoring of both bandwidth and delay.

ISwap: A New Memory Page Swap Mechanism for Reducing Ineffective I/O Operations in Cloud Environments

This paper proposes iSwap, a new memory page swap mechanism that reduces the ineffective I/O swap operations and improves the QoS for applications with a high priority in the cloud environments. iSwap works in the OS kernel. iSwap accurately learns the reuse patterns for memory pages and makes the swap decisions accordingly to avoid ineffective operations. In the cases where memory pressure is high, iSwap compresses pages that belong to the latency-critical (LC) applications (or high-priority applications) and keeps them in main memory, avoiding I/O operations for these LC applications to ensure QoS; and iSwap evicts low-priority applications’ pages out of main memory. iSwap has a low overhead and works well for cloud applications with large memory footprints. We evaluate iSwap on Intel x86 and ARM platforms. The experimental results show that iSwap can significantly reduce ineffective swap operations (8.0% - 19.2%) and improve the QoS for LC applications (36.8% - 91.3%) in cases where memory pressure is high, compared with the latest LRU-based approach widely used in modern OSes.

Persepsi Nasabah terhadap Aplikasi M-Banking pada Bank Swasta dan Bank Pemerintah

Information and communication technology has revolutionized the banking sector and at its peak during the Covid 19 pandemic, most transactions can be carried out without the need to visit a bank and using mobile banking applications. In Indonesia, there are two banks that are most popular in using m-banking, m-BCA which is managed by a private bank and Livin by Mandiri which is managed by a state-owned company. The aim of this research is to analyze whether there are differences of trust, service quality and perceived risk on customer satisfaction in private and government managed m-Banking. The research method uses a quantitative approach based on data collected through online surveys. There are 180 active m-Banking customers with generation Z and Millennial demographics, students and productive workers. The results show that the factors that influence customer satisfaction in using m-Banking lie in the aspects of service quality and trust, while perceived risk has no effect. Furthermore, differences in the influence of m-banking application service quality determine customer satisfaction. Where, m-BCA customers are relatively more satisfied because the service is in accordance with the promises, transaction speed, security, attractive visual appearance, the application is more responsive and easier than the Livin by Mandiri. For generation Z and millennials, the use of digital banking applications is more influenced by the application's ability to meet transaction needs rather than threat factors such as the speed of computing personal data, cyber-crime and bank system errors.

VALIDATING DIMENSIONS OF MOBILE SERVICE QUALITY E-COMMERCE CONSUMER TO CONSUMER (C2C) IN INDONESIA FROM SELLER'S PERSPECTIVE

Along with technological advancement, many sellers in Indonesia have shifted to use digital platform like e-commerce, which is creating potential ecosystem for various e-commerce applications to grow and face intense competition in facilitating direct transactions between consumers (C2C). This study aims to confirm the mobile service quality dimensions of e-commerce on mobile applications. The study adopts a quantitative approach with sellers who are use of popular C2C mobile applications in Indonesia, such as Tokope­dia, Shopee, Bukalapak, and TikTok Shop as the population. Sample selection using purposive technique resulted in a sample size of 313 respondents. Test­ing was conducted using Confirmatory Factor Analysis (CFA) to determine the proposed dimensions of e-commerce mobile application service quality from previous research. The results of the study confirm six factors of mobile service quality in e-commerce applications: Application Design, Reliability, Responsiveness, Trust, Efficiency, and System Availability. Testing with the modified model provides higher fit criteria. ANOVA was used to compare components in each dimension. E-commerce service providers can use the re­sult to improve service quality. These improvements involve refining the ap­plication interface, ensuring reliability, responsiveness, security, efficiency, and system availability, aiming to boost user satisfaction, foster continued app usage, and fortify the service provider's reputation.

A fine-grained robust performance diagnosis framework for run-time cloud applications

To maintain the required service quality of time-critical cloud applications, operators must continuously monitor their runtime status, detect potential performance anomalies, and diagnose the root causes of these anomalies effectively. However, existing performance diagnosis methods face challenges such as the need for high-quality labeled data, the low reusability and robustness of performance anomaly detection models, and the absence of real-time fine-grained root cause localization. These challenges make fixing performance issues quickly and developing effective adaptation decisions difficult. We provide a Fine-grained Robust Performance Diagnosis (FIRED) framework to tackle those challenges. The framework offers a metrics selection component to filter noise and improve detection efficiency, an anomaly detection component that assembles several well-selected base models with a deep neural network, and adopts weakly supervised learning considering fewer labels exist in reality. The framework also employs a real-time, fine-grained root cause localization component to locate dependent resource metrics of performance anomalies. Our experiments show that the framework can effectively reduce data noise and achieve the best accuracy and algorithm robustness for performance anomaly detection. In addition, the framework can accurately localize the first root causes, with an average accuracy higher than 0.7 for locating the first four root cause metrics.

Application of The End User Computing Satisfaction Method to Analyze User Satisfaction Toward the Quality of Mobile Banking Services

This research aims to find out how to analyze user satisfaction with the quality of mobile banking application services using the end-user computing satisfaction model. This research adopts a quantitative approach. Use of questionnaires as a data collection tool. Sampling was done using the purposive sampling technique, with a sample size of 100 respondents. Researchers conducted demographic, outer, and inner model analyses using the PLS-SEM approach via Smart-PLS. This research indicates that most mobile banking application users were satisfied with their overall use. The four hypotheses proposed, namely ease of use, perceived usefulness, and timeliness, were all accepted with solid evidence. The results of hypothesis testing show that three hypotheses have a highly significant influence on user satisfaction, namely H5 (perceived usefulness), H4 (format), and H3 (ease of use). These factors, such as user-perceived usefulness, format quality, and ease of use, provide a positive experience for users to feel satisfied with the application. However, two hypotheses are not accepted, indicating that the accuracy variable (accuracy) and content variable (content) do not significantly influence user satisfaction. The purpose of adding the perceived usefulness variable to this research is to obtain information about how practical the application is for users, and the results of the t-test show that this variable has a significant relationship with user satisfaction.

SEM - PLS in the WebQual 4.0 Method for Enhancing the Quality of Online Tutorial Learning Applications at Open Universities

Universitas Terbuka (UT, literally Open University) organizes distance learning through the Online Tutorial (Tuton) service. Tuton is an internet-based tutorial service that can be accessed via the site http://elearning.ut.ac.id by all UT students, including UPBJJ UT Denpasar students. Analysis of the quality of UPBJJ UT Denpasar student tutoring services has never been carried out before. Based on these problems, this research aims to analyze and measure the quality of Tuton application services using WebQual 4.0 dimensions, which are moderated by gender and age variables. This research uses a quantitative method approach to student satisfaction data from the UT UPBJJ Denpasar Management Study Program, who have used the Tuton application for more than three semesters. Data analysis techniques using the SEM–PLS method. Based on the results of the analysis, it was found that there was a positive influence between the usability variable, the service interaction quality variable, and the Information Quality variable on the user satisfaction variable. The gender moderating variable can act as pure moderation on the service interaction quality and Information Quality variables. Meanwhile, the age variable is a potential moderator of the three variables. From these results, it can be concluded that the service quality of the Tuton application shows a robust model on the Webqual Method indicators for user satisfaction variables, and this application is beneficial and in accordance with student needs. The learning support aspects still need to be improved, especially the speed of response time and the accuracy of the tutorial services provided by tutors.

ASSESSMENT OF SERVICE QUALITY OF PASURUAN E-SAMBAT APPLICATION WITH E-GOVQUAL DIMENSION APPROACH

Public services are government mediators in providing services to the needs of the community. The development of technology makes it easier for state and regional apparatuses to provide public services through an application called E-Government. Similarly, the Pasuruan City Communication and Information Agency has tried to organize the E-Sambat application. This study aims to provide an understanding of the quality of E-Sambat services based on the E-GovQual dimension approach, the gap between E-Sambat performance and public expectations for the E-Sambat application, and knowing which items will be prioritized to be immediately improved in the E-Sambat application. To analyze the feasibility of the application using GAP and the Important Performance Analysis (IPA) method is used to analyze items that are prioritized for improvement. Respondents in this study were 445 respondents. Based on the results of the analysis conducted, the quality of E-Sambat application services is very feasible with a feasibility percentage value of 100%, application performance GAP and public expectations for the Ease of Use variable of 0.08, Trust variable of -0.04, Functionality of the Interaction Environment variable of 0.02, Reliability variable of -0.03, Content and Information Display variable of 0.01, and the Community Support variable of 0.00. The overall average gap is 0.01 which means that people are satisfied with the E-Sambat application service. There are six items that are prioritized for improvement, namely TR 1 (security of personal data of E-Sambat users), TR 6 (access control of E-Sambat users), RLB 1 (speed in downloading E-Sambat forms), CAI 7 (use of colors in the E-Sambat application), CAI 8 (graphics in the E-Sambat application), and CS 5 (User questions answered quickly).

Effect of Livin' by Mandiri Application Service Quality on Customer Satisfaction: Study on PT Bank Mandiri (Persero) Tbk. Solo

This research tries to understand the relationship between service quality and customer satisfaction on the Livin’ by Mandiri, a mobile-banking application of Bank Mandiri. The respondents are customers of the Bank Mandiri Solo UNS Branch office. The number of respondents is 100. The data were collected by questionnaire and test using SPSS 23. The result of this study shows that service quality factors such as tangibles, reliable, assurance, and empathy positively affect customer satisfaction. When the Livin’ by Mandiri application improves in terms of the tangibility, reliability, assurance, and empathy, customer satisfaction will increase. The variable of responsiveness has no significant effect on customer satisfaction. The subject of this research is an application that cannot literally become responsive to serve customers. This research result may be important as the policy implication for Bank Mandiri to make the customers able to use the application optimally.

Analisis Pengelolaan Angkutan Penyeberangan Terhadap Kelancaran dan Keamanan Arus Penumpang dan Barang: Studi Riset pada Sistem Aplikasi Ferizy Pelabuhan Penyeberangan Merak dan Bakauheni

The main problem in service at the Merak Bakauheni Port is the lack of attention to governance, especially in the application of the ferizy application system to the smoothness and safe flow of passengers and goods. Therefore, this research aims to investigate the impact of implementation of the Ferizy application system in ticket purchases on the smoothness and safe of passengers flow and goods at the Merak-Bakauheni Ferry Port. We use quantitative methods by involving using questionnaires that have been filled by 69 respondents. Furthermore, we use the Method of Succesive Interval (MSI) to convert ordinal scale data into intervals in the utilized questionnaire and conduct inferential testing (multivariate analysis MANOVA) to answer the research hypothesis. The research results indicate that the implementation of the Ferizy application (system quality, information quality, service quality, and user satisfaction) made a significant difference to the smoothness and safe of passengers flow and goods simultaneously and partially. The findings of this study specifically discuss the difference in data results on the ferizy application and the manifest of the Sailing Approval Letter (SPB), from the Merak-Bakauheni port and the Bakauheni-Merak port.

Demystifying the QoS and QoE of Edge-hosted Video Streaming Applications in the Wild with SNESet

Video streaming applications (VSAs) are increasingly being deployed on large-scale edge platforms, which have the potential to significantly improve the quality of service (QoS) and end-user experience (QoE), ultimately maximizing business outcomes. However, there is currently very little understanding of how QoS, QoE, and the impact of QoS on QoE for VSAs on edge platforms in the wild and at scale. To close the knowledge gap, we collect SNESet, an active measurement dataset comprising QoS and QoE telemetry metrics of 8 VSAs over four months, covering end-users from 798 edge sites,30 cities, and 3 ISPs in one country.We characterize and compare the QoS and QoE metrics in SNESet with existing publicly available datasets, highlighting that SNESet includes a significantly greater number of metrics (horizontal diversity and vertical hierarchy) and provides more comprehensive coverage of specific metrics.Moreover, we qualitatively and quantitatively analyze the impact of QoS on QoE in both domain-general and domain-specific scenarios. Our findings can inform the system design decisions that different entities in the video ecosystem (content providers, video player designers, third-party optimizers, edge vendors) make to maximize end-users experience and ultimately maximize the business outcomes. We hope SNESet can attract more research efforts in the data management community, computer network community, and beyond.

UniPreCIS: A data preprocessing solution for collocated services on shared IoT

Next-generation smart city applications, attributed to the power of the Internet of Things (IoT) and Cyber–Physical Systems (CPS), significantly rely on sensing data quality. With an exponential increase in intelligent applications for urban development and enterprises offering sensing-as-a-service these days, it is imperative that a shared sensing infrastructure could thwart the better utilization of resources. However, a shared sensing infrastructure that leverages low-cost sensing devices for a cost-effective solution remains unexplored territory. A significant research effort is still needed to make edge-based data shaping solutions more reliable, feature-rich, and cost-effective while addressing the associated challenges in sharing the sensing infrastructure among multiple collocated services with diverse Quality of Service (QoS) requirements. Towards this, we propose UniPreCIS, a novel edge-based data preprocessing solution that accounts for the inherent characteristics of low-cost ambient sensors and their exhibited measurement dynamics concerning application-specific QoS. UniPreCISaims to identify and select quality data sources by performing sensor ranking and selection that dynamically adapts to the change in sensor attributes. Finally, multimodal data preprocessing is performed in a unified manner to meet heterogeneous application QoS and, at the same time, reduce the resource consumption footprint for the resource-constrained network edge. We study the effectiveness of UniPreCISon a real-world testbed deployed on our campus. As observed, the processing time and memory utilization of the stakeholder services have been reduced in the proposed approach while achieving up to 90% accuracy, which is arguably significant compared to state-of-the-art sensing techniques.

IMPROVING THE QUALITY OF PATENT REGISTRATION SERVICES: AN APPLICANT SATISFACTION PERSPECTIVE AT THE DIRECTORATE GENERAL OF INTELLECTUAL PROPERTY

Introduction/Main Objective: Good governance will create good implementation of public service functions as well. On the other hand, bad governance means that public service functions will not be carried out well. Background of the Problem: researched the influence of the quality of patent registration application services on patent applicant satisfaction with DJKI based on reability, responsive, assurance, emphaty dan tangible. Research gaps/Novelty: This research examines the influence of the quality of patent registration application services on satisfaction of patent applicants at DJKI based on reability, responsive, assurance, emphaty dan tangible. Research Methods: This type of research is quantitative research with a cross sectional approach. This research uses the SPSS application. Finding/Result: There is a positive and insignificant influence between the quality of patent registration application services on patent applicant satisfaction with DJKI based on a reliability p-value > 0.05. There is a positive and significant influence between the quality of patent registration application services on patent applicant satisfaction with DJKI based on responsive, assurance, emphaty dan tangible. Conclusions and implications: This research shows that there are 4 indicators of service quality that influence patent applicant satisfaction with DJKI, so this can be of concern to DJKI to increase patent applicant satisfaction with DJKI.

Differentiated Location Privacy Protection in Mobile Communication Services: A Survey from the Semantic Perception Perspective

Mobile communication services raise user privacy concerns in sharing the traveling trajectories while facilitating people’s daily lives. According to these shared trajectories, adversaries can dig users’ multi-modal behavioral semantics by combining with extensive open-source web information. These behavioral semantics have differentiated privacy sensitivity, raising different levels of privacy concerns. It makes users have personalized requirements for protecting their travelings. Resulting in the inevitable evolutionary trend from location privacy protection to differentiated location privacy protection (DLPP). DLPP digs into mobile semantics and characterizes the differentiated location sensitivity by simulating the potential attacks. It provides the privacy protection with differentiated strength to each location. Differentiated and appropriate strength well balances the tradeoff between privacy protection and data availability for the quality of application service. We are motivated to conduct a comprehensive survey on DLPP from the semantic perception perspective. It forms a complete overview of the mobile semantics-aware differentiation in location privacy protection. Specifically, we first review the research works on multi-modal mobile semantic representation. Then, taking the dug semantics as a clue, we summarize the basic principles of DLPP research systematically. To complete the overview, we also summarize their design modes and discuss the open opportunities and challenges for future works.

Prioritizing protection communication in a 5G slice: Evaluating HTB traffic shaping and UL bitrate adaptation for enhanced reliability

Abstract5G network slicing is promising in prioritizing time‐critical protection communication in wireless networks of smart grids. However, network slicing offered by telecommunication providers encompasses all smart grid applications, lacking granularity. Smart grid automation standards provide recommendations on prioritization of protection communication to improve reliability but only for wired connections. Therefore, this paper investigates hierarchical token bucket (HTB) traffic shaping and uplink (UL) bitrate adaptation of a live video stream for prioritizing protection communication within a 5G slice. An experimental setup combines controller‐hardware‐in‐the‐loop (CHIL) with a quality of service (QoS) measurement system for validation. The system under test consists of commercial 5G networks, intelligent electronic devices (IEDs), and merging units for validation with three smart grid applications: fault location, line differential, and intertrip protection. HTB traffic shaping improves protected faults by 47.57% in congested and 1.16% in non‐congested scenarios. UL bitrate of the video stream adaptation by 2 Mbps increases protected faults by 3.69%. HTB traffic shaping even improves prioritization with a wired connection without introducing additional delays. HTB traffic shaping must be deployed in routers to maintain good QoS for critical applications. Collaboration between utilities and telecommunication providers is essential to effectively deploy 5G network slicing on smart grids.

Application-Aware Scheduling for IEEE 802.15.4e Time-Slotted Channel Hopping Using Software-Defined Wireless Sensor Network Slicing.

Given the improvements to network flexibility and programmability, software-defined wireless sensor networks (SDWSNs) have been paired with IEEE 802.15.4e time-slotted channel hopping (TSCH) to increase network efficiency through slicing. Nonetheless, ensuring the quality of service (QoS) level in a scalable SDWSN remains a significant difficulty. To solve this issue, we introduce the application-aware (AA) scheduling approach, which isolates different traffic types and adapts to QoS requirements dynamically. To the best of our knowledge, this approach is the first to support network scalability using shared timeslots without the use of additional hardware while maintaining the application's QoS level. The AA approach is deeply evaluated compared with both the application traffic isolation (ATI) approach and the application's QoS requirements using the IT-SDN framework and by varying the number of nodes up to 225. The evaluation process took into account up to four applications with varying QoS requirements in terms of delivery rate and delay. In comparison with the ATI approach, the proposed approach enhanced the delivery rate by up to 28% and decreased the delay by up to 57%. Furthermore, even with four applications running concurrently, the AA approach proved capable of meeting a 92% delivery rate requirement for up to 225 nodes and a 900 ms delay requirement for up to 144 nodes.

Supervised algorithms for application bandwidth prediction on Amazon Web Service from a rural SME

This article presents a methodology to measure the bandwidth behaviour by making predictions of the network traffic that connects to the cloud in small and medium enterprises in rural areas with difficult access in Colombia, in order to optimize network resources over time and ensure the quality of service in web applications. A comparative study of three neural network algorithms that model a multilayer neural network is performed, selecting the one that has a minimum error that approaches zero; the selected algorithm is trained from a data source to predict the network traffic that connects to the cloud.It is necessary to analyse network behaviour to ensure the quality of web applications in the cloud that transmit information such as data, images, sound, video, etc., some in real time, and that generate large volumes of traffic. Understanding the traffic flowing through the network enables network capacity planning when managing limited resources, such as in the case of small and medium-sized enterprises in rural areas. As a product of the research analysis, a free software prototype will be developed to perform the measurements and predictions in rural areas. The results of the implementation show that the proposed approach is superior to other forecasting methods in terms of accuracy and predictability.

An intelligent fuzzy-based system for handover decision in 5G-IoT networks considering network slicing and SDN technologies

By enabling 5G technology, IoT networks can improve the performance of connected IoT devices. However, handover, ping-pong effect and load balancing are critical issues because of massive and unplaned deployment of small cells. The handover operation in 5G wireless networks is complicated because there are many radio access techniques and technologies. Therefore, the mobility management is required to provide QoS for various applications. In this paper, we present a fuzzy-based system for handover decision in 5G wireless networks considering different network slicing parameters. We implement two Fuzzy-based Handover Decision Models (FHDM): FHDM1 and FHDM2. We evaluate the proposed models by simulations. For FHDM1, Slice Delay (SD), Slice Bandwidth (SB), and Slice Load (SL) are three input parameters and Handover Decision (HD) is the output parameter. For FHDM2, Slice Reliability (SR) is a new considered parameter, so it has four input parameters and the output parameter is HD the same as FHDM1. We found from simulation results that the considered parameters have different effects on HD. For both models, the HD value increases as SD and SL values increase while HD value is decreasing when SB and SR values increase. The results of the simulation indicate that although FHDM2 is more complex than FHDM1, it performs better HD since considers four input parameters. From the simulation results of FHDM2, when we changed SD value form 10% to 90%, we found that the HD value is increased by 50% when SR is 50% and SL is 90%. This indicates that when a user is connecting with the present slice that has bad QoS, it should handover to another slice with better QoS.

Resilient edge machine learning in smart city environments

Distributed Machine Learning (DML) has emerged as a disruptive technology that enables the execution of Machine Learning (ML) and Deep Learning (DL) algorithms in proximity to data generation, facilitating predictive analytics services in Smart City environments. However, the real-time analysis of data generated by Smart City Edge Devices (EDs) poses significant challenges. Concept drift, where the statistical properties of data streams change over time, leads to degraded prediction performance. Moreover, the reliability of each computing node directly impacts the availability of DML systems, making them vulnerable to node failures. To address these challenges, we propose a resilience framework comprising computationally lightweight maintenance strategies that ensure continuous quality of service and availability in DML applications. We conducted a comprehensive experimental evaluation using real datasets, assessing the effectiveness and efficiency of our resilience maintenance strategies across three different scenarios. Our findings demonstrate the significance and practicality of our framework in sustaining predictive performance in smart city edge learning environments. Specifically, our enhanced model exhibited increased generalizability when confronted with concept drift. Furthermore, we achieved a substantial reduction in the amount of data transmitted over the network during the maintenance of the enhanced models, while balancing the trade-off between the quality of analytics and inter-node data communication cost.