Quality Of Service In Terms Research Articles

Peranan Komisaris dan Direksi Bank Syariah dalam Pengelolaan Dana Zakat dan ISR (Islamic Social Responsibility) di Indonesia

Almsgiving is one of the pillars supporting the upholding of Islam as the obligation for the adherents to improve horizontal relations between fellow humans and strengthen vertical relations with Allah SWT. The implementation of Islamic Social Responsibility (ISR) of the Islamic Bank gives a positive assessment in sharia agreement, justice and equality, responsibility for work, welfare, guarantee of nature preservation and benevolent assistance that is not profit-oriented. Proper almsgiving management and ISR implementation make Islamic banks trusted by the public in terms of service quality, satisfaction and loyalty of Muzzaki. It reduces bad images, and provides relevant impacts on social welfare and the progress of the era. The data analysis used to test the hypotheses is Multiple Linear Regression analysis. The data is collected by distributing questionnaires to Commissioners and Directors at 14 (fourteen) Islamic Commercial Banks spread throughout Indonesia. The result of this study shows partially prove the role of Islamic bank commissioners in the amsgiving management only, while the importance of the role of directors in Islamic banks in almsgiving management and the implementation of ISR partially.

HUBUNGAN KUALITAS PELAYANAN DENGAN KEPERCAYAAN MAHASISWA

<p>The Relationship between Service Quality with the Student's Trusty. The objective of this research to know the lecturer’s and education service with competence, guarante of work fast and education service with student’s trusty in Polytechnic LP3I Jakarta Pasar Minggu campus. The research is carried out in campus Pasar Minggu due to the efficiency of time and place of respondent. The method of this research is by using descriptive statistic and hypothesis test. Base on the relation of service qualiy with students trusttuidance for the managerial, mainly in upgrading the service quality in term of upgrading the student's recommendation. The purpose of this research is to exa, it will result: lecturer’s competences have the significant relation eith student’s trusty. Promotion of guarantee of work fast has the significant relation with the students trusty, education service has the significant relation with the student’s trusty.</p><p><strong>Keyword</strong> : Studnts’s trusty, Lecturer’s Competence, Education Service</p>

Negotiation game for joint IT and energy management in green datacenters

As the power demand of datacenters is increasing sharply, a promising solution is to power datacenters locally by renewable energies. However, one of the main challenges when operating such green datacenters is to conciliate the intermittent power supply and the power demand. To deal with this problem, we view the green datacenter as two sub-systems, namely, Information Technology (IT) sub-system which consumes energy, and electrical sub-system which supplies energy. The objective is to find an efficient trade-off between the power demand and power supply, respecting the operational requirements of both sub-systems (i.e., the requirements on utility, or monetary gain, which includes monetary revenue and monetary cost). First, we analyze the problem by a black-box approach. In this approach, the models of the two sub-systems are unknown to each other, and the two sub-systems negotiate by exchanging their power preferences. However, we found that the black-box approach cannot guarantee stable solutions in term of execution time and generational distance (which is the distance between a solution and the Pareto front). Then we introduce a semi black-box approach, in which the two sub-systems are modeled as the buyer and the supplier in a buyer–supplier negotiation game. We propose an algorithm that allows the buyer and supplier to negotiate, seeking for an efficient trade-off between the power demand and power supply. The analytical results show that the semi black-box algorithm converges to equilibrium, and these results are then confirmed by experimental results. We conduct the experiments by implementing a middleware of a datacenter powered by renewable energies. The experimental results show that the semi black-box algorithm improves significantly the stability, quality of service (QoS) and utility of the datacenter, compared to other algorithms. In term of stability, compared to the black-box algorithm, the semi black-box algorithm reduces the standard deviation of execution time and generational distance by 23 and 27 times, respectively. In term of QoS and utility, the semi black-box algorithm outperforms the algorithms that do not consider joint IT-energy management, as well as the algorithms that do not utilize a semi black-box design.

PERANAN KOMISARIS DAN DIREKSI BANK SYARIAH DALAM PENGELOLAAN DANA ZAKAT DAN ISR (ISLAMIC SOCIAL RESPONSIBILITY) DI INDONESIA

Abstrak
 
 Zakat menjadi salah satu rukun penyangga tegaknya Islam serta kewajiban bagi pemeluknya memperbaiki hubungan horizontal antara sesama manusia dan memperkuat hubungan vertikal manusia dengan Allah SWT. Pelaksanaan Islamic Social Responsibility (ISR) Bank Syariah memberikan dampak positif dalam kepatuhan syariah, keadilan dan kesetaraan, bertanggung jawab dalam bekerja, jaminan kesejahteraan, jaminan kelestarian alam serta bantuan kebajikan yang tidak hanya berorientasi pada keuntungan semata-mata.
 Pengelolaan Zakat dan Pelaksanaan ISR yang tepat membuat bank syariah dipercaya masyarakat dalam service quality, kepuasan dan loyalitas Muzzaki, mengurangi image buruk, serta memberikan dampak yang relevan dalam kesejahteraan sosial dan kemajuan zaman.
 Analisis data yang digunakan untuk menguji hipotesis menggunakan analisis Multiple Linear Regressions. Pengumpulan data dengan pendistribusian kuesioner kepada Komisaris dan Direksi pada 14 Bank Umum Syariah yang tersebar di Indonesia.
 Hasil penelitian ini membuktikan secara parsial adanya peranan komisaris bank syariah dalam pengelolaan zakat saja, sedangkan besarnya peranan direksi di bank syariah dalam pengelolaan zakat dan pelaksanaan ISR secara parsial.

Innovation in Public Services Through the Kawi Smara Program at Klungkung Regency

This study aims to determine (1) the effectiveness of the Kawi Smara Innovation Program in improving the quality of public services at Klungkung Regency (2) factors are the inhibitors of the effectiveness of the Kawi Smara Innovation Program in improving the quality of public at Klungkung Regency. This study employed the qualitative descriptive methodology. The results of this study indicate that (1) the implementation of Kawi Smara's innovation program has been effective in terms of service quality, this innovation program has proven to greatly facilitate the public to obtain a marriage certificate, this innovation program has advantages in terms of the speed of the marriage certificate. the solution for the people who want to do their marriage ceremony right away is to get their marriage certificate. The Kawi Smara program is not maximally in quantity, the target of Kawi Smara's innovation program has not been maximally achieved, this is evidenced by the still low percentage of people who follow Kawi Smara's innovative program services. (2) Factors that hinder the effectiveness of the Kawi Smara innovation program at Klungkung Regency based on the results of the study are Lack of socialization, low public awareness and budget constraints.

Design o f a Fault Tolerant Strategy f or Resource Scheduling i n Cloud Environment

Cloud computing supports the technological need of the industry supporting many other technologies. Also, the demand for computing power and storage by recent technologies is reasonably growing in a drastic way. Cloud computing, serving for these technologies are to be developed with advancements that lead to performance improvement both in support to the technologies like block-chain and big data. The allocation of cloud resources is an important strategy to be followed in a wiser manner to incorporate the needs of extra ordinary computing power. In this paper, an efficient resource allocation strategy (FTVMA) is introduced that involves the creation of effective virtual machines (VMs) and performs VM allocation in an efficient manner by considering the failure rates, previous history of failure of VM, execution efficiency as a part of effective scheduling. There exist many reasons for cloudlet failure in VMs. Some of them are overloading of VMs and non-availability of VMs. The introduced FTVMA algorithm considers the failure rate of the physical machine, load of virtual machines and the cost priority of the tasks in order to achieve Quality of Service (QoS) and Quality of Experience (QoE) of the user. The FTVMA methodology proposed in this paper works better for computation intensive VMs and is tested using CloudSim environment. The QoS metrics used to measure the performance of the proposed algorithm are Makespan and VM Utilization. The metric to measure QoE are Priority Miss Rate and Failure Rate. The proposed algorithm shows its improvement in terms of the QoS and QoE metrics. The results obtained are compared with the existing resource scheduling algorithms and it is inferred that the proposed algorithm performs better in terms of QoS and QoE.

Energy Consumption Using HOMER Software

The present and future of power industries rely on effective usage of electric grids integrated with Information and communication technology which are called as smart grids. These grids provide better quality of service in terms of better resource and asset management, finding out faults in the system, efficient energy consumption by decreasing demand and supply gap. The present work throws light on preliminary investigation on energy and power consumption from the real time data collected from a higher education institution. Analysis is done using HOMER software.

An effective handover management based on SINR and software‐defined network over urban vehicular ad hoc networks

AbstractUrban vehicular ad hoc network (UVANET) is a modality of high‐topology variation MANET where vehicles travel across constrained layout of the roads and tall buildings, which eventually results in shadowing effects. One of the critical challenges in UVANET is the handover process that happens when a vehicle changes its association with the roadside unit. Urban area suffers from high vehicular density at traffic signals, and vehicle slowdowns caused by speed limits, frequent link disconnection caused by signal attenuation due to obstacles. Thus, it is difficult for UVANET to disseminate the packets to their destinations located in a specified area. This paper presents an effective handover management that calculates the signal‐to‐interference‐plus‐noise ratio (SINR) to ultimately determine the optimal cluster head for seamless handover in UVANET. It also utilizes the software‐defined network to resolve the problem of handover failure in UVANET. The finding in the experimental results shows that the developed association clustering mechanism based on SINR significantly outperforms the baseline association mechanism. More importantly, it can resolve different types of handover problems that improved the quality of service in terms of throughput, handover latency, packet loss ratio, and handover failure ratio, when compared to the baseline handover mechanisms.

MODEL OF DATA TRAFFIC QOS FAST REROUTING IN INFOCOMMUNICATION NETWORKS

The subject of research in the article is the processes of fast rerouting with the protection of the Quality of Service level in infocommunication networks. The aim of the work is the development of a mathematical model of Fast ReRouting with the protection of the Quality of Service level by the bandwidth and probability of packet loss for data traffic. The following tasks are solved in the article: development and research of a fast rerouting flow-based model with the protection of the Quality of Service level of data traffic in the infocommunication network. The following methods are used: the graph theory, the teletraffic theory, the queuing theory, and mathematical programming methods. The following results were obtained: the fast rerouting flow-based model was developed and investigated, which, due to the introduced protection conditions on indicators of bandwidth and packet loss probability, allows providing the Quality of Service along both the primary and backup multipath. Conclusions: Within the framework of the proposed flow-based model, the fast rerouting technological task was formulated as an optimization problem with the constraints of the conditions of implementation of the multipath routing strategy, conditions of flow conservation, and conditions of protection of the link, node, and level of Quality of Service in terms of bandwidth and packet loss probability. The application of this solution contributes to the optimal use of the available network resource while providing the specified level of Quality of Service in terms of bandwidth and probability of packet loss along both the primary and backup routes in the case of a failure of the infocommunication network elements. The proposed flow-based model can be used as the basis of the algorithmic software of existing routers and/or controllers of Software-Defined Networks, which are responsible for the calculation of the primary and backup paths in the fast rerouting of data traffic sensitive to such Quality of Service indicators as bandwidth and packet loss probability.

Energy Efficiency Optimization for Wireless Body Area Networks Under 802.15.6 Standard

With the attractive applications in e-Health, a booming interest is granted to wireless body area network (WBAN). Through WBAN, healthcare professionals can continuously monitor patient vital signs and detect critical conditions which results in major improvements in the quality of patients’ lives and also in the quality of healthcare services. The big challenge for WBAN is to track and maintain good quality of service (QoS) under real-time and dynamic conditions. In this paper, we propose an enhanced medium access control (MAC) protocol under IEEE 802.15.6 standard based on traffic prioritization. Simulations results show that the proposed protocol outperforms IEEE 802.15.6 MAC in terms of QoS and energy saving under traffic-fluctuation conditions.

A Cross-Layer Approach for Wireless Body Area Networks

Research in wireless body area network (WBAN) has gained interest and has become an emerging health service application because of the potential for its use in continuous monitoring of human well-being. The natural human body movements and environmental interference impose difficulties on WBAN performance, such as operational lifetime and data delivery reliability. This work proposes a cross-layer approach, called CL, based on the IEEE 802.15.4 standard to guarantee quality of service in terms of packet delivery and network lifetime. The proposed protocol is compared to the original standard and results suggest that CL outperforms when interference is the cause of packet delivery failures.

Improving the Mechanism of Detecting and Measuring Holes in Ad hoc Wireless Sensor Network

Abstract Area detection and measuring is one of the most important problems in wireless sensor network because it mainly relates to the continuity and functionality of most routing protocols applied to the region of interest (ROI). Electronics failure, random deployment of nodes, software errors or some phenomena such as fire spreading or water flood could lead to wide death of sensor nodes. The damage on ROI can be controlled by detecting and calculating the area of the holes, resulting from the damaged sensor networks. In this paper, a new mathematical algorithm, wireless sensor hole detection algorithm (WHD), is developed to detect and calculate the holes area in ROI where the sensor nodes are spread randomly. WHD is developed for achieving quality of service in terms of power consumption and average hole detection time. The dynamic behavior of the proposed WHD depends on executing the following steps. Firstly, WHD algorithm divides down the ROI into many cells using the advantage of the grid construction to physically partition the ROI into many small individual cells. Secondly, WHD algorithm works on each cell individually by allocating the nearest three sensor nodes to each of the cell’s coordinates by comparing their positions, WHD connects each cell’s coordinate points with the selected sensor nodes by lines that construct a group of triangles, then WHD calculates the area of upcoming triangles. Repeating the previous step on all the cells, WHD can calculate and locate each hole in the ROI. The performance evaluation depends on the NS-2 simulator as a simulation technique to study and analyze the performance of WHD algorithm. Results show that WHD outperforms, in terms of average energy consumption and average hole discovery time, path density algorithm, novel coverage hole discovery algorithm and distriputed coverage hole Detection.

Cloud service selection based on QoS-aware logistics

With the development of technologies such as cloud computing, Big Data, the Internet of Things, etc., Internet + logistics models are being sought by all parties, leading to the current rise of cloud service platforms for logistics. As such platforms combine many logistics services with similar functions, identification of methods to choose from among a large number of similar services to meet the personalized needs of customers has become especially important. In the work presented herein, QoS data are quantified and filtered through the establishment of quality of service (QoS) decision information systems. Meanwhile, using the variable precision rough set method, the weight of each QoS attribute index is calculated, then the similarity of services, to obtain a comprehensive sequence in terms of service quality that provides a basis for selection of the optimal service. The calculation and analysis results show that this method can effectively choose the best logistics service according to specific business needs.

KUALITAS PELAYANAN ADMINISTRASI TERPADU KECAMATAN DITINJAU DARI INDEKS KEPUASAN MASYARAKAT DI KECAMATAN TANJUNGPINANG KOTA KOTA TANJUNGPINANG PROVINSI KEPULAUAN RIAU

The government has the obligation and responsibility as a provider of public services to meet the needs of the community, which is implemented by both central government agencies, in regional and State-Owned Enterprises. Services that can be provided in the form of goods or merit services. Services provided by the government to the public must be qualified. For that there is a community satisfaction index that is intended for government agencies services units where the results can be used as a reference for the agency service providers to improve and enhance the quality of services provided to the community. A quality service can make people become satisfied. The purpose of this research to determine the District Integrated Administrative Service Quality in terms of Community Satisfaction Index in the District of Tanjungpinang City Tanjungpinang City of Riau Islands province. The research design used is descriptive qualitative research with an inductive approach. The technique of collecting data through interviews, observation, documentation and triangulation. Data were analyzed using data reduction, data tabulation and conclusion. Research results obtained that the quality of the integrated administrative service districts in the District of the City Tanjungpinang already qualified, it is known after a review of the results of community satisfaction index where the value obtained is 75.575 which can be practically considered good or quality. Keywords: quality, service, government

Deep Learning-based Sentiment Analysis: Establishing Customer Dimension as the Lifeblood of Business Management

‘First mover advantage does not go to the first company that launches, it goes to the first company that scales’ (Reid Hoffman, co-founder of LinkedIn, ScaleIt, 2016 ). M. Andreesen defines scale-up as a company that has identified its product/market fit and has reached notable proofs of market traction (e.g., profitability, revenues, active users, registered users, market demand). It has been previously established that five interdependent core dimensions can be used to evaluate scale-up: customer, product, team, business model and financials. Most of the business failures result from falling apart of one or more of these dimensions with others. We in our article discuss the ‘customer dimension’ as the essence of scaling up. For running a profitable business, it is crucial to evaluate customers’ reviews, like their perception and expectation from the product and services in terms of service quality, deliverables, staff and management practices and pricing. This will increase customer satisfaction which will further boost the demand and popularity of the brand and business. The customers today are very vocal in sharing their experiences through social media blogs, channels, review sites and so on. These experiences need to be decrypted by the management to understand the customer’s point of view, their apprehensions and expectations. Sentiment analysis is one of the best ways to tap customer feedback. The usual way of analysis involves the bag of words model using ngrams. A more refined version is an ontology-based analysis. Research has also been done using the radial basis function kernel for support vector machines (SVMs) (for recognizing polarity of sentiments). Naïve Bayes algorithms have also been used in some sentiment studies along with linear kernel SVM classifiers. But we realized during the literature review that it is not enough to just classify the text into positive and negative or a few more categories. It is even more important to know which topics are being discussed by the customers, their intention behind the message and further the need to classify them as complaints, suggestions, appreciation or query and so on. Thus, we in our article discuss the solution to all these types of analyses using ‘deep sentiment analysis’. We discuss the case of a few current social topics and introduce ‘recurrent neural networks’ (RNNs) and ‘convolutional neural networks’ (CNNs) for sentiment and intent analysis. These advanced analytical techniques will help in the ‘pivoting’ of businesses by taking desired actions such as improving product quality, improving quality of services and increasing quality checks in areas with maximum negative reviews. This eventually will help start-up ventures in improving customer experience and gradually help in the scaling of ventures.

On semantic clustering and adaptive robust regression based energy-aware communication with true outliers detection in WSN

To conserve energy and enhance the lifetime of the wireless sensor network (WSN), reducing the amount of data communication by exploiting temporal and spatial correlation of sensed data is well suitable technique. So, instead of sending every data to the destination, it can be worthy of introducing a prediction method to reduce redundant data transmission by exploiting the temporal correlation of sensed data. We show that the prediction accuracy of source data depends not only on the method applied but also on the correctness of the sample data provided by the source nodes. Erroneous sample data (outliers) leads to the wrong prediction. In this paper, we propose an energy efficient SEMantic CLustering (SEMCL) model to mitigate high energy consumption problem in a clustered WSN. Our model produces energy efficient clusters by strong intra-cluster data similarity to exploit spatial correlation of data. We adopt the Robust and Efficient Weighted Least Square method (REWLS) to provide accurate data prediction with negligible errors. Because REWLS method lacks to differentiate true and false outliers and thus to improve further the Quality of Service (QoS) on data accuracy, we propose a separate algorithm, named, True Outlier Detection (TOD). Moreover, to improve the QoS in communications, a reliable backbone network based on the link quality of the data forwarding path has been implemented. Our proposed model has been simulated using real data and compared with the existing techniques to show its efficacy and superiority in terms of QoS on data accuracy, energy consumption, and network lifetime.

Uncertainty-Aware Flight Scheduling for Airport Throughput and Flight Delay Optimization

The continuous growth in the demand for air transportation exceeds the capacity of existing infrastructure, usually leading to unreliable flight schedules, i.e., long flight delays and uncertainties in arrival/departure and taxi times. We tackle the problem in this paper by designing an air traffic control algorithm, which can accommodate both airport throughput and flight quality of service in terms of flight delay on a given runway. The flight scheduling problem is formulated as an integer linear programming, and then converted to a multiobjective optimization problem which enables the computation of tradeoff between scheduling resolution and time complexity. Based on the multiobjective optimization, a heuristic algorithm considering uncertainties in flight arrival/departure time and taxi time is designed to achieve an improvement in airport throughput and a reduction in flight delay. Extensive simulations show that compared to benchmarking schemes, the proposed uncertainty-aware flight scheduling algorithm can improve the airport throughput and flight delay by up to 12.02% and 31.4%, respectively.

Interventions to reduce the impact of dual practice in the public health sector.

Dual practice (i.e. workers who work in the public and private sector) has an impact on health services in terms of quality and costs. However, the effectiveness of regulatory policies has not been proven. We searched in Epistemonikos, the largest database of systematic reviews in health, which is maintained by screening multiple information sources, including MEDLINE, EMBASE, Cochrane, among others. We extracted data from the systematic reviews, reanalyzed data of primary studies, conducted a meta-analysis and generated a summary of findings table using the GRADE approach. We identified three systematic reviews that included 23 primary studies overall, of which all correspond to observational studies. We concluded it is not clear whether the interventions to reduce the negative consequences of dual practice in the health system are effective because the certainty of the available evidence is very low.

Online Learning for Energy Saving and Interference Coordination in HetNets

In heterogeneous cellular networks (HetNets), switching OFF small cells under low user traffic periods has been proved to be an effective energy saving strategy. However, this strategy has strong interactions with interference coordination (IC) mechanisms, making it convenient to address both tasks simultaneously. The motivation of this paper is to develop a self-optimization algorithm capable of jointly controlling energy saving and IC mechanisms using an online learning approach. Our proposal is based on a contextual bandit formulation that, among other challenges, implies discovering the most energy-efficient control actions while satisfying a predefined level of Quality of Service (QoS) for the users. We propose a two-level framework comprising a global controller, in charge of a group of macro cells, and multiple local controllers, one per macro cell. The global controller implements a novel algorithm, referred to as the Bayesian Response Estimation and Threshold Search (BRETS), that is capable of learning, for each control action, its feasibility boundaries in terms of QoS and its energy consumption as a function of the aggregated user traffic. The algorithm comes with a bound on its expected convergence time. The local controllers translate the control actions learned by the global controller into local decisions. Our numerical results show that BRETS is only 1% less efficient than an ideal oracle policy, clearly outperforming other benchmark algorithms.

Cloud data storage: a queueing model with thresholds

In the past decade, cloud platforms have become a standard across the industry for data storage and operations. Such platforms offer high quality of service in terms of reliability and ease of setup at an effective cost. With exponentially high rates of increase of data storage requirements, data is now increasingly stored in clouds. However, there are limited studies which analyze the processes performing the storage operations. Queueing models offer a very natural way of modeling these storage processes. The data packets waiting for storage form a queue which is served by a storage server. Since data packets are transmitted to the cloud in batches for efficiency, this storage server is modelled as a batch server. The storage server goes into sleep mode in between data transmission periods which are, in turn, modelled as vacations. The storage service is resumed after a vacation if there are enough packets in backlog or enough time has elapsed since last storage. This is modelled as restarting thresholds in our model. Analyzing this model helps us evaluate the quality of service (QoS) of storage processes in terms of measures such as backlog size and probability of a new connection to cloud server. These measures are then used to define a user cost function and QoS constraints, and compute optimal storage parameters.