IMPLEMENTASI MCCALL’S FRAMEWORK DALAM PENGUJIAN KUALITAS PERANGKAT LUNAK (STUDI KASUS PORTAL KULIAH KERJA NYATA UNIVERSITAS RIAU)

Quality test is a crucial phase in the system development process to ensure that system work as its requirement. Therefore, the Portal Kukerta (Kuliah Kerja Nyata) Universitas Riau, an information system to manage data and activities of Kukerta, needs to assess. In this research, Portal Kukerta has been assessed using the McCalls software quality framework. The aspect that is focused on this research is product operation. Product operation consists of correctness, usability, integrity, reliability, and efficiency. The data collected by distributing questionnaires to 67 participants. The results show that users give a positive response to two aspects, namely  efficiency 99.90% and usability 64%. However, for the reliability factor 43%, correctness 48%, integrity 56% get a neutral value that there are aspects that are considered less by the user. Based on these results, it can be concluded that the Kukerta portal is very efficient in managing the data of Kukerta University of Riau and can be easily used by users. However, in terms of reliability, correction, and integrity need to be improved. The implication of the research are (1) providing a reference in assessing quality of a software and (2) specifically providing a recommendation for Portal Kukerta Universitas Riau for their system improvements

Multiscale Granger causality

In the study of complex physical and biological systems represented by multivariate stochastic processes, an issue of great relevance is the description of the system dynamics spanning multiple temporal scales. While methods to assess the dynamic complexity of individual processes at different time scales are well-established, multiscale analysis of directed interactions has never been formalized theoretically, and empirical evaluations are complicated by practical issues such as filtering and downsampling. Here we extend the very popular measure of Granger causality (GC), a prominent tool for assessing directed lagged interactions between joint processes, to quantify information transfer across multiple time scales. We show that the multiscale processing of a vector autoregressive (AR) process introduces a moving average (MA) component, and describe how to represent the resulting ARMA process using state space (SS) models and to combine the SS model parameters for computing exact GC values at arbitrarily large time scales. We exploit the theoretical formulation to identify peculiar features of multiscale GC in basic AR processes, and demonstrate with numerical simulations the much larger estimation accuracy of the SS approach compared with pure AR modeling of filtered and downsampled data. The improved computational reliability is exploited to disclose meaningful multiscale patterns of information transfer between global temperature and carbon dioxide concentration time series, both in paleoclimate and in recent years

Bayesian Approach for Reliability Assessment of Sunshield Deployment on JWST

Deployable subsystems are essential to mission success of most spacecraft. These subsystems enable critical functions including power, communications and thermal control. The loss of any of these functions will generally result in loss of the mission. These subsystems and their components often consist of unique designs and applications, for which various standardized data sources are not applicable for estimating reliability and for assessing risks. In this study, a Bayesian approach for reliability estimation of spacecraft deployment was developed for this purpose. This approach was then applied to the James Webb Space Telescope (JWST) Sunshield subsystem, a unique design intended for thermal control of the observatory's telescope and science instruments. In order to collect the prior information on deployable systems, detailed studies of "heritage information", were conducted extending over 45 years of spacecraft launches. The NASA Goddard Space Flight Center (GSFC) Spacecraft Operational Anomaly and Reporting System (SOARS) data were then used to estimate the parameters of the conjugative beta prior distribution for anomaly and failure occurrence, as the most consistent set of available data and that could be matched to launch histories. This allows for an emperical Bayesian prediction for the risk of an anomaly occurrence of the complex Sunshield deployment, with credibility limits, using prior deployment data and test information

Integrated Sensor Fusion Device with an Optimized Mathematical Model to Monitor Civil Engineering Structures

Integrated sensor fusion is a new technique in which multiple sensors intelligently combine data to support application or system performance improvement software. With this method, many sensors combine data for accurate position and orientation information to overcome the inadequacy of each sensor. Data consolidation can be described as measuring the state of an entity as a mixture of data or information. This multidisciplinary field has several advantages, including increased confidence, reliability, and reduced ambiguity when measuring company conditions in engineered systems. This paper discusses the various applications of data fusion in civil engineering in recent years, and puts forward some potential advantages of data fusion in civil engineering. Mathematical modeling (MM) is the skill to transform challenges from application to tractable mathematical formulations that provide insight, answers, and instructions in the theoretical and numerical analysis of the original application. This article presented an integer linear programming mathematical model to divide building activities in a project to solve building planning problems. MMCE (Mathematical Modeling Conceptual Evaluation) introduced it to complete an accurate and quick estimation of civil systems such as traffic networks, structural systems, and building projects, becoming more and more achievable through omnipresent sensor networks and communications systems. By assessing the condition of the system, it can make better decisions more rapidly and better. This has enormous value and a variety of impacts. Fusion data is an essential element of system status assessment. Applications and needs for research are underlined for the future

Optimal Experimental Planning of Reliability Experiments Based on Coherent Systems

In industrial engineering and manufacturing, assessing the reliability of a product or system is an important topic. Life-testing and reliability experiments are commonly used reliability assessment methods to gain sound knowledge about product or system lifetime distributions. Usually, a sample of items of interest is subjected to stresses and environmental conditions that characterize the normal operating conditions. During the life-test, successive times to failure are recorded and lifetime data are collected. Life-testing is useful in many industrial environments, including the automobile, materials, telecommunications, and electronics industries. There are different kinds of life-testing experiments that can be applied for different purposes. For instance, accelerated life tests (ALTs) and censored life tests are commonly used to acquire information in reliability and life-testing experiments with the presence of time and resource limitations. Statistical inference based on the data obtained from a life test and effectively planning a life-testing experiment subject to some constraints are two important problems statisticians are interested in. The experimental design problem for a life test has long been studied; however, the experimental planning considering putting the experimental units into systems for a life-test has not been studied. In this thesis, we study the optimal experimental planning problem in multiple stress levels life-testing experiments and progressively Type-II censored life-testing experiments when the test units can be put into coherent systems for the experiment. Based on the notion of system signature, a tool in structure reliability to represent the structure of a coherent system, under different experimental settings, models and assumptions, we derive the maximum likelihood estimators of the model parameters and the expected Fisher information matrix. Then, we use the expected Fisher information matrix to obtain the asymptotic variance-covariance matrix of the maximum likelihood estimators when $n$-component coherent systems are used in the life-testing experiment. Based on different optimality criteria, such as $D$-optimality, $A$-optimality and $V$-optimality, we obtain the optimal experimental plans under different settings. Numerical and Monte Carlo simulation studies are used to demonstrate the advantages and disadvantages of using systems in life-testing experiments

GIS-Based Interactive Technology in Demographic Record Management and Mapping Towards Sustainable Community

Management of demographic records plays a vital role in understanding and planning for the needs of community living. However, managing conventional records requires more time, cost, and energy without accurate assurance. As there are raising concerns in assessing community information for charity purposes, safety coordination, and crime prevention, especially during emergencies; integrating demographic data with spatial information is becoming significantly important. This paper aims to establish an accessible and visible digital platform of demographic information for respective sectors, namely, the KRT, Qariah group, NGOs, and representatives of CSR projects. The objective is to digitize interactive demographic record management and mapping through GIS-based technology. This study adopts a Geographical Information System (GIS) to digitize information using web GIS integrating with the Unmanned Aerial Vehicle (UAV) technology for data acquisition in the community sampling areas; Puncak Iskandar. The proposed system which leverages the power of spatial analysis and visualization, utilizes GIS technology to store, analyse, and visualize demographic records in a geographical context. It incorporates various demographic data sources, such as census data, health records, and administrative data in managing more efficient and effective data with lower cost, energy, time, and resources. Furthermore, the GIS-based system enables the identification of spatial disparities, inequalities, and interventions in demographic characteristics. Therefore, the integration of this system into community demographic management has provided a powerful platform for accessing and coordinating population dynamics, problem-solving, and sustainable development. The implementation in Puncak Iskandar enhances the accessibility, and visualization of demographic data, enabling policy-makers, researchers, and planners to make informed decisions based on a geographical perspective. The findings demonstrate the reliability of GIS-based demographic record management in a community living towards supporting evidence-based planning, resource allocation, and policy formulation for a wide range of applications, including urban planning, public health, and social services towards a sustainable future

Deciding between information security and usability : Developing value based objectives

Deciding between security and usability of systems remains an important topic among managers and academics. One of the fundamental problems is to balance the conflicting requirements of security and usability. We argue that definition of objectives for security and usability allows for deciding about the right balance between security and usability. To this effect we propose two instruments for assessing security and usability of systems, and develop them in three phases. In Phase 1 we identified 16 clusters of means and 8 clusters of fundamental objectives using the value-focused thinking approach and interviews with 35 experts. Based on phase 1, in the second phase we collected a sample of 201 users to purify, and ensure reliability and unidimensionality of the two instruments. In the third phase, based on a sample of 418 users we confirmed and validated the two instruments found in Phase 2. This resulted in 14 means objectives organized into four categories (minimize system interruptions and licensing restrictions, maximize information retrieval, maximize system aesthetics, and maximize data quality), and 10 fundamental objectives grouped into four categories (maximize standardization and integration, maximize ease of use, enhance system related communication, and maximize system capability). The objectives offer a useful basis for assessing the extent to which security and usability has been achieved in systems. The objectives also provide a decision basis for balancing security and usability.info:eu-repo/semantics/publishedVersio

Analysis and Application of Advanced Control Strategies to a Heating Element Nonlinear Model

open4siSustainable control has begun to stimulate research and development in a wide range of industrial communities particularly for systems that demand a high degree of reliability and availability (sustainability) and at the same time characterised by expensive and/or safety critical maintenance work. For heating systems such as HVAC plants, clear conflict exists between ensuring a high degree of availability and reducing costly maintenance times. HVAC systems have highly non-linear dynamics and a stochastic and uncontrollable driving force as input in the form of intake air speed, presenting an interesting challenge for modern control methods. Suitable control methods can provide sustainable maximisation of energy conversion efficiency over wider than normally expected air speeds and temperatures, whilst also giving a degree of “tolerance” to certain faults, providing an important impact on maintenance scheduling, e.g. by capturing the effects of some system faults before they become serious.This paper presents the design of different control strategies applied to a heating element nonlinear model. The description of this heating element was obtained exploiting a data driven and physically meaningful nonlinear continuous time model, which represents a test bed used in passive air conditioning for sustainable housing applications. This model has low complexity while achieving high simulation performance. The physical meaningfulness of the model provides an enhanced insight into the performance and functionality of the system. In return, this information can be used during the system simulation and improved model based and data driven control designs for tight temperature regulation. The main purpose of this study is thus to give several examples of viable and practical designs of control schemes with application to this heating element model. Moreover, extensive simulations and Monte Carlo analysis are the tools for assessing experimentally the main features of the proposed control schemes, in the presence of modelling and measurement errors. These developed control methods are also compared in order to evaluate advantages and drawbacks of the considered solutions. Finally, the exploited simulation tools can serve to highlight the potential application of the proposed control strategies to real air conditioning systems.openTurhan, T.; Simani, S.; Zajic, I.; Gokcen Akkurt, G.Turhan, T.; Simani, Silvio; Zajic, I.; Gokcen Akkurt, G