Sistem Pendukung Keputusan Penentuan Internet Service Provider di Daerah Condongcatur Menggunakan Metode AHP Berbasis Web

Internet Service Provider (ISP) merupakan perusahaan atau penyedia jasa layanan internet. Setiap ISP memiliki jenis produk serta kualitas layanan yang disediakan berbeda-beda, seperti bandwidth, kualitas jaringan, pemeliharaan, kestabilan koneksi, kecepatan, hingga harga, serta perangkat yang digunakan. Setiap penyedia jasa layanan internet juga pasti memiliki layanan, cakupan lokasi hingga kecepatan yang berbeda pula, sehingga pengguna yang ingin memasang atau menggunakan jasa ini sering merasa kebingungan. Pada penelitian kali ini, dilakukan dengan membangun Sistem Pendukung Keputusan (SPK) dengan maksud untuk dapat mengatasi permasalahan tersebut. Dengan menggunakan sistem SPK maka akan dilakukan proses manajemen data untuk dapat memilah beberapa jenis ISP yang tersedia sesuai dengan kebutuhan pengguna. Tujuan dari dilakukannya penelitian ini adalah membangun Sistem Pendukung Keputusan menggunakan metode Analytical Hierarchy Process atau AHP untuk dapat membantu pengguna dalam melakukan proses pemilihan dari jasa layanan Internet Service Provider. Perolehan atau hasil penelitian yang dilakukan diharapkan dapat mengetahui ISP yang layak digunakan di daerah Condongcatur, Kabupaten Sleman, Daerah Istimewa Yogyakarta. Kata Kunci: Internet Service Provider, Analitycal Hierarchy Process, Sistem Pendukung Keputusa

Blockchain Risk Evaluation on Enterprise Systems using an Intelligent MCDM based model

Blockchain technology (BT) has become popular in the firms in the present time, however, implementation of BT includes several risk factors from various points of view. Some of these risks can be serious for the processes of firms. These risks should be cautiously recognized and analyzed to reduce the negative impacts of them. Assessment of the risks can be recognized as a multi-criteria decision making (MCDM) problem. In this work, the risks that will occur when implementing BT are assessed by using MCDM methodology built on Single Valued Neutrosophic Sets (SVNSs), Analytic Hierarchy Process (AHP), and Decision Making and Trial Evaluation Laboratory (DEMATEL) methods. The main and sub criteria risks are collected via a company in the smart village in Egypt and from previous research, hence, the hierarchical form of the problem is built. AHP is used to show the importance of risk factors and the relationships between risk factors obtained by using the DEMATEL method. The main goal of this study is to aid the firms mainly and the firm in Egypt especially to determine which risks are more serious and to which of them causing effect and are being affected. In this study 8 main criterion and 28 sub-criteria, risks are used. As result, the security risk is important in the main risks but energy costs and data leaks are important in sub risks

Intellectual technologies and decision support systems for the control of the economic and financial processes

Запропоновано комп'ютерна система підтримки прийняття рішень, основними завданнями якої є побудова адаптивної моделі і прогнозування різних типів процесів, які розвиваються в соціально-економічних системах під впливом фундаментальних структурних змін. Складність і актуальність розв'язуваної проблеми полягає в необхідності забезпечити прийнятні якісні прогнози фінансових і економічних показників для коротких вибірок даних, коли використання ретроспективних даних неможливо або суттєво обмежена. Розробка СППР заснована на принципах системного аналізу, тобто можливості обліку деяких стохастичних та інформаційних невизначеностей, формування альтернатив для моделей і прогнозів і відстеження правильності обчислювальних процедур на всіх етапах обробки даних. Реалізована модульна архітектура, яка забезпечує можливість подальшого розширення і модифікації функціональних можливостей системи за допомогою нових методів прогнозування та оцінки параметрів. Крім того, пропонована система, завдяки модульній архітектурі, може бути поліпшена за рахунок використання програмного забезпечення різних виробників без будь-яких додаткових структурних змін. Висока якість кінцевого результату досягається завдяки належному відстеження обчислювальних процедур на всіх етапах обробки даних в ході обчислювальних експериментів: попередня обробка даних, побудова моделі і оцінка прогнозів. Відстеження виконується з відповідними наборами статистичних параметрів якості. Наведено приклад оцінки фінансового ризику в сфері страхування та споживання електроенергії з точки зору енергозбереження. Наведені приклади показують, що розроблена система має хороші перспективи для практичного використання. Передбачається, що система буде універсальною і знайде своє застосування в якості додаткового інструменту для підтримки прийняття рішень при розробці стратегій для компаній і підприємств різних типів.A computer-based decision support system is proposed the basic tasks of which are adaptive model constructing and forecasting of various types of processes that are developing in socio-economic systems under the influence of fundamental structural changes. The complexity and urgency of the solvable problem is the need to provide acceptable quality forecasts of financial and economic indicators for short data samples, when the usage of retrospective data is impossible or significantly limited. The DSS development is based on the system analysis principles, i.e. the possibility for taking into consideration of some stochastic and information uncertainties, forming alternatives for models and forecasts, and tracking of the computing procedures correctness during all stages of data processing. A modular architecture is implemented that provides a possibility for the further enhancement and modification of the system functional possibilities with new forecasting and parameter estimation techniques. In addition, the proposed system, thanks to the modular architecture, can be improved by using the software of different vendors without any additional structural changes. A high quality of the final result is achieved thanks to appropriate tracking of the computing procedures at all stages of data processing during computational experiments: preliminary data processing, model constructing, and forecasts estimation. The tracking is performed with appropriate sets of statistical quality parameters. The example is given for estimation of financial risk in the insurance sphere and the electricity consumption in terms of energy saving. The examples solved show that the system developed has good perspectives for practical use. It is supposed that the system will be universal and find its applications as an extra tool for support of decision making when developing the strategies for companies and enterprises of various types.Предложена компьютерная система поддержки принятия решений, основными задачами которой являются построение адаптивной модели и прогнозирование различных типов процессов, которые развиваются в социально-экономических системах под воздействием фундаментальных структурных изменений. Сложность и актуальность решаемой проблемы заключается в необходимости обеспечить приемлемые качественные прогнозы финансовых и экономических показателей для коротких выборок данных, когда использование ретроспективных данных невозможно или существенно ограничено. Разработка СППР основана на принципах системного анализа, то есть возможности учета некоторых стохастических и информационных неопределенностей, формирования альтернатив для моделей и прогнозов и отслеживания правильности вычислительных процедур на всех этапах обработки данных. Реализована модульная архитектура, которая обеспечивает возможность дальнейшего расширения и модификации функциональных возможностей системы с помощью новых методов прогнозирования и оценки параметров. Кроме того, предлагаемая система, благодаря модульной архитектуре, может быть улучшена за счет использования программного обеспечения разных производителей без каких-либо дополнительных структурных изменений. Высокое качество конечного результата достигается благодаря надлежащему отслеживанию вычислительных процедур на всех этапах обработки данных в ходе вычислительных экспериментов: предварительная обработка данных, построение модели и оценка прогнозов. Отслеживание выполняется с соответствующими наборами статистических параметров качества. Приведен пример оценки финансового риска в сфере страхования и потребления электроэнергии с точки зрения энергосбережения. Решенные примеры показывают, что разработанная система имеет хорошие перспективы для практического использования. Предполагается, что система будет универсальной и найдет свое применение в качестве дополнительного инструмента для поддержки принятия решений при разработке стратегий для компаний и предприятий различных типов

Choosing Wearable Internet of Things Devices for Managing Safety in Construction Using Fuzzy Analytic Hierarchy Process as a Decision Support System

Many safety and health risks are faced daily by workers in the field of construction. There is unpredictability and risk embedded in the job and work environment. When compared with other industries, the construction industry has one of the highest numbers of worker injuries, illnesses, fatalities, and near-misses. To eliminate these risky events and make worker performance more predictable, new safety technologies such as the Internet of Things (IoT) and Wearable Sensing Devices (WSD) have been highlighted as effective safety systems. Some of these Wearable Internet of Things (WIoT) and sensory devices are already being used in other industries to observe and collect crucial data for worker safety in the field. However, due to limited information and implementation of these devices in the construction field, Wearable Sensing Devices (WSD) and Internet of Things (IoT) are still relatively underdeveloped and lacking. The main goal of the research is to develop a conceptual decision-making framework that managers and other appropriate personnel can use to select suitable Wearable Internet of Things (WIoT) devices for proper application/ implementation in the construction industry. The research involves a literature review on the aforementioned devices and the development and demonstration of a decision-making framework using the Fuzzy Analytic Hierarchy Process (FAHP)

Проєктування інформаційної системи розрахунку рейтингу здобувачів вищої освіти

The current information systems for calculating the rating of applicants for higher education were analyzed in the paper, as well as their importance for the educational process organization and a study motivation increasement among applicants for higher education. In course of the research several advantages and disadvantages are highlighted. Among the main disadvantages of such systems is the calculation of ratings based on one criterion only, usually – educational ratings. The main requirements and tasks for the development of a multi-criteria based information system for calculating the rating of higher education are formulated, and also the main methods for project implementation are identified. The chosen methodological approaches enabling formulation of the problem statement and research hypothesis, requirements, and functionality of the information system for determining the rating of higher education were established. During the development of the information system, DSS (the Decision Support System) was chosen as the basic technology for rating calculation. The scheme and model of calculation process of rating are developed based on the mentioned technology. The developed information system for determining the rating of higher education applicants during the calculation of the rating can take into account the following criteria: indicators in education; results of scientific, official (public) activity; sports results, etc. Such criteria are determined by the regulations of the Lviv State University of Internal Affairs – an institution of higher education with specific learning conditions. This system is a separate subsystem of the integrated information system of higher education institution management and has generally accepted client-server architecture. The versatility and flexibility of the developed system allows introducing it for other higher education institutions with specific learning conditions, as well as in the activities of classical institutions of higher education.Проаналізовано інформаційні системи розрахунку рейтингу здобувачів вищої освіти та їх значення для організації навчального процесу, підвищення мотивації до навчання серед здобувачів вищої освіти. Виокремлено низку їх переваг та недоліків. Серед основних недоліків більшості таких систем – розрахунок рейтингу на підставі тільки одного критерію, переважно – показників у навчанні. За результатами проведеного аналізу сформульовано основні вимоги та завдання для розроблення інформаційної системи розрахунку рейтингу здобувачів вищої освіти на підставі багатьох критеріїв, визначено основні методи для реалізації проєкту. Обрані методологічні підходи дали змогу сформулювати постановку проблеми та дослідницьку гіпотезу, встановити вимоги та функціонал інформаційної системи визначення рейтингу здобувачів вищої освіти. Під час розроблення інформаційної системи за базову технологію розрахунку рейтингу обрано систему підтримання прийняття рішень DSS (англ. Decision Support System). На підставі згаданої технології розроблено схему та модель процесів розрахунку рейтингу. Розроблена інформаційна система визначення рейтингу здобувачів вищої освіти під час розрахунку рейтингу здатна враховувати різні критерії: показники у навчанні; результати наукової, службової (громадської) діяльності; спортивні результати тощо. Такі критерії, зокрема, визначені нормативно-правовими актами Львівського державного університету внутрішніх справ – закладу вищої освіти зі специфічними умовами навчання. Ця система є окремою підсистемою інтегрованої інформаційної системи управління закладом вищої освіти та має загальноприйняту клієнт-серверну архітектуру. Універсальність і гнучкість розробленої системи дає змогу запровадити її як для інших закладів вищої освіти із специфічними умовами навчання, так і у діяльність класичних закладів вищої освіти

Capturing Software Architecture Knowledge for Pattern-Driven Design

Context: Software architecture is a knowledge-intensive field. One mechanism for storing architecture knowledge is the recognition and description of architectural patterns. Selecting architectural patterns is a challenging task for software architects, as knowledge about these patterns is scattered among a wide range of literature. Method: We report on a systematic literature review, with the aim of building a decision model for the architectural pattern selection problem. Moreover, twelve experienced practitioners at software-producing organizations evaluated the usability and usefulness of the extracted knowledge.\newline Results: An overview is provided of 29 patterns and their effects on 40 quality attributes. Furthermore, we report in which systems the 29 patterns are applied and in which combinations. The practitioners confirmed that architectural knowledge supports software architects with their decision-making process to select a set of patterns for a new problem. We investigate the potential trends among architects to select patterns. Conclusion: With the knowledge available, architects can more rapidly select and eliminate combinations of patterns to design solutions. Having this knowledge readily available supports software architects in making more efficient and effective design decisions that meet their quality concerns

Assessing The Potential For Banking Decision Support Systems And Their Role In Making Unstructured Decision Field Study On Syrian Private Commercial Banks

There is an urgent need for accurate information as soon as possible to make quick decisions based on accurate and importance studies, and emerged several systems dealing with these areas, including management information systems, operational information systems, expert systems, including: Decision-making system Support System (DSS), which assists senior management in decision-making that serves the organization's objectives, and decision support systems assist all users regardless of administrative level in administrative decision making. The research aims at assessing the potential of the decision support systems, including the material potential, human potential, technical potential, organizational potential of the studied banks, and their role in decision-making to solve the unstructured problems left by the war. In order to achieve this, two main hypotheses were formulated. The researcher used the questionnaire technique to collect the data analyzed using statistical tests, the most important of which were the one-sample T. test and the Pearson Correlation. The researcher found several results, the most important of which are: The necessary resources for decision support systems are at a good level, and there is a strong positive relationship between the availability of the necessary capabilities for the banking decision support systems and their role in the decision making process in the studied banks.   أصبحت هناك حاجة ماسة إلى المعلومات الدقيقة بأسرع  وقت لاتخاذ قرارات سريعة صائبة مبنية على دراسات بالغة الدقة والأهمية، وظهرت عدة نظم تهتم بهذه المجالات منها نظم المعلومات الإدارية، نظم المعلومات التنفيذية، والنظم الخبيرة ومن ضمن هذه النظم: النظام المتخصص في عملية اتخاذ القرار Decision Support System (DSS) ، الذي يساعد الإدارة العليا في اتخاذ القرار الذي يخدم أهداف  المنظمة، كما أن نظم دعم القرار يساعد كافة المستخدمين بغض النظر عن المستوى الإداري في اتخاذ القرارات الإدارية. ويهدف البحث إلى تقييم الإمكانات اللازمة لنظم دعم القرار وتشمل: الإمكانات المادية، والإمكانات البشرية، والإمكانات الفنية، والإمكانات التنظيمية في المصارف محل الدراسة، ودراسة دورها في اتخاذ القرارات لحل المشكلات غير المهيكلة التي خلفتها الحرب. ولتحقيق ذلك تمّ صياغة فرضتين رئيستين، واستخدم الباحث أسلوب الاستبانة لجمع البيانات الّتي تمّ تحليلها باستخدام اختبارات إحصائيّة أهمّها: اختبار الوسط الحسابي One- Sample t. test، واختبار الارتباط الثّنائي Pearson Correlation. وقد توصل الباحث إلى عدّة نتائج أهمّها: تتوافر الإمكانات اللازمة لنظم دعم القرار بمستوى جيد، كما توجد علاقة طردية قوية بين توافر الإمكانات اللازمة لنظم دعم القرارات المصرفية ودورها في اتخاذ القرارات غير المهيكلة في المصارف محل الدراسة

Factors That Drive the Selection of Business Intelligence Tools in South African Financial Services Providers

Innovation and technology advancements in information systems (IS) result in multiple product offerings and business intelligence (BI) software tools in the market to implement business intelligence systems (BIS). As a result, a high proportion of organisations fail to employ appropriate and suitable software tools meeting organisational needs, resulting in a prime number of BI solution failures and abandoned projects are therefore recorded. Due to such project failures, benefits associated with BI are not realised hence organisations loose enormous investments on BI solutions and competitive advantage. The study aims at discovering and exploring critical factors influencing the selection of BI tools when embarking on the selection process. This is a quantitative research study and questionnaire surveyed data was collected from 92 participants working in South African financial services providers listed on the Johannesburg Stock Exchange (JSE) appearing in the top 100 based on market capitalization. The data was analysed quantitative by employing the use of SPSS and SmartPLS-3 software's to test the significance of influential factors using the proposed conceptual model that emerged from the literature. The findings showed that a combination of domain technical and non-technical factors is critical. Therefore, software tool technical factors (functionality, ease of use, compatibility, availability of an integrated hardware/software package, and availability of source code), vendor technical factors (availability of technical support, technical skills, quality of product, availability of user manual for important information, tutorial for learning and troubleshooting guide, and experience in using product developed by the same vendor), and opinion non-technical factors (end-users, subordinates, outside personnel acquaintances, and improvement in customer service) emerged as significant combination of influential factors to be considered. The study contributes to both academia and industry by providing influential determinants for software tool selection. It is hoped that the findings presented will contribute to a greater understanding of factors influencing the selection of BI tools to researchers and practitioners alike. Furthermore, organisations seeking to select and deliver appropriate BI tools will be better equipped to drive such endeavours

Intelligent Decision Support Systems—An Analysis of Machine Learning and Multicriteria Decision-Making Methods

The selection and use of appropriate multi-criteria decision making (MCDM) methods for solving complex problems is one of the challenging issues faced by decision makers in the search for appropriate decisions. To address these challenges, MCDM methods have effectively been used in the areas of ICT, farming, business, and trade, for example. This study explores the integration of machine learning and MCDM methods, which has been used effectively in diverse application areas. Objective: The objective of the research is to critically analyze state-of-the-art research methods used in intelligent decision support systems and to further identify their application areas, the significance of decision support systems, and the methods, approaches, frameworks, or algorithms exploited to solve complex problems. The study provides insights for early-stage researchers to design more intelligent and cost-effective solutions for solving problems in various application domains. Method: To achieve the objective, literature from the years 2015 to early 2020 was searched and considered in the study based on quality assessment criteria. The selected relevant literature was studied to respond to the research questions proposed in this study. To find answers to the research questions, pertinent literature was analyzed to identify the application domains where decision support systems are exploited, the impact and significance of the contributions, and the algorithms, methods, and techniques which are exploited in various domains to solve decision making problems. Results: Results of the study show that decision support systems are widely used as useful decision-making tools in various application domains. The research has collectively studied machine learning, artificial intelligence, and multi-criteria decision-making models used to provide efficient solutions to complex decision-making problems. In addition, the study delivers detailed insights into the use of AI, ML and MCDM methods to the early-stage researchers to start their research in the right direction and provide them with a clear roadmap of research. Hence, the development of Intelligent Decision Support Systems (IDSS) using machine learning (ML) and multicriteria decision-making (MCDM) can assist researchers to design and develop better decision support systems. These findings can help researchers in designing more robust, efficient, and effective multicriteria-based decision models, frameworks, techniques, and integrated solutions

Development of a decision support system through modelling of critical infrastructure interdependencies : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Emergency Management at Massey University, Wellington, New Zealand

Critical Infrastructure (CI) networks provide functional services to support the wellbeing of a community. Although it is possible to obtain detailed information about individual CI and their components, the interdependencies between different CI networks are often implicit, hidden or not well understood by experts. In the event of a hazard, failures of one or more CI networks and their components can disrupt the functionality and consequently affect the supply of services. Understanding the extent of disruption and quantification of the resulting consequences is important to assist various stakeholders' decision-making processes to complete their tasks successfully. A comprehensive review of the literature shows that a Decision Support System (DSS) integrated with appropriate modelling and simulation techniques is a useful tool for CI network providers and relevant emergency management personnel to understand the network recovery process of a region following a hazard event. However, the majority of existing DSSs focus on risk assessment or stakeholders' involvement without addressing the overall CI interdependency modelling process. Furthermore, these DSSs are primarily developed for data visualization or CI representation but not specifically to help decision-makers by providing them with a variety of customizable decision options that are practically viable. To address these limitations, a Knowledge-centred Decision Support System (KCDSS) has been developed in this study with the following aims: 1) To develop a computer-based DSS using efficient CI network recovery modelling algorithms, 2) To create a knowledge-base of various recovery options relevant to specific CI damage scenarios so that the decision-makers can test and verify several ‘what-if’ scenarios using a variety of control variables, and 3) To bridge the gap between hazard and socio-economic modelling tools through a multidisciplinary and integrated natural hazard impact assessment. Driven by the design science research strategy, this study proposes an integrated impact assessment framework using an iterative design process as its first research outcome. This framework has been developed as a conceptual artefact using a topology network-based approach by adopting the shortest path tree method. The second research outcome, a computer-based KCDSS, provides a convenient and efficient platform for enhanced decision making through a knowledge-base consisting of real-life recovery strategies. These strategies have been identified from the respective decision-makers of the CI network providers through the Critical Decision Method (CDM), a Cognitive Task Analysis (CTA) method for requirement elicitation. The capabilities of the KCDSS are demonstrated through electricity, potable water, and road networks in the Wellington region of Aotearoa New Zealand. The network performance has been analysed independently and with interdependencies to generate outage of services spatially and temporally. The outcomes of this study provide a range of theoretical and practical contributions. Firstly, the topology network-based analysis of CI interdependencies will allow a group of users to build different models, make and test assumptions, and try out different damage scenarios for CI network components. Secondly, the step-by-step process of knowledge elicitation, knowledge representation and knowledge modelling of CI network recovery tasks will provide a guideline for improved interactions between researchers and decision-makers in this field. Thirdly, the KCDSS can be used to test the variations in outage and restoration time estimates of CI networks due to the potential uncertainty related to the damage modelling of CI network components. The outcomes of this study also have significant practical implications by utilizing the KCDSS as an interface to integrate and add additional capabilities to the hazard and socio-economic modelling tools. Finally, the variety of ‘what-if’ scenarios embedded in the KCDSS would allow the CI network providers to identify vulnerabilities in their networks and to examine various post-disaster recovery options for CI reinstatement projects