Construction Of Decision Support System Research Articles

Bridging National Policies with Practical Rural Construction and Development: Research on a Decision Support System Based on Multi-Source Big Data and Integrated Algorithms

While national policies play a crucial role in shaping local development, effective governance is essential for rural revitalization. However, the successful implementation and impact of these policies in rural areas can vary due to unique local circumstances, limited information, and a lack of sophisticated decision making tools. Closing the divide between overarching national policies and practical rural development is an immediate necessity. This study begins by creating a comprehensive five-dimensional evaluation system encompassing industrial economy, public utilities, transportation and logistics, policy and institutions, and resources and the environment. It then summarizes four typical development modes—the suburban fusion mode, the characteristic industry-oriented mode, the humanistic and ecological resource-based mode, and the balanced development mode with less distinct characteristics—through an analysis of the Chinese government’s policy framework for rural construction. Subsequently, it introduces a decision support system for rural construction and development founded on multi-source heterogeneous big data and integrated algorithms. This system was tested using 782 townships as samples for classification, evaluation, and decision support. The results leverages insights into current rural development trends to efficiently align with national policies and provide customized implementation recommendations tailored to local resource characteristics. This contributes to the practical execution of rural revitalization strategies and the advancement of scientific rural decision making.

Semantic web-based diagnosis and treatment of vector-borne diseases using SWRL rules

Vector-borne diseases (VBDs) are a kind of infection caused through the transmission of vectors generated by the bites of infected parasites, bacteria, and viruses, such as ticks, mosquitoes, triatomine bugs, blackflies, and sandflies. If these diseases are not properly treated within a reasonable time frame, the mortality rate may rise. In this work, we propose a set of ontologies that will help in the diagnosis and treatment of vector-borne diseases. For developing VBD’s ontology, electronic health records taken from the Indian Health Records website, text data generated from Indian government medical mobile applications, and doctors’ prescribed handwritten notes of patients are used as input. This data is then converted into correct text using Optical Character Recognition (OCR) and a spelling checker after pre-processing. Natural Language Processing (NLP) is applied for entity extraction from text data for making Resource Description Framework (RDF) medical data with the help of the Patient Clinical Data (PCD) ontology. Afterwards, Basic Formal Ontology (BFO), National Vector Borne Disease Control Program (NVBDCP) guidelines, and RDF medical data are used to develop ontologies for VBDs, and Semantic Web Rule Language (SWRL) rules are applied for diagnosis and treatment. The developed ontology helps in the construction of decision support systems (DSS) for the NVBDCP to control these diseases.

尼泊尔社会经济-生态复合系统恢复力评价及影响因素辨识

PDF HTML阅读 XML下载 导出引用 引用提醒 尼泊尔社会经济-生态复合系统恢复力评价及影响因素辨识 DOI: 10.5846/stxb202202060297 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 中国科学院A类战略性先导科技专项项目（XDA20010302） Assessment of socioeconomic-ecological composite system resilience and its influencing factors analysis in Nepal Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:“一带一路”沿线部分国家处于生态环境脆弱、社会经济落后状态，开展社会经济-生态复合系统恢复力时空特征评估及关键要素识，对于实现"一带一路"倡议"走出去"战略和绿色丝路建设至关重要。基于社会发展、经济水平、基础设施建设、生态环境、自然灾害风险5个一级指标24个二级指标构建了社会经济-生态复合系统恢复力评价指标体系，利用主成分分析法和结构方程模型评价了2000-2015年尼泊尔县域尺度社会经济-生态复合系统恢复力并分析了其时空分异特征，厘清了影响社会经济-生态复合系统恢复力的关键因素及其影响机制。结果表明：①尼泊尔社会经济-生态复合系统恢复力在县域尺度上主要集中在中低和中等恢复力水平，而中高恢复力呈由南向北逐渐降低态势，南部地区以及位于中部发展区的首都加德满都河谷地区恢复力水平相对较高；②2000-2015年尼泊尔社会经济-生态复合系统恢复力在不同阶段呈现波动变化状态，2005年恢复力最优，2010和2015年部分区域恢复力降低明显，系统恢复力区域间差异逐步增大；③社会发展、经济水平、基础设施、建设生态环境和自然灾害风险对系统恢复力提升的总效应分别为0.99，0.07，0.11，0.89和-0.12；按照指标影响程度来看，尼泊尔提升恢复力的关键路径主要在于促进社会经济发展、改善生态环境、推动基础设施建设以及降低灾害风险。未来尼泊尔应依托"一带一路"建设平台加强与周边国家合作交流，提升社会保障与区域均衡发展，促进产业升级及积累资本，发展生态林业并加强灾害监测及决策支持系统建设，实现社会、经济和生态的协同与可持续发展。 Abstract:In the face of multiple crises and challenges brought by global change and intensified human activities, how to cope with various risks and maintain system resilience has become one of the important issues of regional sustainable development. The One Belt and One Road initiative is international economic cooperation initiative put forward by China, which aims to promote economic globalization and win-win international cooperation. While, some countries along the One Belt and One Road are in a fragile ecological environment and backward in social and economic development, such as Nepal whose socioeconomic-ecological composite system has potential low risk resistance characteristics. It is crucial to evaluate the spatiotemporal characteristics of the socioeconomic-ecological composite system resilience of typical countries and identify the key factors for the implementation of the "Go Global" strategy and the Green Silk Road construction. Taking Nepal as case study area, an index system for evaluating the resilience of the socioeconomic-ecological composite system was constructed based on five first-level indicators and 24 second-level indicators from the perspectives of social development, economic level, infrastructure construction, ecological environment, and the natural disaster risk. Then, based on principal component analysis and structural equation model, this paper evaluated the resilience of socioeconomic-ecological composite system at county-level in Nepal from 2000 to 2015, analyzed its temporal and spatial variation characteristics, and clarified the key factors influencing the resilience and its influencing mechanism. The results showed that at the county level, the resilience of the socioeconomic-ecological composite system in Nepal was mainly concentrated at the low and medium levels, while the resilience of the middle and high levels gradually decreased from south to north, and the resilience of the southern region and the Capital Kathmandu Valley in the central development zone was relatively high. In addition, from 2000 to 2015, the resilience of socioeconomic-ecological composite system in Nepal fluctuated and showed spatial differences at different stages. The resilience was the highest in 2005, and decreased significantly in some regions in 2010 and 2015, and the regional differences of the system resilience increased gradually. Moreover, the total effects of social development, economic level, infrastructure construction, ecological environment and natural disaster risk on resilience improvement were 0.99, 0.07, 0.11, 0.89 and -0.12, respectively. According to the effect degree of the factors, the key path to enhance Nepal's resilience mainly lay in promoting social and economic development, improving the ecological environment, promoting infrastructure construction and reducing disaster risk. In the future, Nepal should rely on the "One Belt and One Road Initiative" construction platform to strengthen cooperation and exchanges with neighboring countries, improve social security and the balanced regional development, promote industrial upgrading and capital accumulation, develop ecological forestry, strengthen disaster monitoring and decision support system construction, and realize social, economic and ecological coordination and sustainable development. 参考文献 相似文献 引证文献

ETCD: An effective machine learning based technique for cardiac disease prediction with optimal feature subset selection

Cardiac disease is the leading cause of death worldwide. The early diagnosis and prognosis can help patients live longer by lowering mortality and boosting survival rates. The paucity of radiologists and doctors in various nations, due to a variety of factors, is a substantial barrier to early diagnosis. Computational intelligence is an emerging concept in the field of medical imaging to identify, prognosticate, and diagnose disease, among numerous initiatives to construct decision support systems. It relieves radiologists and doctors from being overworked and reduces the time it takes to diagnose patients promptly. In this work, an effective technique for cardiac disease (ETCD) prediction based on machine intelligence has been proposed. To ensure the success of our proposed model, we used effective Data Collection, Data Pre-processing, and feature selection process to generate accurate data for the training model. ETCD utilizes the optimal feature subset selection algorithm (OFSSA) to extract features from different datasets (Cleveland, Hungarian, Combined dataset, and Z_Alizadeh Saini datasets) having varying properties available at the UCI machine learning repository. With ETCD, the average accuracy performance for considered datasets gets increased with SVM, KNN, DT, NB, and RF classifiers by 6.227%, 2.72%, 7.345%, 14.084%, and 18.921% respectively. Further, the results of the experiments demonstrate that ETCD outperformed several contemporary baseline approaches in terms of accuracy and was comparable in terms of sensitivity, specificity, precision, and F_Score. ETCD returns the best feasible solution among all input predictive models considering performance criteria and improves the efficacy of the system, hence can assist doctors and radiologists in a better way to diagnose cardiac patients.

Good practices and ethical issues in food safety related research

After introducing a historical view of research ethics and the main schools of thought, the paper is structured around two main topics: On the one hand, the protection of the environment surrounding the research experiments conducted, which is a major aspect in food safety related research and includes the staff carrying out the research. On the other hand, collective decision aspects, which are involved in the construction of decision support systems for food safety enhancement. Based on a few examples in food safety related research, the paper reviews the ethical issues considered, the ethical principles applied, and the main measures taken in these cases.

Alternative Marine Fuel Research Advances and Future Trends: A Bibliometric Knowledge Mapping Approach

While the marine sector contributes significantly to the global economy, its environmental impact is a cause for apprehension due to growing concerns about ship emissions. The International Maritime Organization (IMO) has set decarbonization strategies consistent with sustainable development goals. The impending legislation aimed at reducing greenhouse gas (GHG) emissions from maritime shipping by at least half by 2050 and to zero by the end of the century. A growing body of research has focused on alternative marine fuel selection; hence, this bibliometric review is timely. We assess the global scientific research on alternative marine fuel for knowledge mapping based on the articles available on the Scopus database since 1973. A total of 749 publications associated with alternative marine fuel has been subjected to a range of bibliometric analyses to explore this research field quantitatively and qualitatively. The study utilized the R-studio bibliometrics package and VOSviewer bibliometric tools to generate the results. The field of study has a growth rate of 7.05%, having a significant contribution to knowledge from the USA, the United Kingdom, India, and China. Recent trends indicate that researchers are increasingly focused on alternative fuel oil choices. By analyzing commonly used keywords, it was possible to trace a multi-criteria decision analysis process that might be utilized to construct decision support systems for alternative maritime fuel selection. According to relevant articles, the research community has concentrated on the possibility of alternative fuels being utilized in place of traditional marine fuels to reduce emissions from the shipping sector from an environmental, technological, and economic standpoint. The current study offers an updated and comprehensive overview of research trends on alternative marine fuels. Researchers interested in data mapping work in this area can begin with this endeavor.

Selection of a Wheat Harvester according to Qualitative and Quantitative Criteria

With the development of technology and the expansion of agricultural machinery diversity, the need for an appropriate group decision-making system has arisen. The increasing number of criteria and alternatives complicates the decision-making process. Moreover, the uncertainty in the data leads to more complexity in the decision. To select a wheat combine, multiple quantitative criteria were considered, such as the grain tank, rated horsepower, speed draining, and cleaning, along with qualitative criteria, including the level of harvest or harvest losses, fuel consumption, comfort and safety, the ability to harvest wet and lying, and price. To rank seven alternatives through the MULTIMOORA (multi-objective optimization on the basis of ratio analysis) method, a group decision making model applied for qualitative criteria and the Simos method was used for weighting as a subsidiary of mental groups. The performance of the hybrid model was confirmed by experts in agricultural machinery. The consensus model, when used in the process of group decision making, reduces the conflict level of decision-makers regarding criteria, alternatives and the decision matrix. The results of this research will be beneficial for industrial agriculture, especially wheat combine buyers. The proposed explainable consensus model can be used to construct decision support systems and can be applied to various decision-making problems owing to operability and easiness.

DECISION SUPPORT SYSTEM ON THE FORMATION AND IMPLEMENTATION OF THE STRATEGY OF TRANSPORT INFRASTRUCTURE INNOVATIVE DEVELOPMENT

The strategic level of public management of transport infrastructure innovative development is characterized by a high degree of uncertainty in the assessment of the environment, weak formalization of management methods and widespread use of expert assessments and knowledge, multicriteriality in assessing decisions. In order to improve the quality of strategic processes, it is necessary to use decision support systems. Based on the analysis of research, it is determined that decision support systems can overcome the difficulties associated with multicriteria, limited resources and incomplete information. The study identifies three levels of decision support systems, depending on the specifics of the tasks and the technology used. The authors determined the composition of the decision support system, which includes: file accumulation systems; data analysis systems; accounting systems; representative (image) systems; optimization systems; recommendation systems. Based on the existing approaches to the construction of decision support systems and certain procedures of strategic public administration, the article develops a decision support system for the formation and implementation of a strategy for innovative development of transport infrastructure. The authors proposed a system of decision support for the formation and implementation of a strategy for innovative development of transport infrastructure, which includes the consistent implementation of blocks. The study identifies elements of such a system, which include a set of task blocks (goal setting, project proposals, strategic alternatives, motivation, communication, controlling) and tool modules (data, expert evaluation, analytics, modeling). The use of the developed decision support system for the formation and implementation of the strategy of transport infrastructure innovative development allows to increase the quality and validity of strategic decisions and, accordingly, to ensure the possibility of effective implementation of strategic public administration.

Analysis of the implementation of a multi-scenario decision support system in the treatment of lung cancer

The object of the research is the decision support system in the treatment of lung cancer, the subject of the research – the use of a multi-scenario interface in the construction of decision support systems. One of the problem areas in software development is the need for multi-criteria adaptation of interfaces to users. This problem became especially acute after the introduction of quarantine when various automation systems began to develop rapidly, aimed at reducing direct contact between the customer and the service provider. If earlier software users were the more or less related group, now the difference began not only at the level of technical qualifications. Now, when developing software, more attention should be paid to physiological and psychological differences between users, features of hardware and software, environment, and other criteria. In the current situation, it turned out that in most cases automated systems are used by persons who are not interested in these systems but simply have to use them. One of the options for solving this problem is to create an adaptive universal interface. This research is aimed at analyzing methods for implementing multi-scenario decision support systems in the treatment of lung cancer. In the research, attention is paid to the following aspects: adaptive intelligent interface, architecture and structure of the adaptive intelligent interface, algorithms for the functioning of agents of adaptive system interfaces. In the research, the system was used by 500 participants for 30 days. The benchmark was the type of data display scenario selected at the start and end of the day. The research showed a gradual transition of users to scenarios of higher complexity, which involve the analysis of all available information. The tendency of reverse transitions decreases with time, and from the 18th day of using the system, the type of the selected interface changes in rare moments. These results proved the possibility of using automatically configurable interfaces, and bringing them to the final form will be achieved in 18–20 days of using the system.

DSS construction based on the ontology of dairy production

The purpose of the work is to build and implement a decision support system (DSS) in dairy production based on formalized mathematical models and an ontological approach. The decomposition of the process of dairy production is carried out; the main factors influencing it and the relationship between them are highlighted. The ontology of the subject area has been formed, which is presented as a conceptual scheme and a class hierarchy. To describe the sequence of the influence of factors and identify control actions, the Ishikawa scheme for the production of dairy products has been developed. A formalized description of the efficiency of the dairy production process is proposed. A DSS has been developed for the production of dairy products, taking into account the factors associated with the variety and type of forage plants, methods of sowing seeds, pre-sowing preparation, class and type of soil, agro-climatic indicators, fertilization, class of animals and feed additives.

소셜 네트워크 분석을 통한 도시 계획 의사결정지원 시스템 개발 동향 규명 : 생태산업개발(EID)과 관련된 도시 계획을 중심으로

Purpose: This study aims at identifying the development trends of decision support system (DSS) for the urban planning in relation to the ecological industry in order to secure the decision support base for leading sustainable eco-industrial development (EID) within the city. Method: In this study, through text mining technique, key words was extracted from the titles and abstracts of the DSS-related research documents published from 2003 to 2019 in international academia. Their relationships were analyzed through Social Network Analysis (SNA). Result: Most of the extracted key words were analyzed to have close relations with each other in the network. In particular, the very strong link between the ‘circular economy’ and the ‘environment’ showed that the application of the concept of circular economy is needed in the decision-making process. In particular, ‘China’ is the keyword that appeared most frequently in the research documents, which has strong links with other topics, especially with ‘urbanization’, ‘CO₂ emission’, and ‘NPS pollutants’. Researches around the world conducted to economically implement EID and reduce negative social and environmental impacts during the development process show that it is necessary to develop DSS construction to optimize vehicle routes, manage water quality, and minimize carbon dioxide emissions. It was found that while ‘cost’ and ‘policy makers’ are factors that directly influence the decision-making process, ‘sustainable development’ is a factor that has a high mediating influence on the process.

Medical decision-making support system based on bayesian networks in medical diagnostics

Modern level of medical science development provides the attending doctor with thousands of various diagnostic and therapeutic techniques as well as medicines. Practically applicating them, the clinician has to take into account a variety of factors: indications and contraindications of the method or modalities of treatment, characteristics of the patient and the course of the disease, compatibility or strengthening of the influence of certain examination methods, medications on each other, individual drug intolerance and contraindications in the patient. It becomes more difficult to keep all this in memory and make error-free, correct and timely decisions. Moreover, the situation is rapidly aggravated by the fact that the volume of knowledge in medicine is growing incrementally, and the time for a doctor to make an appropriate decision when making a diagnosis does not increase. In this regard, the question of creating a system that will minimize the time for a doctor to make a decision on the presence of a particular disease arises.
 AIM: To develop a medical decision-making support system based on Bayesian networks in diagnosing patients.
 RESULTS: A variant of the medical decision support system for the diagnosis of cold, flu and coronavirus are considered. A Bayesian network model using the GeNIe Academic software is proposed. The results of the percentages of possible diseases of the patient based on the existing symptoms are obtained.
 CONCLUSION: The approach to the decision support system construction considered in the article is intended to assist doctors in making a diagnosis to a patient based on his anamnesis. It should be noted that the constructed Bayesian network can be modified by adding other symptoms with their conditional probabilities and adjusting the existing ones after expert judgment (6 figs, bibliography: 6 refs).

Construction of decision support system of standardized diagnosis and treatment on nutrition in cancer patients

Rationale: Our previous data had showed that more than half of cancer patients with nutritional risks did not receive nutritional therapy, and 50% of patients received inappropriate treatment in China.(1) Here, we propose to establish a decision support system of standardized diagnosis and treatment on nutrition based on .NET procedures in Sir Run Run Shaw Hospital (SRRSH) to improve quality of life and prognosis of cancer patients.

РОЗРОБКА МОДЕЛІ ЗНАНЬ ДЛЯ ІНФОРМАЦІЙНОЇ СИСТЕМИ ПІДТРИМКИ ПРИЙНЯТТЯ РІШЕНЬ АВІАЦІЙНИМ ОПЕРАТОРОМ ПРИ ВИНИКНЕННІ ОСОБЛИВИХ ВИПАДКІВ В ПОЛЬОТІ

Предметом вивчення в статті є методи, що дозволяють вирішити проблему невизначеності в процесі побудови систем підтримки прийняття рішень авіадиспетчера при виникненні особливих випадків в польоті. Метою є аналіз і обґрунтування вибору математичного апарату для побудови СППР авіадиспетчера. Завдання: аналіз ряду відомих методів інтелектуального аналізу даних, а саме: еволюційних алгоритмів, нейронних мереж, нечіткої логіки та байєсівських мереж з точки зору доцільності їх застосування при побудови систем підтримки прийняття рішень авіадиспетчера управління повітряним рухом при виникненні особливих випадків в польоті. Використовуваними методами є: методи аналізу і синтезу складних інформаційних систем, методи імітаційно-статистичного моделювання. Отримано такі результати. В результаті проведеного аналізу було встановлено, для побудови моделі СППР авіадиспетчера найбільш ефективним є використання апарату байєсівських мереж, який представляє собою перспективний ймовірнісний інструментарій, що дозволяє моделювати складні ієрархічні статичні та динамічні системи. Це обумовлено тим, що на відміну від популярних на даний час моделей "чорних скриньок" байєсівська мережа дозволяє отримати зрозуміле пояснення одержаних висновків, має їх логічну інтерпретацію, надає можливість врахування невизначеностей параметричного, статичного і структурного характеру і, що є особливо важливим, ґрунтується на фундаментальних положеннях теорії ймовірностей, яка розроблялась не одне сторіччя. Висновки. Напрямком подальших досліджень є побудова системи підтримки прийняття рішень авіадиспетчера з використанням байєсівських мереж і технології ймовірнісного програмування

Model of the geospatial situation of the decision support system for automatic determination of inland vessel movement

Abstract The development of modern IT techniques and technologies creates appropriate possibilities for automation of navigation and construction of decision support systems in ship control. The solutions proposed by these systems should ensure the safe performance of maneuvers, take into account applicable traffic regulations and should be rational, i.e. apply criteria used and accepted by people. The basis for implementing these types of systems is the analysis of decision-making processes in ship control carried out by navigators. The development of the decision process model is the basis for the design and construction of navigator decision support systems. The article presents a comprehensive analysis of issues related to modelling of decision-making situations and implementation of decision-making processes in ship control in a restricted (inland) area. The paper presents methods and algorithms for decision support in a collision situation, defining a safe trajectory, taking into account elements of the ship’s own dynamic properties, road law provisions, navigation restrictions and changes in the strategy of behavior in relation to various objects encountered. The purpose of this article is the concept of a model of decision support system within a specific geospatial situation in three dimensions for complex calculations regarding the movement of inland vessels.

МОДЕЛЮВАННЯ РОЗХОДЖЕННЯ СУДЕН У СИСТЕМІ ПІДТРИМКИ ПРИЙНЯТТЯ РІШЕНЬ СУДНОВОДІЯ

The aim of the study is to develop modern conceptual approaches to the construction of decision support systems in navigation, to determine the theoretical and practical foundations for creating such systems and priority ways of their practical implementation. From the analysis of recent publications, it has been revealed that the widespread use of new information technologies and modern technical means of navigation leads to an increase in the detail of the present navigation situation, but at the same time its assessment becomes more complicated and the time available to the navigator for analysis and development of the necessary control decision is reduced. For this reason, the development of decision support systems (DSS) for the navigator, which use new meaningful models of the hazard identification process for navigating a ship in the event of prerequisites for an emergency, is an urgent task of the present time. The creation of such systems will reduce the negative impact of the human factor on the processes of ship traffic control. The article develops theoretical and practical foundations for constructing a DSS for a navigator, taking into account the peculiarities of the movement of ships, the process of human interaction with technical means of navigation. The article develops theoretical and practical foundations for constructing a DSS for a navigator, taking into account the peculiarities of the movement of ships, the process of human interaction with technical means of navigation. New mathematical models of control over the process of divergence of ships are proposed. The classification of ships according to the degree of danger is carried out, depending on the change in the angle of the line of their relative movement. Criteria for a quantitative assessment of the hazard level of a ships based on the analysis of changes in the angle of the line of its relative motion are presented. The results obtained are the basis for further increasing the efficiency of the functioning of the ergatic system «man - technical means of navigation» and the comprehensive implementation of the achievements of new information technologies in the ship control processes.

Research of data mining and web technology in university discipline construction decision support system based on MVC model

PurposeTaking the discipline construction in colleges and universities as the application background, based on the research on data mining technology and decision support system technology, the data generated by university management information system are effectively utilized. The paper aims to discuss these issues.Design/methodology/approachBased on the Beijing Key Discipline Information Platform as the data source, the decision tree algorithm of data mining is studied. On the basis of decision tree C4.5, the Bayesian theory is applied to the post-pruning operation of the decision tree.FindingsA decision tree post-pruning algorithm based on the Bayesian theory is studied and put forward in order to simplify the decision tree, which improves the generalization ability of the whole algorithm. Finally, the algorithm is used to build the prediction model of key disciplines. Combined with the decision support system architecture, data warehouse and the data mining algorithm constructed by university discipline, based on J2EE standard enterprise system specification, MVC model is applied. Moreover, a prototype system of decision support system for discipline construction in colleges and universities with browser/server (B/S) structure is completed and implemented.Originality/valueA decision tree post-pruning algorithm based on the Bayesian theory is studied and put forward in order to simplify the decision tree, which improves the generalization ability of the whole algorithm. Finally, the algorithm is used to build the prediction model of key disciplines. Combined with the decision support system architecture, data warehouse and the data mining algorithm constructed by university discipline, based on J2EE standard enterprise system specification, MVC model is applied. Moreover, a prototype system of decision support system for discipline construction in colleges and universities with B/S structure is completed and implemented.

Aplikasi Pemilihan Supplier Menggunakan Metode Profile Matching (Studi Kasus: Toko Maju Jaya)

The supplier is a business run by parties who disburse a product to a person or a company. In carrying out its operational activities Maju Jaya Store get supply of products from various suppliers. There are several suppliers selling the same item with different offerings, making it difficult for the shop owner to decide on the supplier to be selected when going to the rest of the goods. Currently supplier selection is done by contacting one by one supplier via telephone to find the best offer. This certainly takes a lot of time as well as cost. Resolving the problems that have been exposed is with the construction of Decision Support System of supplier selection using Profile Matching Method. The supplier selection process begins with the determination of criteria and sub criteria, weighting criteria then calculating and grouping core and secondary factors, calculating the total value, and then the system will display the rank of the supplier to be selected for consideration in decision making. Based on the test that is done alpha and beta testing yield percentage of success equal to 100%. While the real data comparison test and using Profile Matching Method has a success percentage 80%.

Aplikasi Pemilihan Supplier Menggunakan Metode Profile Matching (Studi Kasus: Toko Maju Jaya)

The supplier is a business run by parties who disburse a product to a person or a company. In carrying out its operational activities Maju Jaya Store get supply of products from various suppliers. There are several suppliers selling the same item with different offerings, making it difficult for the shop owner to decide on the supplier to be selected when going to the rest of the goods. Currently supplier selection is done by contacting one by one supplier via telephone to find the best offer. This certainly takes a lot of time as well as cost. Resolving the problems that have been exposed is with the construction of Decision Support System of supplier selection using Profile Matching Method. The supplier selection process begins with the determination of criteria and sub criteria, weighting criteria then calculating and grouping core and secondary factors, calculating the total value, and then the system will display the rank of the supplier to be selected for consideration in decision making. Based on the test that is done alpha and beta testing yield percentage of success equal to 100%. While the real data comparison test and using Profile Matching Method has a success percentage 80%.

Construction of Decision Support System (DSS) for Equipment Support Based on Big Data

To build a Decision Support System(DSS) for equipment support based on big data analysis, The connotation and structure of DSS in big data environment are studied, and the data elements and decision scenario of big data decision for equipment support are analyzed. The basic framework of big data decision system for equipment support is preliminarily constructed. The purpose of this paper is to provide guidance and reference for the application of big data technology in the field of equipment support.