Decision Support System Software Research Articles

Sustainable development of smart cities and smart territories based on the model of minimizing externalities.

The development of conceptual models of a digital city poses numerous challenges for developers. The public sector concept model has become one of the most difficult models to use. When developing algorithms to find a solution, the multidirectional interests of businesses and public institutions are combined. This type of model reflects the most acute and urgent problems faced by megapolises with regard to combining numerous localized services provided to the community in a limited territory. The administrations of both cities and regions (the scale of the smart territories) must make decisions concerning overcoming the barriers existing between the profits of commercial structures, the negative externalities generated by their activities, and the social benefits to the population in the territory under their control. It is necessary to solve this problem to achieve the effective management of enterprises belonging to the segment of long-term participants in various business activities, interacting with the surrounding social and business environment in a complex. This study takes into account the complex structures of the economic processes characteristic of megacities. The periodicity of economic processes is also taken into account. When choosing an optimization criterion, functions reflecting the level of internalization of responsibility for external effects were considered. The authors propose a mathematical model that can be used as part of the management decision support systems software, aiming at taking into account the externalities of a wide range of national, institutional, business, and social activities.

Sustainable development of smart cities and smart territories based on the model of minimizing externalities

The development of conceptual models of a digital city poses numerous challenges for developers. The public sector concept model has become one of the most difficult models to use. When developing algorithms to find a solution, the multidirectional interests of businesses and public institutions are combined. This type of model reflects the most acute and urgent problems faced by megapolises with regard to combining numerous localized services provided to the community in a limited territory. The administrations of both cities and regions (the scale of the smart territories) must make decisions concerning overcoming the barriers existing between the profits of commercial structures, the negative externalities generated by their activities, and the social benefits to the population in the territory under their control. It is necessary to solve this problem to achieve the effective management of enterprises belonging to the segment of long-term participants in various business activities, interacting with the surrounding social and business environment in a complex. This study takes into account the complex structures of the economic processes characteristic of megacities. The periodicity of economic processes is also taken into account. When choosing an optimization criterion, functions reflecting the level of internalization of responsibility for external effects were considered. The authors propose a mathematical model that can be used as part of the management decision support systems software, aiming at taking into account the externalities of a wide range of national, institutional, business, and social activities.

Sustainable development of smart cities and smart territories based on the model of minimizing externalities

The development of conceptual models of a digital city poses numerous challenges for developers. The public sector concept model has become one of the most difficult models to use. When developing algorithms to find a solution, the multidirectional interests of businesses and public institutions are combined. This type of model reflects the most acute and urgent problems faced by megapolises with regard to combining numerous localized services provided to the community in a limited territory. The administrations of both cities and regions (the scale of the smart territories) must make decisions concerning overcoming the barriers existing between the profits of commercial structures, the negative externalities generated by their activities, and the social benefits to the population in the territory under their control. It is necessary to solve this problem to achieve the effective management of enterprises belonging to the segment of long-term participants in various business activities, interacting with the surrounding social and business environment in a complex. This study takes into account the complex structures of the economic processes characteristic of megacities. The periodicity of economic processes is also taken into account. When choosing an optimization criterion, functions reflecting the level of internalization of responsibility for external effects were considered. The authors propose a mathematical model that can be used as part of the management decision support systems software, aiming at taking into account the externalities of a wide range of national, institutional, business, and social activities.

Automatic Detection of Dentigerous Cysts on Panoramic Radiographs: A Deep Learning Study

Aim: The aim of this study is to create a model that enables the detection of dentigerous cysts on panoramic radiographs in order to enable dentistry students to meet and apply artificial intelligence applications.
 Methods: E.O. and I.T. who are 5th year students of the faculty of dentistry, detected 36 orthopantomographs whose histopathological examinations were determined as Dentigerous Cyst, and the affected teeth and cystic cavities were segmented using CranioCatch's artificial intelligence supported clinical decision support system software. Since the sizes of the images in the dataset are different from each other, all images were resized as 1024x514 and augmented as vertical flip, horizontal flip and both flips were applied on the train-validation. Within the obtained data set, 200 epochs were trained with PyTorch U-Net with a learning rate of 0.001, train: 112 images (112 labels), val: 16 images (16 labels). With the model created after the segmentations were completed, new dentigerous cyst orthopantomographs were tested and the success of the model was evaluated.
 Results: With the model created for the detection of dentigerous cysts, the F1 score (2TP / (2TP+FP+FN)) precision (TP/ (TP+N)) and sensitivity (TP/ (TP+FN)) were found to be 0.67, 0.5 and 1, respectively.
 Conclusion: With a CNN approach for the analysis of dentigerous cyst images, the precision has been found to be 0.5 even in a small database. These methods can be improved, and new graduate dentists can gain both experience and save time in the diagnosis of cystic lesions with radiographs.

Project Management System of Exploration Program in the Light of Prioritizing of Reservoir Engineering Stages According to the Criterion of Prospects

A model of the project portfolio management system of a geological exploration enterprise has been developed, taking into account the stages of work. The model includes a control object, a decision-making subsystem, which includes a control device represented by the decision support software system “Balance of Groundwater Availability” (BGA) and an executive device represented by a decision-maker, making decisions at a geological exploration enterprise. The stimulus to the target asset arises on the one hand in connection with the implementation of sectorial and federal programs within the area for the development of the geological industry and the reproduction of mineral resources, on the other hand, it is the need to maintain a certain balance of the availability of raw materials in the region, in particular, underground water. Hence, it is necessary for the underground water exploration company to take into account the specifics of the programs in view of the interconnection of the sites within one large field of regional scale. In this case, the project portfolio needs to be managed, taking into account the network nature of their interaction, i.e. mutual influence on the remaining sections of the field. On the other hand, when forming a portfolio of projects of a geological exploration enterprise, it is necessary to take into account staging and phasing of geological exploration, their seasonal nature allows viewing the model of the management system in the context of discrete time. The work was carried out with the financial support of the grant of the President of the Russian Federation No. MD-2409.2020.5.

Construction of algorithms for solving the inverse problem when using indicators in several calculation functions

This paper reports a solution to the inverse problem when using indicators in several calculation functions. Such problems arise during the formation of a multi-level scorecard; solving them makes it possible to determine the value of arguments in order to achieve the specified value of the resulting indicator of each level. Thus, the characteristics of an economic object can be defined in order to achieve the specified indicators of its functioning. Optimization models are given in the presence of various types of conditions for achieving the result. In contrast to existing methods, the approach based on building nonlinear programming models makes it possible to solve the inverse problem for the case where several indicators are used in different calculation functions. Algorithms for solving the inverse problem have been constructed, involving the transformation of constraints and the use of an iterative procedure based on inverse calculations. For the case of using coefficients of relative importance, two techniques of solving the problem have been considered: the formation of a single model for subtasks and the adjustment of the solution to subtasks while minimizing the sum of squares of argument changes. In comparison with the existing method, the proposed algorithms have made it possible to derive a solution with a greater correspondence of the changes in the arguments to the coefficients of relative importance. A solution to the inverse problem has been considered related to the formation of marginal profit of an enterprise in the presence of two points of sale and three types of products, as well as the joint formation of revenue and cost. The results of this study could prove useful to specialists in the field of decision-making in the economy and to developers of software decision support systems that include functions for solving inverse and optimization problems.

Супервизорное управление исполнительными механизмами машин лесозаготовок и лесного хозяйства

The article presents structural diagrams of an automated control system for technological processes and information flows of logging operations. The article includes subject and research methodology. The study in a field of logging operations confirms the fact of increasing rate of using special forest machinery like forest harvesters for conducting timber-logging operations. One of the main advantages of forest harvesters is the automated functions that allow the control system to optimize the cutting of the tree trunk, taking into account the price of the assortment and its optimal parameters. The majority of forest harvesters in service are equipped with a continuous pull-through harvesting head. It is shown that reducing production and resource losses, preserving the natural environment and adequate measures for the reproduction of wood resources becomes possible due to the transfer of management of forestry processes to a qualitatively new level through the use of modern automated control systems for technological processes and information flows (APCS IP). The development of a software decision support system (DSS) was conducted according to the results of the data process analysis. The automated decision support system provides support for operator activities and a model for making a decision on the appointment and execution of timber-logging operations.

Efficient and Sustainable Reconfiguration of Distribution Networks via Metaheuristic Optimization

Improving the efficiency and sustainability of distribution networks (DNs) is nowadays a challenging objective both for large networks and microgrids connected to the main grid. In this context, a crucial role is played by the so-called network reconfiguration problem, which aims at determining the optimal DN topology. This process is enabled by properly changing the close/open status of all available branch switches to form an admissible graph connecting network buses. The reconfiguration problem is typically modeled as an NP-hard combinatorial problem with a complex search space due to current and voltage constraints. Even though several metaheuristic algorithms have been used to obtain—without guarantees—the global optimal solution, searching for near-optimal solutions in reasonable time is still a research challenge for the DN reconfiguration problem. Facing this issue, this article proposes a novel effective optimization framework for the reconfiguration problem of modern DNs. The objective of reconfiguration is minimizing the overall power losses while ensuring an enhanced DN voltage profile. A multiple-step resolution procedure is then presented, where the recent Harris hawks optimization (HHO) algorithm constitutes the core part. This optimizer is here intelligently accompanied by appropriate preprocessing (i.e., search space preparation and initial feasible population generation) and postprocessing (i.e., solution refinement) phases aimed at improving the search for near-optimal configurations. The effectiveness of the method is validated through numerical experiments on the IEEE 33-bus, the IEEE 85-bus systems, and an artificial 295-bus system under distributed generation and load variation. Finally, the performance of the proposed HHO-based approach is compared with two related metaheuristic techniques, namely the particle swarm optimization algorithm and the Cuckoo search algorithm. The results show that HHO outperforms the other two optimizers in terms of minimized power losses, enhanced voltage profile, and running time. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This article is motivated by the emerging need for effective network reconfiguration approaches in modern power distribution systems, including microgrids. The proposed metaheuristic optimization strategy allows the decision maker (i.e., the distribution system operator) to determine in reasonable time the optimal network topology, minimizing the overall power losses and considering the system operational requirements. The proposed optimization framework is generic and flexible, as it can be applied to different architectures both of large distribution networks (DNs) and microgrids, considering various types of system objectives and technical constraints. The presented strategy can be implemented in any decision support system or engineering software for power grids, providing decision makers with an effective information and communication technology tool for the optimal planning of the energy efficiency and environmental sustainability of DNs.

IMPLEMENTASI TOPSIS DALAM PEMBERIAN REWARD GURU TERBAIK PADA SMK SWASTA 1 HKBP PEMATANGSIANTAR

Reward is a form of appreciation received by an individual for the achievement of a work performance that aims to motivate the individual to have high productivity. In managerial terms, giving a warning is a good and reasonable thing to do by the leader to his subordinates. Likewise with the Private Vocational School 1 HKBP Pematangsiantar. This research was conducted to provide solutions to problems that occur through the design of a decision support system software for giving the best teacher reward with the Technique for Order Preferences by Similarity to Ideal Solution (TOPSIS) method with assessment components including (1) discipline, (2) involvement, (3 ) attendance, (4) leadership, (5) training and (6) social. The Decision Support System for providing teacher rewards is able to accommodate subjective problems, lack of transparency, and doubts about its accuracy and the output is very credible. Thus the decision-making process for giving the best teacher reward is efficient, effective and objective and can be used as a recommendation for school principals in determining which teachers deserve rewards. From the 10 data samples used, the results of the analysis using the Decision Support System show that the highest recommendation value is 0.7149 on behalf of A8, while the lowest recommendation value is 0.2851 on behalf of A10. Recommendation, DSS, TOPSIS, Reward

405. Trend in blood culture results in Washington DC during and prior to Pandemic COVID-19

BackgroundThe rate of bacterial and/or fungal infections among COVID-19 cases is reportedly low. Antimicrobial Stewardship Programs (ASPs) provide continuous surveillance of blood cultures to secure appropriate choice and duration of therapy. Comparing to historic data, we characterize our ASP experience in bacteremic surveillance during the COVID-19 pandemic.MethodsConsecutive blood cultures at the Washington DC VA Medical Center were captured in an ASP-driven decision support software system (TheraDoc, Premier/DSS Inc) between Jan 1st 2018-May 31st 2020. In the setting of an established ASP, the organism positive cultures were reviewed over the first five months (Jan-May) of each of the three years collected. Results of cultures were characterized as either pathogenic gram positive (MSSA/MRSA/Enterococci/PSSP/PRSP/Strep sp.), pathogenic aerobic and anaerobic gram negative organisms and a skin contaminant-category (GPRs/skin flora/CNS).ResultsOver 3 yrs, 528 patients had 1464 positive cultures from among 8727 admissions, 83638 inpatient-days. The proportion of pathogenic GP bacteria and pathogenic GN bacteria were not statistically significantly different 38% (2018) vs 37% (2019) vs 39% (2020) and 33%, 31%, 27% respectively. There was slight trend in the increase of pathogenic GP 9.6 vs 9.5 vs 11.7 per 1,000 inpatient days and skin contaminant-category with 12.0 vs 11.0 vs. 14.1 per 1,000 patient days from 2019 to 2020. We noted a dramatic shift in culture surveillance report during the peak COVID-infection rates (March-April), notable for several weeks of few to no culture positive results. When broken down by month, variability was noted (data not shown). COVID-19 infected patients represented 9.0% (7/78) of positive blood culture results in 2020 Jan-May, only 5.1% (4/78) were treated as non-contaminants and were related to indwelling catheters or urosepsis.ConclusionOverall and adjusted rates of the blood cultures sent during the pandemic months in 2020 were comparable to the comparative years. Surveillance revealed short term changes in patterns which may have reflected the pandemic induced changes to admissions. COVID-19 infected patients rarely experienced line and hospital acquired bactermia/fungemia, most during the recovery period.Disclosures All Authors: No reported disclosures

Интеллектуальная программная система оптимизации адаптивного управления процессами бизнес-планирования

The article describes the functionality developed by the authors of an intelligent software system for optimizing adaptive control of business planning processes in the face of uncertainty. The results are based on a new method for optimizing adaptive project management using network economic and mathematical modeling. Based on this method, a methodology has been developed for solving the problem of optimizing adaptive control of business planning processes, which in the proposed intelligent software decision support system uses a block containing an adaptive control optimization model. As the objective function (evaluation functional) in the method used, the value of the length of the time period for the execution of the business plan, which needs to be minimized, is considered. The method used allows you to create a class of acceptable strategies for adaptive control of the implementation process for the business plan in question. Within the framework of this class of strategies, an optimal adaptive control strategy for the implementation of business planning processes is formed, the optimal time for its implementation and the optimal schedule for implementing the business plan as a whole, and the corresponding optimal adaptive control strategies are calculated. Application of the proposed new method in an intelligent software system allows for feedback and optimal time for the implementation of the business project as a whole. The developed intelligent system is designed to automate the modeling of business planning processes and optimize adaptive decision-making control during their implementation on the basis of network economic and mathematical modeling, as well as methods and tools for developing intelligent soft systems. The created system takes into account the existing specific technical and economic conditions and information support. The results obtained in this work can serve as the basis for creating intelligent instrumental systems for supporting managerial decision-making in the implementation of business planning processes in the face of information uncertainty and risks.

The method of increasing the efficiency of the man-machine system functioning by improving the quality of decision support system software

The article addresses improving the performance of man-machine systems (MMS) by improving the quality of decision support system software (DSSS). The proposed solutions are based on existing models and methods, which have been analysed in detail in a scientific study, in particular the application of methodical static application debugging in certain solutions obtained. It is proposed to use the methods for solving the problem of MMS control according to the vector criterion as the basis for solving this problem. A mechanism for synthesizing a comprehensive plan of operations to improve the quality of the DSS software is proposed, and the possibility of analysing the step-by-step implementation of a plan to obtain an analytical assessment is shown. For this purpose, a comprehensive plan is presented in the form of a relevance tree, built in accordance with the provisions of graph theory and the rank approach. The time complexity of the algorithms implementing the relevance tree tasks was evaluated. Based on the formalized solutions obtained, it was found that the maximum number of edges for a graph that implements the relevance tree does not exceed , the number of views of edges does not exceed , that is, the total number of operations that implements the scanning of edges and adding them to the weighted minimum cover (WMC) does not exceeds . It is established that during the implementation of the operation of adding ribs in the WMC, at each step, after the fixation of the previous result, the number of ribs to be examined decreases, so the total complexity of the algorithms will not exceed . The solutions obtained meet the requirements of DSTU ISO/IEC 9126, ISO DSTU / IEC 14598, and take into account the requirements of the Software Quality Requirements and Evaluation series of standards as the value of the vertices of the event tree graph. In the process of solving the problem, the specificity of the functioning of the MMS was taken into account, the possibility of formalizing various aspects of knowledge (aesthetic, disizional, causal, diontic) and ensuring a given level of efficiency in finding solutions.

A new software architecture proposal for an evidence-based Decision Support System in dentistry.

in dentistry, clinical problems could be resolved using many therapeutic approaches that may results in very different therapies. In order to choose the best option, a good evaluation of therapy long-term survival and success rate is mandatory. The routine use of a decision support analysis software is nowadays limited due to the lack of software's flexibility especially when a variety of possible therapeutic option are present. The aim of this research was to develop a new algorithm model for a Decision Support System software to give diagnosis support in dentistry. Beta tests were designed to study the computer software in different clinical situations based on clinical data. The therapeutic options can be conservative/endodontic or extractive/prosthetic therapies. In two of clinical situation selected could be possible to choose both therapies. in clinical situations tested, the DDS software correctly identified the several therapeutic options. When multiple treatments were possible the beta test showed an output mask that correctly showed a range of options with their corresponding survival and success rate. The software architecture proposed by the authors is technically feasible, can support the clinician choices based on scientific evidence and up-to-date references and gain informed consent based on data easily understandable for the patient.

Implementasi Metode Simple Additive Weighting (SAW) Pada Sistem Informasi Evaluasi Kinerja Guru (Studi Kasus SMK Utama Bandar Lampung)

AbstrakEducation in Indonesia continues to improve throughout the 21st century. This is none other than because of the continuous evaluation of the education system which provides information on the lack of educational gaps and their renewal. Therefore, SMK Utama Bandar Lampung is present in the middle of the community at very affordable costs and is supported by qualified teachers or teachers. Each teacher or teacher conducts a process of selecting the best teachers to get qualified teaching staff. However, data management management of the achievement of the question has not yet been implemented to produce the right decision. This is because it takes time to process the results of questions and in the process of determining teacher performance it is possible for errors to occur. Based on this description, SMK Utama Bandar Lampung requires a decision support system that is expected to find solutions in the process of determining the best teacher. Assessment of decision systems that can facilitate the process of processing data on teacher performance assessment results in SMK Utama Bandar Lampung. Therefore, the researcher proposes a decision support system software engineering using Simple Additive Weighting (SAW). This system can be used to make it easier for students to assess teachers at SMK Utama Bandar Lampung, to help schools, especially principals, in evaluating the shortcomings and strengths of teacher performance at SMK Utama Bandar Lampung.

Interviews with experts in rare diseases for the development of clinical decision support system software - a qualitative study

BackgroundPatients with rare diseases (RDs) are often diagnosed too late or not at all. Clinical decision support systems (CDSSs) could support the diagnosis in RDs. The MIRACUM (Medical Informatics in Research and Medicine) consortium, which is one of four funded consortia in the German Medical Informatics Initiative, will develop a CDSS for RDs based on distributed clinical data from ten university hospitals. This qualitative study aims to investigate (1) the relevant organizational conditions for the operation of a CDSS for RDs when diagnose patients (e.g. the diagnosis workflow), (2) which data is necessary for decision support, and (3) the appropriate user group for such a CDSS.MethodsInterviews were carried out with RDs experts. Participants were recruited from staff physicians at the Rare Disease Centers (RDCs) at the MIRACUM locations, which offer diagnosis and treatment of RDs.An interview guide was developed with a category-guided deductive approach. The interviews were recorded on an audio device and then transcribed into written form. We continued data collection until all interviews were completed. Afterwards, data analysis was performed using Mayring’s qualitative content analysis approach.ResultsA total of seven experts were included in the study. The results show that medical center guides and physicians from RDC B-centers (with a focus on different RDs) are involved in the diagnostic process. Furthermore, interdisciplinary case discussions between physicians are conducted.The experts explained that RDs exist which cannot be fully differentiated, but rather described only by their overall symptoms or findings: diagnosis is dependent on the disease or disease group. At the end of the diagnostic process, most centers prepare a summary of the patient case. Furthermore, the experts considered both physicians and experts from the B-centers to be potential users of a CDSS. The experts also have different experiences with CDSS for RDs.ConclusionsThis qualitative study is a first step towards establishing the requirements for the development of a CDSS for RDs. Further research is necessary to create solutions by also including the experts on RDs.

Decision Support System for Selection of Achieving Students Using the Multi Attribute Rating Technique Method

The background of this research is the process of selecting students in SMA Negeri 1 Sumberpucung so far is still not objective because it only looks at the best report card grades without any other process. That causes the inappropriate selection of high achieving students in SMA Negeri 1 Sumberpucung because the student is not only assessed in terms of report cards but also needs to consider other factors. So the selected students can represent the school at a higher level, namely the district and provincial levels. The purpose of this study is to build a decision support system to help selectors make the selection of high achieving students in SMA Negeri 1 Sumberpucung and assist in making decisions in the selection process of high achieving students using the Simple Multi Attribute Rating Technique (SMART) method. The stages of the research method used the waterfall software development method. In the first stage, an analysis of input and output needs is carried out, the second stage is by designing a decision support system using the SMART method, the third stage is customizing the decision support system, the fourth stage of program testing and the final stage of program implementation. The Decision support system is built based on the web and uses a MySQL database. From this research, it is expected to be able to produce an application or decision support system software. Keywords: Decision Support System; Student Achievement Selection; Simple Multi Attribute Rating Technique (SMART) DOI: 10.7176/IKM/10-5-06 Publication date: August 31 st 2020

Applying the Weighted Product Method for The Best Selection of Personal Quality Control in Pt. Pacific Equinox Surabaya

The aim of this research is to design and implement a decision support system software for the selection of the best quality control at PT. Pacific Equinox Surabaya. The intent and purpose of this research is to study the process of selecting the best employees who have been working on a manual system into a computerized system and use the Weighted Product method as an algorithm to facilitate the process of selecting the best employees.This system also has the advantage of helping the management process data and values of PT. Pacific Equinox Surabaya employees. In addition, more efficient time efficiency and also helps in the process of making reports required by management.The results of this study are applications that can make it easier to analyze a number of data, in order to help provide information as a result of the best employee decision making. But this system also still has weaknesses in terms of facilities and program appearance so that it still needs improvement

DIAGNOSTIC SYSTEM OF PERCEPTION OF NAVIGATION DANGER WHEN IMPLEMENTATION COMPLICATED MANEUVERS

Context. The article focuses on the question of automated decision-making analysis made by the operator in ergatic systems of critical infrastructures on the example of marine transport control in difficult navigation conditions. It is evident enough that the main criterion for an adequate perception of input information done by an operator is highly likely to predict the choice of behavioral decision-making strategies in discrete time conditions. However, the difficulty of modeling the operator’s actions is found to be lying in non-linear pattern of taking definite decisions in emergency situations and deviations from the Codes and Rules.Objective. The research purpose strategy of conducted investigation can be defined as the development of the mathematical platform for a decision support system (DSS) module with an aim to identify the class-forming set of atomic elements. In particular this issue determines the fact of distortion of the perception of information about navigation risks predicting the operator’s behavior pattern while having vessel running process. This is possible to have it depicted through formal analysis.Method. To capture the analysis of danger perception by the operator the paper introduces a mathematical model of data collection which identifies the fact of perception distortion in the form of attribute space of metadata obtained by the method of converting information from navigation devices. Besides, the factor of disorientation of the operator can be considered to be a shift on a displaced bridge which significantly affects on the analysis of information for adequate decision making. In addition, taking into account the failure of navigation equipment such as: RADAR, ARPA, AIS, ECDIS, especially while doing exit from the automatic control mode, a dangerous precedent can possibly be created for the operator not ready to perceive the complexity of the situation. To make it work a formal analysis was carried out using the extending risks possibility level tasks during the transition under these conditions. In addition to this item, a probabilistic model of perceiving the situation under the conditions of the error set is reported to have been constructed. So, as the result, the modeling process turned out to show the definite evidence of getting no way possibility to have the degree of criticality of the navigation situation determined without a clear identification of factors affecting the distortion of perception of the operator. Nevertheless, generalized statistical data are sure to be not enough and there is a special need of taking into account an individual information model of each operator for the effective work of DSS as this process faces real challenges. It must be significantly noticed that in order to analyze the perception of information by the operator a special test for defining preferences when choosing a strategy of control actions in the form of maneuvering under difficult navigation conditions purpose was created. Regarding the test results, as well as data on the passage of locations, certain attention is advised to be drawn to the classification analysis of 15 parameters using artificial neural networks having been carried out by our team and, as a consequence, the boundaries of deviations in the perception of navigational danger were found out and clarified. Additional superior item to be spoken about is certainly the introduction of rules and algorithms having been welcomed into the DSS core including the following: interaction field, RADAR and NIS synchronization tools; actual navigational hazard in a given cartographic area; ships trajectories and, as a result, simulations of probable deviations in the information perception of the operator.Results. In order to meet beneficial agreement between the effectiveness of the developed DSS with the proposed formalanalytical approaches an experiment was assumed to be appropriate to be conducted using the Navi Trainer 5000 navigation simulator (NTPRO 5000). Based on the foregoing, due to comprehensive results in experiment metadata for the 2.5 years of operation of navigation simulators and DSS software tools the identification of the deviation probabilities in the information perception of dangers was achieved and export the predicted data to new locations for the operator and cartographic areas was performed. Undoubtedly, the experimental investigation confirmed the hypothesis of the study and reflected completely the feasibility of using this DSS to make predictions of possible risks when control the vessel by analyzing the information model of the operator.Conclusions. Formal-analytical approaches presented in the study combined with the developed DSS software tools and the information itself made it possible to classify the decision-making strategies of the operator when control the vessel and to predict the probability of catastrophic consequences. The feasibility of the proposed models and methods was successfully revealed by carried out experiments.

Penerapan Sistem Pendukung Keputusan (DSS) dalam Manajemen Pemeliharaan Perkerasan

Pavement maintenance for the road network in Surabaya does not yet have a scientific basis such as monitoring and evaluation.This study illustrates the possibility of applying a Decision Support System (DSS) in pavement maintenance management to evaluate the asphalt pavement surface conditions. Common types of Asphalt Concrete pressures include (Asphalt hemorrhage, various pavement cracking modes, pot holes, longitudinal and transverse deformations) with various conditions of severity and intensity included in the system database, mathematical models for calculating severity and levels for each type of distress as well entered. This software was developed in the Microsoft Visual Basic environment using a logic programming process. The pavement condition rating (PCR) of the road section will be determined by the system. The system suggests necessary maintenance actions based on an estimated increase in pavement age and on the cost of alternative treatments. This system is examined in evaluating the asphalt pavement surface conditions of the freeway to Juanda International Airport. Traditional visual inspection and manual calculation procedures have also been carried out. The sidewalk surface is divided into sections, and the sidewalk condition is visually visible Evaluated and assessed using specially designed forms, ranking is in the range (26-93)% representing "very bad to very good" conditions for the road section based on the ranking index provided . Data is entered into the decision support system software developed. The results are very much in accordance with the results of software development. It was concluded that the Decision Support System developed, can help planners, or policy makers to support decision making in the maintenance of pavement.

SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN BAHAN BAKU PRODUKSI DENGAN METODE WEIGHTED PRODUCT PADA PT. LUHAI INDUSTRI

This study aims to be able to assist PT Luhai Industri Indonesia in processing data of new raw materials by making appropriate decisions with prices that are quite economical but with good enough quality, while the data processing techniques here use the decision support system method to determine adequate raw material production good and efficient. So not only is the information needed faster, the time needed to process the data will be faster. In the process of building a decision support system for the selection of raw materials for production using a system development method with a weighted product that uses a multiplication formula to link the rating of each attribute, where the rating must be raised first with the weight of the attribute concerned, in this study will use a method approach Waterfall in the development of the system from collecting data for user needs to the data to be processed into an attribute and weighting with the weighted product method in determining decisions on the final result of the software to be made, while the tools used in research to describe the flow of the system this is by using a structured method namely UML (Unfield Method Language) in describing the functional program model. This decision support system software will be built with Visual Studio 2010 programming language with a client server system so to adjust the system here will use MySQl as the database.