scholarly journals Kualitas Sistem Informasi Berdasarkan ISO/IEC 25010: Literature Review

2021 ◽  
Vol 20 (1) ◽  
pp. 15
Author(s):  
Made Dwi Mulyawan ◽  
I Nyoman Satya Kumara ◽  
Ida Bagus Alit Swamardika ◽  
Komang Oka Saputra
Keyword(s):  
Decision Support ◽  
Literature Review ◽  
Decision Support System ◽  
Product Quality ◽  
Support System ◽  
Mobile Application ◽  
Quality Model ◽  
Software Product ◽  
Quality In Use

Intisari— Sistem informasi saat ini telah menjadi bagian penting dalam meningkatkan efektifitas dan efisiensi suatu proses bisnis, sehingga diperlukan suatu pengukuran kualitas perangkat lunak untuk mengetahui sejauh mana sistem dapat menghasilkan informasi yang berkualitas. Dalam melakukan pengukuran kualitas ada beberapa model yang dapat digunakan sebagai panduan dalam melakukan penilaian perangkat lunak. ISO/IEC 25010 merupakan salah satu model kualitas yang dapat digunakan sebagai standar dalam melakukan pengukuran kualitas perangkat lunak. ISO/IEC 25010 terdiri dari software product quality model dan quality in use model. Artikel ini menelaah beberapa literature yang membahas mengenai pengukuran kualitas perangkat lunak yang menggunakan model ISO/IEC 25010. Saat ini ISO/IEC 25010 telah diterapkan untuk menilai kualitas pada sistem informasi akademik, sistem informasi pemerintah dan lembaga swasta, game, mobile application, dan decision support system. Hasil dari penilaian kualitas perangkat lunak dapat ditentukan melalui pengukuran terhadap aspek penting yang dipilih berdasarkan kebutuhan dari setiap perangkat lunak. Selain itu cara pengujian dan pengumpulan data yang digunakan dalam penilaian dapat berpengaruh terhadap tingkat akurasi dari pengukuran kualitas perangkat lunak.

Perceived Effectiveness of Artificial Intelligence based Decision Support System in a Clinical Setting: A Systematic Literature Review (Preprint)

2020 ◽  
Author(s):  
Avishek Choudhury
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Decision Support ◽  
Literature Review ◽  
Decision Support System ◽  
Support System ◽  
Clinical Setting ◽  
Clinical Decision Making ◽  
Theoretical Perspective ◽  
Care Providers

UNSTRUCTURED Objective: The potential benefits of artificial intelligence based decision support system (AI-DSS) from a theoretical perspective are well documented and perceived by researchers but there is a lack of evidence showing its influence on routine clinical practice and how its perceived by care providers. Since the effectiveness of AI systems depends on data quality, implementation, and interpretation. The purpose of this literature review is to analyze the effectiveness of AI-DSS in clinical setting and understand its influence on clinician’s decision making outcome. Materials and Methods: This review protocol follows the Preferred Reporting Items for Systematic Reviews and Meta- Analyses reporting guidelines. Literature will be identified using a multi-database search strategy developed in consultation with a librarian. The proposed screening process consists of a title and abstract scan, followed by a full-text review by two reviewers to determine the eligibility of articles. Studies outlining application of AI based decision support system in a clinical setting and its impact on clinician’s decision making, will be included. A tabular synthesis of the general study details will be provided, as well as a narrative synthesis of the extracted data, organised into themes. Studies solely reporting AI accuracy an but not implemented in a clinical setting to measure its influence on clinical decision making were excluded from further review. Results: We identified 8 eligible studies that implemented AI-DSS in a clinical setting to facilitate decisions concerning prostate cancer, post traumatic stress disorder, cardiac ailment, back pain, and others. Five (62.50%) out of 8 studies reported positive outcome of AI-DSS. Conclusion: The systematic review indicated that AI-enabled decision support systems, when implemented in a clinical setting and used by clinicians might not ensure enhanced decision making. However, there are very limited studies to confirm the claim that AI based decision support system can uplift clinicians decision making abilities.

Variables Influencing Machine Learning-Based Cardiac Decision Support System: A Systematic Literature Review

2019 ◽  
Vol 892 ◽  
pp. 274-283
Author(s):  
Mohammed Ashikur Rahman ◽  
Afidalina Tumian
Keyword(s):  
Machine Learning ◽  
Decision Support ◽  
Literature Review ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision ◽  
Machine Learning Techniques ◽  
Cardiac Care ◽  
Learning Techniques

Now a day, clinical decision support systems (CDSS) are widely used in the cardiac care due to the complexity of the cardiac disease. The objective of this systematic literature review (SLR) is to identify the most common variables and machine learning techniques used to build machine learning-based clinical decision support system for cardiac care. This SLR adopts the Preferred Reporting Item for Systematic Review and Meta-Analysis (PRISMA) format. Out of 530 papers, only 21 papers met the inclusion criteria. Amongst the 22 most common variables are age, gender, heart rate, respiration rate, systolic blood pressure and medical information variables. In addition, our results have shown that Simplified Acute Physiology Score (SAPS), Sequential Organ Failure Assessment (SOFA) and Acute Physiology and Chronic Health Evaluation (APACHE) are some of the most common assessment scales used in CDSS for cardiac care. Logistic regression and support vector machine are the most common machine learning techniques applied in CDSS to predict mortality and other cardiac diseases like sepsis, cardiac arrest, heart failure and septic shock. These variables and assessment tools can be used to build a machine learning-based CDSS.

scholarly journals Development of a model for choosing strategies for investing in information security

2021 ◽  
Vol 2 (3 (110)) ◽  
pp. 43-51
Author(s):  
Valeriy Lakhno ◽  
Volodimir Malyukov ◽  
Berik Akhmetov ◽  
Dmytro Kasatkin ◽  
Liubov Plyska
Keyword(s):  
Decision Support ◽  
Information Security ◽  
Decision Support System ◽  
Support System ◽  
New Class ◽  
Modular Software ◽  
Proposed Model ◽  
Software Product ◽  
Continue Research ◽  
Multidimensional Objects

This paper has proposed a model of the computational core for the decision support system (DSS) when investing in the projects of information security (IS) of the objects of informatization (OBI). Including those OBI that can be categorized as critically important. Unlike existing solutions, the proposed model deals with decision-making issues in the ongoing process of investing in the projects to ensure the OBI IS by a group of investors. The calculations were based on the bilinear differential quality games with several terminal surfaces. Finding a solution to these games is a big challenge. It is due to the fact that the Cauchy formula for bilinear systems with arbitrary strategies of players, including immeasurable functions, cannot be applied in such games. This gives grounds to continue research on finding solutions in the event of a conflict of multidimensional objects. The result was an analytical solution based on a new class of bilinear differential games. The solution describes the interaction of objects investing in OBI IS in multidimensional spaces. The modular software product "Cybersecurity Invest decision support system " (Ukraine) for the Windows platform is described. Applied aspects of visualization of the results of calculations obtained with the help of DSS have been also considered. The Plotly library for the Python algorithmic language was used to visualize the results. It has been shown that the model reported in this work can be transferred to other tasks related to the development of DSS in the process of investing in high-risk projects, such as information technology, cybersecurity, banking, etc.

scholarly journals AQUACISION: a multiparameter aquaculture water quality ester and decision support system

2021 ◽  
Vol 24 (1) ◽  
pp. 530
Author(s):  
Mark Anthony A. Lazo ◽  
Louise Mark Kit S. Geronimo ◽  
Lester John T. Comilang ◽  
Kenneth John B. Cayme ◽  
Jay M. Ventura ◽  
...  
Keyword(s):  
Water Quality ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Quality Model ◽  
Ph Level ◽  
Total Dissolved Solid ◽  
Aquaculture Water

The paper presents a multiparameter aquaculture water quality tester with a decision support system. A device was developed to aid aquaculture farmers in monitoring water quality parameters and maintaining or achieving optimal levels by suggesting ways on how a farmer can respond to such measurements. The AQUACISION device measures six different water quality parameters; temperature, practical salinity, pH level, total dissolved solid (TDS), oxidation-reduction potential (ORP), and algae density. Measurements were sent to the AQUACISION application where they were processed to determine the course of action that was best to maintain or achieve optimal levels using fuzzy rules. Based on the comparative result, the AQUACISION was accurate in measuring temperature, practical salinity, pH level, TDS, and ORP during the actual testing. The application also received an excellent rating on the ISO/IEC 25010 software quality model standard

A DSS User is a Happy Negotiator

2016 ◽  
pp. 590-611
Author(s):  
Patrick Hippmann
Keyword(s):  
Decision Support ◽  
Literature Review ◽  
Decision Support System ◽  
Decision Support Systems ◽  
Support System ◽  
Support Systems ◽  
Research Framework ◽  
Analysis And Design ◽  
The Impact ◽  
Research And Design

The present work states that the analysis and design of decision support systems should consider their impacts on the emotional behaviors of negotiators. This paper provides a brief literature review with respect to this issue, and an outline of a research framework, which explains how to assess and analyze the dynamics of emotional behaviors in text-based negotiations. Subsequently, it provides some results, which show that a decision support system does not mitigate but intensifies emotional behaviors, toward the end of successful as well as failed text-based online negotiations. It is concluded that the research and design of decision support systems should focus more on the impact such systems have on the emotional behaviors of the supported negotiators.

An Environment for Guidelinebased Decision Support Systems for Outpatients Monitoring

2017 ◽  
Vol 56 (04) ◽  
pp. 283-293 ◽  
Author(s):  
Giordano Lanzola ◽  
Paolo Bossi ◽  
Silvana Quaglini ◽  
Elisa M. Zini
Keyword(s):  
Decision Support ◽  
Side Effects ◽  
Decision Support System ◽  
Mobile Devices ◽  
Support System ◽  
Mobile Application ◽  
Web Application ◽  
Mobile Technologies ◽  
Specific Patient ◽  
Patient Reported

SummaryObjectives: We propose an architecture for monitoring outpatients that relies on mobile technologies for acquiring data. The goal is to better control the onset of possible side effects between the scheduled visits at the clinic.Methods: We analyze the architectural components required to ensure a high level of abstraction from data. Clinical practice guidelines were formalized with Alium, an authoring tool based on the PROforma language, using SNOMED-CT as a terminology standard. The Alium engine is accessible through a set of APIs that may be leveraged for implementing an application based on standard web technologies to be used by doctors at the clinic. Data sent by patients using mobile devices need to be complemented with those already available in the Electronic Health Record to generate personalized recommendations. Thus a middleware pursuing data abstraction is required. To comply with current standards, we adopted the HL7 Virtual Medical Record for Clinical Decision Support Logical Model, Release 2.Results: The developed architecture for monitoring outpatients includes: (1) a guideline-based Decision Support System accessible through a web application that helps the doctors with prevention, diagnosis and treatment of therapy side effects; (2) an application for mobile devices, which allows patients to regularly send data to the clinic. In order to tailor the monitoring procedures to the specific patient, the Decision Support System also helps physicians with the configuration of the mobile application, suggesting the data to be collected and the associated collection frequency that may change over time, according to the individual patient’s conditions. A proof of concept has been developed with a system for monitoring the side effects of chemo-radiotherapy in head and neck cancer patients.Conclusions: Our environment introduces two main innovation elements with respect to similar works available in the literature. First, in order to meet the specific patients’ needs, in our work the Decision Support System also helps the physicians in properly configuring the mobile application. Then the Decision Support System is also continuously fed by patient-reported outcomes.

scholarly journals DEVELOPING THE ALGORITHM OF AN AUTOMATED EXPERT SELECTION SYSTEM FOR CONDUCTING CORRECTION MEASURES TO IMPROVE THE DRILLING JIG PERFORMANCE

2021 ◽  
Vol 2021 (1) ◽  
pp. 52-60
Author(s):  
Aleksandr Feofanov ◽  
Anna Busheva
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Product Quality ◽  
Support System ◽  
Automated System ◽  
Selection System ◽  
Russian Science ◽  
Corrective Measures ◽  
Expert Selection ◽  
Fmea Analysis

This article presents the main problems that arise during the drilling jig operation. The paper considers the main nodes of the jig and their purpose. An FMEA-analysis is carried out, on the basis of which the main risks for the consumer arising during the operation are identified, and corrective measures are proposed to improve the product quality. The main methods used for choosing the experts are analyzed, and an automated system for selecting the experts in the Russian Science Foundation is considered. The article presents the scheme of the developed decision support system and the algorithm of the automated system for selecting the experts to carry out corrective measures including various methods.

scholarly journals QUALITY MEASUREMENT OF TRANSPORTATION SERVICE APPLICATION GO-JEK USING ISO 25010 QUALITY MODEL

2019 ◽  
Vol 10 (1) ◽  
pp. 233-242
Author(s):  
Millati Izzatillah
Keyword(s):  
Product Quality ◽  
Mobile Application ◽  
Quality Measurement ◽  
Quality Model ◽  
Model Quality ◽  
Quality Dimension ◽  
Transportation Service ◽  
Service Application ◽  
Quality In Use

GO-JEK is the most widely used transportation service application by Indonesian society that its users reached 21.6% of the total users of transportation service application. GO-JEK application has 12 services include many functions that must running well. The services can be ordered by multiple users in the same time. Based on that condition, quality of GO-JEK application need to be measured that all functions running well or not. So, the result will be better application performance using mobile application quality measurement standards ISO 25010 Quality Model. Testing result of all subcharacteristics in ISO 25010 Quality Model, quality of GO-JEK application in Product Quality dimension is 79.30% on Android device and 80.88% on iOS device from maximum product quality value of mobile application is 91.37%. While in Quality in Use dimension is 76.22% from maximum quality in use value of mobile application is 94.75%. These things show GO-JEK application have a good quality in product quality dimension and in quality in use dimension or the user’s perspective.

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