Patient facing decision support system for interpretation of laboratory test results

Tourism is one of the important economic sectors in Indonesia that needs to be developed. This is based on data of the number of tourist visits from “Kementrian Pariwisata Republik Indonesia” website that the number of tourists in Indonesia is very much and continues to increase over time. Due to the increasing number of tourist visits from various places, makes many entrepreneurs are competing to establish a hotel as a place of business with variety of price, class, facility and service. Then, the growth of the hotels became very rapid. With so many choices of the hotels, of course it will cause a problems for tourists to decide which hotel is suitable with the desired criteria. With the development of information technology in this era of globalization, technology should be utilized to solve this problem as a decision support system that can recommend which hotel is the most suitable from the tourist desires. The hotel data to be used in this research comes from hotel search site. The methods used for this decision support system are SAW and TOPSIS methods. The reason for using this methods is because SAW has the ability to assess more accurately because it is based on criteria and the computation of TOPSIS method is efficient and fast. The criteria used on choosing the hotel are price, facilities and class. The results of this research has been generated as a web-based application for hotel recommendation. Based on the test results of this hotel recommendation system application, this application works as expected.

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Key Technologies for Development of Track Utilization Decision Support System in Railway Passenger Stations

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.655-657.2375 ◽

2013 ◽

Vol 655-657 ◽

pp. 2375-2380

Author(s):

Ying Gui Zhang ◽

Ding You Lei

Keyword(s):

Decision Support ◽

Decision Support System ◽

Support System ◽

Test Results ◽

Dynamic Adjustment ◽

Time Dynamic ◽

Object Based ◽

Key Technologies ◽

Trial Test ◽

Railway Passenger

Development of track utilization decision support system (TUDSS) is one of the most important component parts for realizing decentralized and self-regulated control in railway passenger stations. The system can provide technical and decision supports for dispatchers to solving track utilization problems (TUP), and its development thus needs many key technologies. Furthermore, we analyze and further put forward real-time dynamic adjustment technology, object-based graphical block technology, cross time span consistency processing technology, carrying capacity of station throat calculating principle and also other key technologies to help to develop the system and realize its functions. Moreover, its trial test results show that the system can make and adjust track utilization plans effectively and fast, and meet the diversified practical needs for TUP in passenger stations.

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SISTEM PENDUKUNG KEPUTUSAN PENENTUAN JENIS TANAMAN PANGAN BERDASARKAN KANDUNGAN TANAH MENGGUNAKAN METODE ANALYTICAL HIERARCHY PROCESS (AHP) DENGAN ALGORITMA GENETIKA

Compiler ◽

10.28989/compiler.v4i2.96 ◽

2015 ◽

Vol 4 (2) ◽

Author(s):

Yuliani Indrianingsih ◽

Winda Susyanti Naibaho

Keyword(s):

Genetic Algorithm ◽

Decision Making ◽

Decision Support ◽

Decision Support System ◽

Support System ◽

Analytical Hierarchy Process ◽

Test Results ◽

Consistency Ratio ◽

Hierarchy Process

Samosir regency is a from North Sumatera province which dominantly people is live on agriculture. The most of the farmers using autodidact learning to determining the types of plants that will be process the appropriate with their land, where farmers just learn from their experiences and exchange opinion with another farmers. Based of the problem, the system will be built by Analytical Hierarchy Process (AHP) with Genetic Algorithm. The result of the testing from method Analytical Hierarchy Process (AHP) obtained result with consistency ratio values < 0,1, which is -0,5936 while the result of the testing from Genetic Algorithm obtained value of the fitness is 157,25. Based on the test results, it can be concluded that the method Analytical Hierarchy Process (AHP) obtained the result more consistent with the value of consistency ratio should be < 0,1, so it will be easier to making decision, while on the analysis of Genetic Algorithm, obtained result are probabilistic as always having random process, so that decision making can not be consistent. So, Decision Support System to determination of plants based by contents of soil which are good and suitable is method Analytical Hierarchy Process (AHP).

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Sistem Pendukung Keputusan Pemilihan Atlet Panahan Menggunakan Metode Analitycal Hierarchy Process Berbasis Web

JURNAL PILAR TEKNOLOGI Jurnal Ilmiah Ilmu Ilmu Teknik ◽

10.33319/piltek.v3i2.12 ◽

2019 ◽

Vol 3 (2) ◽

Author(s):

Eka Bayu Bimantara ◽

Arief Budiman ◽

Pradityo Utomo

Keyword(s):

Decision Support ◽

Decision Support System ◽

Support System ◽

Black Box ◽

Test Results ◽

Priority Vector ◽

Selection Decision ◽

Hierarchy Process ◽

Selection Of ◽

Process Method

Decision Support System is a system was used to help getting making decisions on a problem, such as selecting students in the archery sports that will be face to a championship event such as SEA GAMES (South East Games). In Decision Support System there are many methods that can be used, one of them is Analitycal Hierarchy Process method. Analitycal Hierarchy Process method is one of the more efficient decision-making methods because the data is very detailed, all the criteria and alternatives will be compared one by one. The calculation used to solve a problem uses multiplication to relate the preference value, where the value for each criteria and alternative must be searched for eigen / priority vector first, after it is proved consistency using RI table (ratio index), if the result of verification is less than 10% (0.1) then it is consistent and the calculation can be continued, but if the verification result is more than 10% (0.1) then the calculation is considered inconsistent and needs to be repeated from the beginning. This support system uses a web base, where the data entered will be saved into the MySQL database. The test results of the Student Selection Selection Decision Support System Using Analitycal Hierarchy Process Method Based Web get results as expected on the Black Box. So it can be concluded an accurate percentage of system success of 100%.Keywords : Decision Support System, Black Box, Analitycal Hierarchy Process, The Selection Of Athlete.

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TOPSIS Method Application in Choosing The Most-Sale POS Cashier Machine Stuffs and Tools in PT. Mahadana Wikasita

SinkrOn ◽

10.33395/sinkron.v6i1.10898 ◽

2021 ◽

Vol 6 (1) ◽

pp. 1-12

Author(s):

Rani Irma Handayani ◽

Normah Normah ◽

Deni Wironoto

Keyword(s):

Decision Support ◽

Decision Support System ◽

Support System ◽

Ideal Solution ◽

Test Results ◽

Topsis Method ◽

A Value ◽

Order Preference ◽

One Year ◽

A Company

PT. Mahadana Wikasita is a company engaged in the sale of machine goods and pos cashier tools. In order to face business competition there are some problems that often arise regarding the sale of goods. PT. Mahadana Wikasita is lacking in monitoring the goods sold, what items consumers need and the storage of data is less effective, so the company can not determine exactly which goods to buy. Therefore, a decision support system is needed that can help solve this problem. In this research, the decision support system used is by Techinique for Order Reference by Similarity to Ideal Solution (TOPSIS) which consists of seven stages using several criteria such as price, type, quality and customer interest. In the test results calculated using the Method For Order Preference bySimiliarity to Ideal Solution (TOPSIS) it can be concluded that the highest value is kios Pakmo mobile cashier application package with a value of 0.920, can be interpreted as the best selling item for one year.

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Impact of interactions between drugs and laboratory test results on diagnostic test interpretation – a systematic review

Clinical Chemistry and Laboratory Medicine (CCLM) ◽

10.1515/cclm-2018-0900 ◽

2018 ◽

Vol 56 (12) ◽

pp. 2004-2009 ◽

Cited By ~ 3

Author(s):

Jasmijn A. van Balveren ◽

Wilhelmine P.H.G. Verboeket-van de Venne ◽

Lale Erdem-Eraslan ◽

Albert J. de Graaf ◽

Annemarieke E. Loot ◽

...

Keyword(s):

Decision Support ◽

Laboratory Test ◽

Health Care Professionals ◽

Test Interpretation ◽

Test Results ◽

Correct Interpretation ◽

Laboratory Staff ◽

Laboratory Test Results ◽

Incorrect Diagnosis ◽

Clinical Rules

Abstract Intake of drugs may influence the interpretation of laboratory test results. Knowledge and correct interpretation of possible drug-laboratory test interactions (DLTIs) is important for physicians, pharmacists and laboratory specialists. Laboratory results may be affected by analytical or physiological effects of medication. Failure to take into account the possible unintended influence of drug use on a laboratory test result may lead to incorrect diagnosis, incorrect treatment and unnecessary follow-up. The aim of this review is to give an overview of the literature investigating the clinical impact and use of DLTI decision support systems on laboratory test interpretation. Particular interactions were reported in a large number of articles, but they were fragmentarily described and some papers even reported contradictory findings. To provide an overview of information that clinicians and laboratory staff need to interpret test results, DLTI databases have been made by several groups. In a literature search, only four relevant studies have been found on DLTI decision support applications for laboratory test interpretation in clinical practice. These studies show a potential benefit of automated DLTI messages to physicians for the correct interpretation of laboratory test results. Physicians reported 30–100% usefulness of DLTI messages. In one study 74% of physicians sometimes even refrained from further additional examination. The benefit of decision support increases when a refined set of clinical rules is determined in cooperation with health care professionals. The prevalence of DLTIs is high in a broad range of combinations of laboratory tests and drugs and these frequently remain unrecognized.

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Penerapan Metode Fuzzy Tsukamoto untuk Pemilihan Karyawan Terbaik Berbasis Java Desktop

Digital Zone Jurnal Teknologi Informasi dan Komunikasi ◽

10.31849/digitalzone.v11i1.3944 ◽

2020 ◽

Vol 11 (1) ◽

pp. 130-149

Author(s):

Fandra Satria ◽

Alexander J.P. Sibarani

Keyword(s):

Decision Support ◽

Problem Solving ◽

Decision Support System ◽

Support System ◽

Employee Performance ◽

Visual Observation ◽

Test Results ◽

The Status ◽

Trading Activities ◽

Selection Of

Penelitian ini dilakukan di PT. Patra Trading, yang memiliki bisnis utama pada aktivitas niaga produk-produk non BBM. Perusahaan memandang bahwa kinerja pegawai perlu ditingkatkan melalui pemberian penghargaan secara periodik terhadap karyawan yang memiliki kinerja terbaik. Pemilihan karyawan berkinerja terbaik selama ini dilakukan dengan menerapkan tiga kriteria yaitu: Absensi, kepribadian, dan problem solving. Penilaian dilakukan dengan mengambil data dari mesin absensi dan pengamatan secara visual. Untuk kriteria kepribadian dan problem solving sering diabaikan karena nilai yang bersifat subjektif. Seluruh perhitungan dilakukan secara manual. Sistem pendukung keputusan perlu diterapkan untuk dapat mengatasi hal tersebut. Metode fuzzy tsukamoto merupakan metode yang digunakan untuk membantu dalam pemberian rekomendasi secara cepat, tepat, dan akurat. Maka dikembangkan sebuah aplikasi yang dapat memberi rekomendasi terhadap penentuan karyawan berkinerja terbaik berdasarkan kriteria yang sudah ditentukan. Dari hasil pengujian, seluruh fungsi berjalan dengan baik dan diperoleh hasil karyawan yang memperoleh nilai tertinggi dengan status “TERBAIK” memperoleh nilai probabilitas 90,85586. Kata kunci: Fuzzy, Karyawan, Tsukamoto, Sistem Pendukung Keputusan Abstract This research was conducted at PT. Patra Trading, which has a main business in trading activities of non-fuel products. The company considers that employee performance needs to be improved through periodic rewards of employees who have the best performance. The selection of the best performing employees so far has been done by applying three criteria, namely: Attendance, personality, and problem solving. Assessment is done by taking data from the attendance machine and visual observation. For personality criteria and problem solving are often ignored because the values are subjective. All calculations are done manually. Decision support systems need to be implemented to overcome this. Tsukamoto fuzzy method is a method used to assist in providing recommendations quickly, precisely, and accurately. Then an application was developed that could provide recommendations for determining the best performing employees based on predetermined criteria. From the test results, all functions run well and the results obtained by employees who received the highest value with the status of "BEST" obtained a probability value of 90.8586. Keywords: Fuzzy, Employee, Tsukamoto, Decision Support System

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Implementasi fuzzy weighted product penyusunan aksi rehabilitasi rekonstruksi pasca bencana berbasis decision support system dynamic

JURNAL ELTEK ◽

10.33795/eltek.v18i1.171 ◽

2020 ◽

Vol 18 (1) ◽

pp. 1

Author(s):

Agung Teguh Almais ◽

Fatchurrohman Fatchurrohman ◽

Khadijah Fahmi Hayati Holle

Keyword(s):

Decision Support ◽

Decision Support System ◽

Natural Disasters ◽

Test Data ◽

Support System ◽

System Dynamic ◽

Test Results ◽

The Government

Penyusunan aksi rehabilitasi rekonstruksi pasca bencana alam dilakukan untuk mengetahui jenis kerusakan dan besarnya kerugian pasca bencana alam yang harus ditanggung pemerintah. Agar jenis kerusakan dan besarnya kerugian pasca bencana alam sesuai data yang dilapangan maka dilakukan penelitian yang mengimplementasikan Decision Support System Dynamic (DSSD) dengan metode Fuzzy-Weighted Product (F-WP). Hasil dari pengujian menghasilkan tiga jenis data yang berbeda yaitu data uji yang sama dengan data pola, data uji yang tidak sama dengan data pola, dan data uji yang tidak bisa diterpakan untuk pengujian. Masing-masing jenis data uji tersebut memilik prosentase yaitu 73% data uji yang sama dengan data pola, 22% data uji yang tidak sama dengan data pola, dan 5% merupakan data yang tidak dapat digunakan sebagai data uji. Dari hasil pengujian tersebut dapat disimpulkan bahwa metode Fuzzy-Weighted Product (F-WP) dapat diterapkan pada Decision Support System Dynamic (DSSD) untuk membantu surveyor dalam melakukan penyusunan aksi rehabilitasi rekonstruksi pasca bencana alam. Preparation of rehabilitation reconstruction actions after natural disasters is carried out to determine the types of damage and the number of losses after natural disasters that must be borne by the government. So that the type of damage and the magnitude of losses after natural disasters match the data in the field, a study is carried out that implements a Decision Support System Dynamic (DSSD) with the Fuzzy-Weighted Product (F-WP) method. The results of tests produce three types of data that are different, namely the same test data with pattern data, test data that are not the same as pattern data, and test data that cannot be applied for testing. Each type of test data has a percentage that is 73% of the same test data like the pattern data, 22% of the test data are not the same as the pattern data, and 5% are data that cannot be used as test data. From the test results it can be concluded that the Fuzzy-Weighted Product (F-WP) method can be applied to the Decision Support System Dynamic (DSSD) to assist surveyors in carrying out the rehabilitation reconstruction actions after natural disasters.

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Diagnostic error as a result of drug-laboratory test interactions

Diagnosis ◽

10.1515/dx-2018-0098 ◽

2019 ◽

Vol 6 (1) ◽

pp. 69-71

Author(s):

Jasmijn A. van Balveren ◽

Wilhelmine P.H.G. Verboeket-van de Venne ◽

Lale Erdem-Eraslan ◽

Albert J. de Graaf ◽

Annemarieke E. Loot ◽

...

Keyword(s):

Decision Support ◽

Laboratory Test ◽

Diagnostic Errors ◽

Drug Effects ◽

Diagnostic Error ◽

Test Results ◽

Laboratory Test Results ◽

Number Of Patients ◽

Erroneous Diagnosis ◽

Improve Patient

Abstract Background Knowledge of possible drug-laboratory test interactions (DLTIs) is important for the interpretation of laboratory test results. Test results may be affected by physiological or analytical drug effects. Failure to recognize these interactions may lead to misinterpretation of test results, a delayed or erroneous diagnosis or unnecessary extra tests or therapy, which may harm patients. Content Thousands of interactions have been reported in the literature, but are often fragmentarily described and some papers even reported contradictory findings. How can healthcare professionals become aware of all these possible interactions in their individual patients? DLTI decision support applications could be a good solution. In a literature search, only four relevant studies have been found on DLTI decision support applications in clinical practice. These studies show a potential benefit of automated DLTI messages to physicians for the interpretation of laboratory test results. All physicians reported that part of the DLTI messages were useful. In one study, 74% of physicians even sometimes refrained from further additional examination. Summary and outlook Unrecognized DLTIs potentially cause diagnostic errors in a large number of patients. Therefore, efforts to avoid these errors, for example with a DLTI decision support application, could tremendously improve patient outcome.

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