scholarly journals Implementation of Preference Selection Index Method in Decision Support System for Selecting School Inventory Users

2020 ◽  
Vol 2 (2) ◽  
pp. 333-339
Author(s):  
Doris Yolanda Saragih ◽  
Kalvin Sinaga
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Selection Index ◽  
Instructional Media ◽  
Index Method ◽  
The Third ◽  
Service Behavior ◽  
Final Score ◽  
Psi Method

This study aims to solve the problem of using a limited inventory of supporting media for learning at SD 096782 Tumorang Huta Dua Tumorang school, Gunung Maligas District, Simalungun Regency. The limitations of school inventories in the use of instructional media must be distributed to teachers so that they can be used in teaching. Therefore, the difficulty of distributing school inventory was overcome by implementing a decision support system using the Preference Selection Index (PSI) method. This method uses 6 criteria consisting of: years of service, behavior, performance, attendance, responsibility, and last education. The results of the application of the DSS with the PSI method obtained alternatives that are priority recommendations for school inventory users. The recommendation results obtained from the application of the DSS with the PSI method are Teacher_3 alternative with a final value of 0.8506. The second alternative is Teacher_01 with a final score of 0.8190 and the third alternative is Teacher_07 with a final score of 0.7846.

SISTEM PENDUKUNG KEPUTUSAN PENENTUAN PRIORITAS PEMBANGUNAN DAERAH MENERAPKAN METODE PREFERENCE SELECTION INDEX (PSI)

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Martina Klarasia Siahaan ◽  
Mesran Mesran ◽  
Sumiaty Adelina Hutabarat ◽  
Joli Afriany
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Data Collection ◽  
Decision Support System ◽  
Support System ◽  
System Development ◽  
Selection Index ◽  
Fund Allocation ◽  
Collection Data ◽  
Psi Method

This study aims to determine development priorities in 2018 Kota Medan District covering planning, use and evaluation of village development. This study uses qualitative research, with a case study strategy. The technique of collecting data is done by interviews, observation and documentation. Test the validity of data by triangulating data sources and data collection techniques. Data analysis uses determination techniques through data collection, data reduction, data presentation and conclusion. Evaluations for the Village Fund for 2017 include constraints faced during the implementation of development and allocation of village funds such as a lack of sense of responsibility between village officials in managing village funds, people who care about development are still few, and there is a lack of meetings to deliver information on village fund allocation to the community. The decision support system for determining village development priorities has stages, starting from selecting criteria, aspects to assessments that have been set, decision making difficulties in determining priorities and calculating weights. Related to this, the Preference Selection Index (PSI) method can be used to solve the problem. The results of the process are in the form of village rankings as a recommendation for decision making to choose as suitable occupies the designated fields. The results of the system supplementation, it was concluded that the use of this method can help the process of making prioritization of development, can be studied, quite easy to use, and produce information used.Keywords: Decision Support System, Development Priority, PSI

scholarly journals Implementation of Simple Multi Attribute Rating Technique Method using Decision Support System Concept (Case Recommendation of Salon Place in Pematangsiantar City)

2019 ◽  
Vol 3 (1) ◽  
pp. 25
Author(s):  
Indra Riyana Rahadjeng ◽  
Agus Perdana Windarto
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Assessment Criteria ◽  
Purchase Decision ◽  
Final Value ◽  
The Third ◽  
Final Score ◽  
The Ideal

The purpose of the research is to determine the ideal salon place considering the salon is a place visited by women to beautify themselves. This research can also be used as recommendations in the form of information in deciding whether consumers visit the salon or not based on research results. The method used in decision making is the SMART (Simple Multi Attribute Rating Technique) method. To determine the evaluation of the salon, researchers used 5 assessment criteria, among others: service (C1), facilities (C2), products (C3), price (C4) and Purchase Decision (C5). For alternatives used as a salon, among others: salon Sukim (A1), Necis (A2), Endah (A3), Crown (A4) and Chan Dhai (A5). The results obtained by Sukim (A1) with a final value of 0.8835 as the first rank, Endah Salon (A2) with a final score of 0.5530 as the second rank and Chan Dai (A5) with a final value of 0.45 as the third rank.

SISTEM PENDUKUNG KEPUTUSAN UNTUK MENENTUKAN DAGING KAMBING BERKUALITAS BAIK DENGAN METODE FUZZY SUGENO BERBASIS ANDROID

2018 ◽  
Vol 10 (1) ◽  
pp. 1005
Author(s):  
Achmad Dika Asrori ◽  
Retno Wardhani ◽  
Masruroh Masruroh
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Design Stage ◽  
The Third

The decision support system used to determine good quality meat using Fuzzy Sugeno Method is made using Eclipse Application with some stages, those are: making the project then create the layout file and Java, after that design stage and coding are done once the project is ready to run. The results of the calculation on the Fuzzy Sugeno Method test show that there are five variables. First, the color of meat has three sets. It is categorized as bad 1 if it is in the range of 1-3,  good in the range of 4-6, and bad 2 in the range of 7-8. The second variable is related to the fat color. It has two sets, those are bad if it is in the range of 4-9 and good in the range 1-3. The third variable is marbling which has two sets, those are bad if it is in the range of 1-9 and good in the range of 10-12. The fourth variable has three sets, those are bad 1 if it is in the range of 0-4, good in the range of 5,3-5,8, and bad 2 in the range of 5,8-8 . The third category of marbling has two sets, those are bad if it is in the range of 8 and good in the range of 8.

SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN GURU BERPRESTASI KOTA MEDAN MENERAPKAN METODE PREFERENCES SELECTION INDEX (STUDI KASUS : DINAS PENDIDIKAN KOTA MEDAN)

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Fajar Syahputra ◽  
Mesran Mesran ◽  
Ikhwan Lubis ◽  
Agus Perdana Windarto
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Formal Education ◽  
Basic Education ◽  
Selection Index ◽  
Main Task ◽  
Selection Of

The teacher is a major milestone in the world of education, the ability and achievement of students cannot be separated from the role of a teacher in teaching and guiding students. Based on the Law of the Republic of Indonesia No. 14 of 2005 concerning Teachers and Lecturers, in Article 1 explained that teachers are professional educators with the main task of educating, teaching, guiding, directing, training, evaluating, and evaluating students in early childhood education through formal education, basic education and education medium. Whereas in Article 4 of the Act, it is explained that the position of teachers as professionals serves to enhance the dignity and role of teachers as learning agents to function to improve the quality of national education.Decision making is an election process, among various alternatives that aim to meet one or several targets. The decision-making system has 4 phases, namely intelligence, design, choice and implementation. These phases are the basis for decision making, which ends with a recommendation.The Preferences Selection Index (PSI) method is a rarely used decision support system method. This method is a method developed by stevanie and Bhatt (2010) to solve the Multi Criteria Decision Making (MCDM). With the right consideration, this method can be one of the tools to determine policies in decision-making systems, especially the selection of outstanding teachers. Determination of policies taken as a basis for decision making, must use criteria that can be defined clearly and objectively.Keywords: Decision Support System, PSI, Selection of Achieving Teachers

scholarly journals Decision support system analysis for selecting a baby cream product with Preference Selection Index (PSI) Baby Sensitive Skin Under 3 Year

2021 ◽  
Vol 1933 (1) ◽  
pp. 012035
Author(s):  
Muhammad Amin ◽  
Novica Irawati ◽  
Hommy Dorthy Ellyany Sinaga ◽  
Dwi Retnosari ◽  
Jauhari Maulani ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
System Analysis ◽  
Selection Index ◽  
Sensitive Skin

scholarly journals Decision Support System on Selection of Lecturer Research Grant Proposals using Preferences Selection Index

2019 ◽  
Vol 1255 ◽  
pp. 012006 ◽  
Author(s):  
Siti Sundari ◽  
Karmila ◽  
Masduki Nizam Fadli ◽  
Dedy Hartama ◽  
Agus Perdana Windarto ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Selection Index ◽  
Grant Proposals ◽  
Selection Of ◽  
Research Grant

scholarly journals INTELCITY AND MULTIPLE CRITERIA WEB-BASED NEGOTIATION DECISION SUPPORT SYSTEM FOR REAL ESTATE

2005 ◽  
Vol 11 (3) ◽  
pp. 183-189 ◽  
Author(s):  
Artūras Kaklauskas ◽  
Vita Urbanavičienė
Keyword(s):  
Decision Support ◽  
Real Estate ◽  
Decision Support System ◽  
Citizen Participation ◽  
Support System ◽  
Development Project ◽  
Multiple Criteria ◽  
Third Party ◽  
Web Based ◽  
The Third

The authors of this paper together with the other VGTU scientists participate in the international project INTELCITIES and present Multiple Criteria Web‐Based Negotiation Decision Support System for Real Estate (NDSSRE). INTELCITIES project is a research and development project that aims to pool advanced knowledge and experience of e‐government, planing systems and citizen participation. NDSS‐RE includes a decision support tool based on the methods of alternative generation and multiple criteria analysis that enable negotiating parties to evaluate their systems of preferences and recognize opportunities for trade‐off between differently valued objectives and joint gains. At present the developed NDSS‐RE allows for the performance of the following functions: search for real estate alternatives; finding out alternatives and making an initial negotiation table; multiple criteria analyses of alternatives; negotiation based on real calculations; determination of the most rational real estate purchase variant on the ground of characteristics describing effectiveness of the analysed alternatives. The third part of the paper deals with traditional negotiation principles and describes negotiation tactics, such as “The Atractive Alternative”, “The Stall and Jolt”, “The Comparative Value”, “The Third Party”, “The No More Money” and “The Walk Away” tactics. More traditional negotiation principles and tactics have been planned to integrate in future concerning the described NDSS‐RE system because the knowledge and implementation of all the above mentioned tactics and principles lead to more successful negotiation for the lowest possible price buying real estate.

scholarly journals ANALISIS FAKTOR YANG MEMPENGARUHI IPK MAHASISWA TERHADAP PENENTUAN KUALITAS PROSES PEMBELAJARAN DENGAN METODE ELECTRE II

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Riski Yanti ◽  
Agus Perdana Windarto ◽  
Suhada Suhada
Keyword(s):  
Decision Support ◽  
Academic Success ◽  
Decision Support System ◽  
Support System ◽  
Teaching Material ◽  
The Third

This study aims at what factors influence the value of Student GPA in StikomTunas Bangsa Pematangsiantar. Data used is obtained by giving questionnaires to students of STIKOM Tunas Bangsa Pematangsiantar. With alternatives used, namely curriculim, intelligence, absenteeism, and value. While the criteria used are the names of respondents who answer a question. The method used in this study is Electre II. From the results of the ELECTRE II calculation, the third alternative A3 is obtained as the first rank, A2 as the second rank, A4 as the third rank, and A1 as the last alternative. It is hoped that this research can be used by the education as teaching material for the students' academic success and progress.Keywords: Students, GPA,  Decision Support System, ELECTRE II

scholarly journals Decision Support System for Selection of Candidates for PASKIBRAKA Using the TOPSIS Method

Tech-E ◽  
2020 ◽  
Vol 4 (1) ◽  
pp. 44
Author(s):  
Nungsiyati Nungsiyati ◽  
Sri Hartati ◽  
Deli Wahana Aprilianti
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Assessment Process ◽  
Topsis Method ◽  
Order Preference ◽  
Long Time ◽  
Final Score ◽  
Manual Calculation ◽  
Selection Of

Activities in the selection of candidates for PASKIBRAKA every year aim to find the best sons and daughters who will be assigned as heirloom flag raisers. Selection of candidates for PASKIBRAKA members is done manually, to determine the final score of each participant. The selection committee still uses paper and is separate from the assessment to one criterion with the other criteria. In the assessment process with a large number of participants it will take a long time. To simplify the assessment process, a decision support system is needed for the selection of PASKIBRAKA candidates, using the TOPSIS Method (Technique for Order Preference by Similarity to Ideal Solution). TOPSIS is one method that is easy to use to solve multi-criteria problems by taking into account the values ​​of existing criteria. Based on the results of the case example, the candidate PASKIBRAKA selection shows that the results of the experiment use the same system as the manual calculation. And the calculation of the TOPSIS Method will produce output in the form of ranking from PAKIBRAKA candidates  

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