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

JURNAL ELTEK ◽  
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.

scholarly journals DECISION SUPPORT SYSTEM FOR PROVISION OF NATURAL DISASTER VICTIM LOGISTIC ASSISTANCE WITH TOPSIS METHOD

2020 ◽  
Vol 2 (2) ◽  
pp. 55-60
Author(s):  
Enok Tuti Alawiah ◽  
Sefrika Sefrika
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Natural Disasters ◽  
Natural Disaster ◽  
Support System ◽  
Topsis Method ◽  
Public Facilities ◽  
The Government ◽  
Alternative Solutions

At the beginning of 2020 there was a natural disaster that caused many people to lose their homes, damage to public facilities and infrastructure, as well as the breakdown of transportation links connecting villagers, especially in 3 districts namely Sukajaya, Nanggung, and Cigudeg. As a result of the disaster, many villages are isolated and residents need a lot of logistical support to meet their needs. To overcome these problems, we need a system that can help the government and volunteers who are interested in the decision making the process so that the provision of assistance for victims of natural disasters can be right on target and in accordance with the urgency of basic needs and logistics needed. Decision support systems using the TOPSIS method are used to solve multi-criteria problems by offering various alternative solutions to solve problems. The results obtained a final preference value of 0.68 from C3 criteria in order to prioritize residents with closed transportation access to channel disaster relief funds for victims of natural disasters in Bogor Regency.

SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN GURU PRODUKTIF PESERTA PELATIHAN ASESOR KOMPETENSI LSP P1 SMK SWASTA DWIWARNA MEDAN MENGGUNAKAN METODE THE EXTENDED PROMETHEE II (EXPROM II)

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Dwika Assrani ◽  
Mesran Mesran ◽  
Ronda Deli Sianturi ◽  
Yuhandri Yuhandri ◽  
Akbar Iskandar
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Multicriteria Analysis ◽  
Professional Certification ◽  
Promethee Ii ◽  
Certification Exams ◽  
The Government ◽  
Alternative Ranking ◽  
The Right

Vocational schools that have been licensed from BNSP to LSP P1 (first party professional certification institute) are schools that have been able to carry out their own competency certification exams for their students and later a competency assessor who will test and declare the eligibility of the students, competency assessors are productive teachers who have participated in and been given training by the government, in that training the schools choose from the number of productive teachers from each department to become competency assessor trainees in accordance with predetermined criteria so a decision support system is needed so there is no gap in the selection of productive teacher assessor training participants, a vocational school that has become a P1 LSP must have a competency assessor and is a requirement to be a P1 LSP. one of the solutions to the problem is the right one by using the Decision Support System (SPK). Decision Support System (DSS) can help the school in making the decision to choose the productive teacher of the appropriate assessor training and improve the efficiency of the decision. The Extended Promethee II (EXPROM II) is a development of the Promethee II method based on the ideal and anti-ideal solution. Promethee II itself is a method of making decisions on the function of preferences with problems through an outranking approach (ranking) or is a multicriteria analysis, comparing one alternative to another and calculating the alternative gap in pairs so as to produce an output that is alternative ranking based on the highest value.Keywords: Competitive Assessor LSP P1, SPK, The Extended Promethee II

scholarly journals Decision Support System for Indonesian Government Fast E-Tendering Based on Vendor Classification

2016 ◽  
Vol 4 (1) ◽  
Author(s):  
Edi Wahyu Widodo ◽  
Tri Harsono ◽  
Ali Ridho Barakbah
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Good Governance ◽  
Current System ◽  
Electronic System ◽  
Electronic Procurement ◽  
Advantages And Disadvantages ◽  
The Government ◽  
Procurement System

In the last few years in the world of auctions, electronic auctions become a hot topic for discussion, especially in Indonesia. In Indonesia, the auction has been using online electronic system since 2007 with all its advantages and disadvantages. This system is one of a fairly successful program in a good governance. Until now, there are 620 government agencies in Indonesia have been using this electronic procurement systems[19]. The Government can perform a budget efficiency nearly 5% of the total budget by using today's electronic procurement system. The current system is good enough, but there are still some deficiencies found. Some of solutions to cover the deficiency offered in this paper. Starting from the classification of goods or services according to the UNSPSC, applying business classification with ISIC Indonesia in 2009, recording the activity of vendors for consideration decision, and implementing a decision support system using AHP to facilitate the auction committee to determine the winner. All of above matters are intended to improve the effectiveness and efficiency of the current system.

scholarly journals An Evolutionary-Based Sentiment Analysis Approach for Enhancing Government Decisions during COVID-19 Pandemic: The Case of Jordan

2021 ◽  
Vol 11 (19) ◽  
pp. 9080
Author(s):  
Ruba Obiedat ◽  
Osama Harfoushi ◽  
Raneem Qaddoura ◽  
Laila Al-Qaisi ◽  
Ala’ M. Al-Zoubi
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Sentiment Analysis ◽  
Support System ◽  
Support Vector ◽  
Whale Optimization ◽  
Vector Machines ◽  
Standard Classification ◽  
The Government ◽  
F Measure

The world has witnessed recently a global outbreak of coronavirus disease (COVID-19). This pandemic has affected many countries and has resulted in worldwide health concerns, thus governments are attempting to reduce its spread and impact on different aspects of life such as health, economics, education, and politics by making emergent decisions and policies (e.g., lockdown and social distancing). These new regulations influenced people’s daily life and cast significant burdens, concerns, and disparities on various population groups. Taking the wrong actions and enforcing bad decisions by some countries result in increasing the contagion rate and more catastrophic results. People start to post their opinions and feelings about their government’s decisions on different social media networks, and the data received through these platforms present a very useful source of information that affects how governments perceive and cope with the current the pandemic. Jordan was one of the top affected countries. In this paper, we proposed a decision support system based on the sentiment analysis mechanism by combining support vector machines with a whale optimization algorithm for automatically tuning the hyperparameters and performing feature weighting. The work is based on a hybrid evolutionary approach that aims to perform sentiment analysis combined with a decision support system to study people’s posts on Facebook to investigate their attitudes and feelings toward the government’s decisions during the pandemic. The government regulations were divided into two periods: the first and latter regulations. Studying public sentiments during these periods allows decision-makers in the government to sense people’s feelings, alert them in case of possible threats, and help in making proactive actions if needed to better handle the current pandemic situation. Five different versions were generated for each of the two collected datasets. The results demonstrate the superiority of the proposed Whale Optimization Algorithm & Support Vector Machines (WOA-SVM) against other metaheuristic algorithms and standard classification models as WOA-SVM has achieved 78.78% in terms of accuracy and 84.64% in term of f-measure, while other standard classification models such as NB, k-NN, J84, and SVM achieved an accuracy of 69.25%, 69.78%, 70.17%, and 69.29%, respectively, with 64.15%, 62.90%, 60.51%, and 59.09% F-measure. Moreover, when comparing our proposed WOA-SVM approach with other metaheuristic algorithms, which are GA-SVM, PSO-SVM, and MVO-SVM, WOA-SVM proved to outperform the other approaches with results of 78.78% in terms of accuracy and 84.64% in terms of F-measure. Further, we investigate and analyze the most relevant features and their effect to improve the decision support system of government decisions.

scholarly journals The Hotel Recommendation System Using SAW (Simple Additive Weighting) And TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) Method

bit-Tech ◽  
2019 ◽  
Vol 1 (3) ◽  
pp. 131-145
Author(s):  
Aditiya Hermawan ◽  
Evan
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Recommendation System ◽  
Solution Method ◽  
Test Results ◽  
Economic Sectors ◽  
Web Based ◽  
Search Site ◽  
Simple Additive Weighting

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.

scholarly journals Penerapan Algoritma Simple Additive Weighting untuk Membantu Dalam Menentukan Calon Penerima Bantuan Pangan Non Tunai

2020 ◽  
Vol 6 (1) ◽  
pp. 37
Author(s):  
Andri Andreas ◽  
Antonius Wiryadinata ◽  
Halim Agung
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Weighting Method ◽  
Technical Problems ◽  
The Government ◽  
Food Needs ◽  
Simple Additive Weighting ◽  
To Receive

Bantuan Pangan Non Tunai (BPNT) is a program organized by the government in overcoming poverty and food needs. The BPNT program aims to reduce the burden of expenditure and provide more balanced nutrition to Beneficiary Families (KPM). However, in the implementation of the BPNT program there were still technical problems, including the determination of potential BPNT recipients who were wrongly targeted. To facilitate Government in determining prospective BPNT recipients, the authors make a decision support system using the Simple Additive Weighting method where this system generates ranking to choose citizens who are entitled to receive BPNT through calculating the criteria of each alternative. It is expected that this application can provide recommendations for prospective BPNT recipients who are more targeted.

APLIKASI SISTEM PENDUKUNG KEPUTUSAN PENERIMA BANTUAN SOSIAL TUNAI (BST) DENGAN METODE FUZZY TSUKAMOTO

2020 ◽  
Vol 1 (2) ◽  
pp. 42-55
Author(s):  
Cut Lutfianda
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
System Application ◽  
Social Assistance ◽  
Assistance Program ◽  
The Republic ◽  
The Government ◽  
The Right ◽  
Social Affairs

The government has issued policies and programs to anticipate the handling of this pandemic, one of which is the Social Assistance Program provided through the leading sector of the Ministry of Social Affairs of the Republic of Indonesia in the form of social assistance programs provided to the poor and communities that have a socio-economic impact from the corona pandemic. One of the programs launched by the government through the Ministry of Social Affairs is the Cash Social Assistance Program or Cash Social Assistance. The research objective was to develop a decision support system application for cash social assistance recipients (BST) with the Tsukamoto fuzzy method which can be used as a tool to quickly determine BST recipients. The several stages of work consist of; data collection, analysis, design and application design, implementation, and testing and evaluation. Based on the results of research and testing of the decision support system to determine BST recipients using the Fuzzy Tsukamoto method that has been carried out by researchers, several conclusions can be drawn, namely: 1) Expert system application for finding BST recipients is an application based on rules for solving problems to determine BST recipients with a high degree of accuracy and is used as a reference for BST recipients for the government to determine the right target recipients to be selected, and 2) The results of the analysis generated from this system are the same as the results of calculations manually using the theory of the Fuzzy Tsukamoto method so that the accuracy of the results is appropriate with calculations obtained from the trial.

scholarly journals Implementasi Fuzzy ELECTRE Untuk Penilaian Kerusakan Akibat Bencana Alam

2017 ◽  
Vol 7 (2) ◽  
pp. 81
Author(s):  
Agusta Praba Ristadi Pinem
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Natural Disasters ◽  
Support System ◽  
Integrated System ◽  
System Combination ◽  
Decision Making System ◽  
Electre Method ◽  
Ranking Information

Indonesia is prone to geology natural disasters, such as the earthquake and tsunami. The research aims to develop decision support system that can be used for assessment of damage caused by natural disaster after disaster. The method used in this system is method of fuzzy   ELECTRE and ECLAC. Fuzzy ELECTRE method used to determine the priority of the affected area, while ECLAC method used to calculate the natural disasters damage. Fuzzy method used in the process of assessing the weight and classification process. Variables used in this research is the sector that were damaged. Integration of fuzzy and ELECTRE methods applied in the prioritization of areas affected by natural disasters. The result of this research is classification of disaster area with rank based on weighting. Output visualized decision-making system in the form of dashboards in the form of mapping the area affected by the disaster. The variable rate of interest was made as a decision maker in the form of mapping that indicates the priority areas most severely affected by natural disasters. The process of calculation, analysis and ranking built in one integrated system. Combination mapping and decision support system produce information to support decision making. Ranking information similar with priority in BNPB documents with 0.96 coefficient Rank Spearman correlation (ρ).

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

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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