SISTEM PENDUKUNG KEPUTUSAN PENERIMA BANTUAN KELUARGA HARAPAN KHUSUS LANSIA DENGAN MENERAPKAN VIKOR (STUDI KASUS: DESA PATUMBAK II)

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Swandi Dedi Arnold Pardede ◽  
Mesran Mesran ◽  
Melda Panjaitan ◽  
Fince Tinus Waruwu ◽  
Puji S Ramadhan
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Social Protection ◽  
Social Assistance ◽  
Processing System ◽  
Director General ◽  
Final Decision ◽  
System Components ◽  
The Government

The development of Indonesia's population at this time is very rapid so that Indonesia has many problems including poverty problems that occur in the midst of society. In dealing with these problems the government has a program with a form of social assistance known today as the Elderly Family Hope Program (PKH). In accordance with the Decree of the Director General of Social Protection and Security Number 26 / LJS / 12/2016 in terms of social assistance the Recipients are those that have been determined by the Director General of Social Family. As well as in the Distribution this assistance is distributed in four stages one Year. Decision Support System is a computer-based system consisting of several components, namely language system components, system components of knowledge, and problem processing system components that are interrelated with one another, in making decisions through the use of data. data and decision models in order to solve a problem. The VIKOR method where this method focuses on ranking and chooses from an alternative set and determines the solution to the problem of criteria that are constrained and can result in decision making as a final decision and the best ranking method is the lowest resultKeywords: Decision Support System, Vikor, Recipient of Family Hope Assistance 

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.

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 Social Assistance Decision Support System Using the Naive Bayes Method

2021 ◽  
Vol 1 (1) ◽  
pp. 85
Author(s):  
Moh. Syaiful Anam
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Naive Bayes ◽  
Confusion Matrix ◽  
Social Assistance ◽  
Naïve Bayes ◽  
Bayes Method ◽  
Naive Bayes Method

Covid-19 telah menjadi pandemi yang menyebar hampir ke seluruh penjuru dunia. Karena proses penularannya yang begitu cepat Dalam masa pandemi covid -19, pandemi ini menyebar ke seluruh sendi kehidupan dan salah satu yang paling menjadi perhatian adalah dibidang sosial ekonomi. Banyak terdapat bantuan Sosial (Bansos) yang disalurkan baik oleh pemerintah ataupun pihak swasta lain. Penelitian ini bertujuan untuk membuat sistem pendukung keputusan bantuan sosial menggunakan metode Naive Bayes, selanjutnya melakukan Analisa menggunakan tabel Confusion Matrix.  Dalam menyelesaikan masalah dengan menggunakan metode Naive Bayes dari hasil pembahasan yang dilakukan dapat ditarik kesimpulan Naive Bayes dan aturan yang dihasilkan memiliki tingkat akurasi tinggi (good) yaitu sebesar 73% dan Sementara nilai Precision sebesar 92% dan Recall sebesar 86%. Sehingga metode Naive Bayes dapat diterapkan dalam menentukan prediksi yang lebih banyak dan potensial aturan yang dihasilkan untuk membantu menentukan pemberian bantuan sosial.

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.

scholarly journals Group Decision Support System Using The Analytic Network Process and Borda Methods for Selecting

2019 ◽  
Vol 13 (4) ◽  
pp. 333
Author(s):  
Beta Yudha Mahindarta ◽  
Retantyo Wardoyo
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Decision Maker ◽  
Support System ◽  
Group Decision ◽  
Housing Development ◽  
Final Decision ◽  
Group Decision Support System ◽  
Individual Decision ◽  
Selection Of

The amount of land for the current location of housing development has resulted in developers choosing the location of housing development regardless of the condition of the land, infrastructure, socio-economic. To overcome this problem a computer system is needed in the form of a GDSS that can assist in the selection of Housing Development Locations.This study aims to implement a GDSS with ANP and Borda methods to determine the selection of the right and fast housing development location. GDSS is needed because there are 3 Individual Decision Makers, DM-1  assessing based on Land Conditions, DM-2 assessing Infrastructure-based, DM-3 assess the Socio-Economic and Decision Maker based groups to make the final decision. The ANP method is used to weight the criteria from each alternative location, to the alternative ranking of housing construction locations for each individual Decision Maker. The Borda method is used to combine the results of ranking carried out by the Group Decision Maker so that it gets the final ranking as a determinant of the Location of Housing Development.The final result of this research is a decision support system that can help developers to get a priority recommendation according to the needs of the developer.

Sistem Pendukung Keputusan Penentuan Kualitas Tempe Siap Jual Dengan Metode Weight Product

2020 ◽  
Vol 3 (2) ◽  
pp. 158-162
Author(s):  
Benyamin Sembiring ◽  
Sulindawaty Sulindawaty
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Raw Material ◽  
Final Decision ◽  
Traditional Methods ◽  
Calculation Process ◽  
Product Method

According to this SNI, soybean tempeh is packaged in well-closed packages, namely leaves and plastic. At MSME Latersia Berkat Tempe, it was found that information problems determining the quality of tempe were very diverse in determining the quality of tempe, generally using traditional methods. In this study, the calculation was carried out by applying the SPK with the Weighted Product (WP) method in determining the quality of ready-to-sell tempe and designing the Decision Support System (SPK) application with the Weighted Product (WP) method in determining the quality of ready-to-sell tempe using Visual Studio 2010. Analysis of the data obtained Tempe data as alternative data is taken from general packaging, namely Tempe Wrapped in Plastic and Tempe Wrapped in Leaves. The criteria for determining the quality of tempe production, in this study are influenced by Raw Material (C1), Type of Yeast (C2), Packaging (C2), Taste (C4), Color (C5), Typical Odor of Tempe (C6), Texture (C7), Sales (C8). In the application, the Alternative Data and Criteria Data are inputted, then the calculation process is carried out using the Weighted Product method. The result of the WP ranking calculation is determined to be the highest value to be the final decision of the system.

A Study of Fuzzy Logic as a Decision Support System for Determining the Best Athletes

2018 ◽  
Vol 7 (2.13) ◽  
pp. 348
Author(s):  
Siddik Karo-Karo ◽  
. . ◽  
. . ◽  
. . ◽  
. .
Keyword(s):  
Fuzzy Logic ◽  
Decision Support ◽  
Decision Support System ◽  
Decision Maker ◽  
Support System ◽  
Final Decision ◽  
Optimal Selection ◽  
Selection Of Variables ◽  
Selection Of

The selection of athletes with the best conditions is very required to follow various sports agenda that will be followed, to do the selection can be used decision support system by applying fuzzy logic as a tool of decision maker by doing the selection of variables used. Expected results with the use of this fuzzy logic obtained optimal selection with sufficient variables complete and the best athlete is a recommendation given and not made the final decision.  

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