scholarly journals Decision Support System for Tour Package Recommendation in Bali Using BWM-MARCOS Method

2021 ◽  
pp. 143
Author(s):  
Ni Ketut Pradani Gayatri S ◽  
I Made Candiasa ◽  
Kadek Yota Ernanda Aryanto
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Confusion Matrix ◽  
Travel Agent ◽  
Optimal Weight ◽  
Travel Agents ◽  
Alternative Tourism

Bali is one of the provinces with profitable tourism opportunities. It has led to many businesses related to tourism, which is a travel agent. Travel agents in Bali usually offer variety of tour packages with different prices and specifications. The problem experienced by tourists in determining tour packages is that the price of tour packages is quite high and does not match the tourist budget. In addition, the schedule of visits from tour packages is also inflexible. This problem can be overcome by making a decision support system for forming tour packages. This study uses the BWM method to determine each criterion’s optimal weight and the MARCOS to rank alternative tourism objects that will form a tour package. Testing results using confusion matrix get an accuracy value of 74.19%, precision of 81.25%, recall / sensitivity of 72.22% and specificity of 76.92%.

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 Initiative For Thyroid Cancer Diagnosis: Decision Support System For Anaplast Thyroid Cancer

2017 ◽  
Vol 1 (2) ◽  
pp. 48
Author(s):  
Jamil Ahmed Chandio ◽  
M. Abdul Rehman Soomrani ◽  
Attaullah Sehito ◽  
Shafaq Siddiqui
Keyword(s):  
Thyroid Cancer ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Confusion Matrix ◽  
Measurement Techniques ◽  
Research Area ◽  
Classification Problems ◽  
Biomedical Image ◽  
High Level

Due to the high level exposure of biomedical image analysis, Medical image mining has become one of the well-established research area(s) of machine learning. AI (Artificial Intelligence) techniques have been vastly used to solve the complex classification problems of thyroid cancer. Since the persistence of copycat chromatin properties and unavailability of nuclei measurement techniques, it is really problem for doctors to determine the initial phases of nuclei enlargement and to assess the early changes of chromatin distribution. For example involvement of multiple transparent overlapping of nuclei may become the cause of confusion to infer the growth pattern of nuclei variations. Un-decidable nuclei eccentric properties may become one of the leading causes for misdiagnosis in Anaplast cancers. In-order to mitigate all above stated problems this paper proposes a novel methodology so called “Decision Support System for Anaplast Thyroid Cancer” and it proposes a medical data preparation algorithm AD (Analpast_Cancers) which helps to select the appropriate features of Anaplast cancers such as (1) enlargement of nuclei, (2) persistence of irregularity in nuclei and existence of hyper chromatin. Proposed methodology comprises over four major layers, first layer deals with the noise reduction, detection of nuclei edges and object clusters. Second layer selects the features of object of interest such as nuclei enlargement, irregularity and hyper chromatin. Third layer constructs the decision model to extract the hidden patterns of disease associated variables and final layer evaluates the performance evaluation by using confusion matrix, precision and recall measures. The overall classification accuracy is measured about 97.2% with 10-k fold cross validation.

scholarly journals Implementasi Decision Support System Dynamic Menggunakan Weight Product Untuk Menentukan Uang Kuliah Tunggal

2020 ◽  
Vol 5 (1) ◽  
pp. 1-8
Author(s):  
Dyah Ayu Wiranti ◽  
Kurnia Siwi Kinasih ◽  
Ainafatul Nur Muslikah ◽  
Dyah Wardani ◽  
Agung Teguh Wibowo Almais
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Private Colleges ◽  
Confusion Matrix ◽  
System Dynamic ◽  
Student Needs ◽  
Time Of Admission ◽  
F Measure

Single tuition is the extension of the single tuition, which can be interpreted as a payment system made at the time of admission in both State and private colleges in Indonesia.  Where this single tuition can provide benefits for the equitable of each student and help the students who are less able in terms of the economy that is certainly derived from the underprivileged family. In the calculation process determines the single tuition money each student needs a long process and time. So, there is an idea to implement a Decision Support System Dynamic (DSSD) so that at the time of determination of single tuition can be evenly and by the actual situation. One method that can be used on DSSD is the Weighted Product (WP) method. By implementing the method of WP combined with the concept of DSSD, then generated values of confusion matrix (recall, precision, f-measure, and accuracy) obtained by looking for the value of comparison between test data with pattern data. Obtained confusion matrix value with system testing and get the results Precision 88.89%, Recall 82.76%, Accuracy 77.14%, F-Measure 85.71%.

scholarly journals PENERAPAN DECISION SUPPORT SYSTEM DYNAMIC MENGGUNAKAN SIMPLE ADDICTIVE WEIGHTING DALAM PENENTUAN PEGAWAI TERBAIK

2020 ◽  
Vol 5 (1) ◽  
pp. 17-24
Author(s):  
Tanti Rismawati ◽  
Muhammad Aji Pangestu ◽  
Agung Teguh Wibowo Almais
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Test Data ◽  
Support System ◽  
Intelligent System ◽  
Confusion Matrix ◽  
Web Based ◽  
Simple Additive Weighting ◽  
A Company ◽  
F Measure

Lots of applications or programs that are very useful to simplify human work. This includes applications that are made within a company. A company needs an intelligent system or an agent that controls the company's system. In a company has employees who work. This research will discuss the Dynamic Decision Support System in determining the best employees using one of the web-based Multi-Criteria Decision Making methods, which is Simple Additive Weighting (SAW). By using 2 types of data namely pattern data and test data. The data inputted were 15 data consisting of 10 test data and 5 pattern data. Then a confusion matrix can be obtained in the form of an accuracy value of 25%, a precision of 100%, a recall of 14%, and an F Measure of 24.5%.

scholarly journals PENERAPAN WEIGHTED PRODUCT UNTUK MENENTUKAN MUSYRIF-MUSYRIFAH MA’HAD SUNAN AMPEL AL-ALY UIN MAULANA MALIK IBRAHIM MALANG

2020 ◽  
Vol 5 (1) ◽  
pp. 44-52
Author(s):  
Hardiana Riski RIswanto ◽  
Rofi'ul Khasanah ◽  
Layla Qomariyah ◽  
Siti Kholifah
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Decision Support Systems ◽  
Support System ◽  
Support Systems ◽  
Confusion Matrix ◽  
Electoral System ◽  
Existing Problems ◽  
Selection Processes ◽  
F Measure

Decision support systems mushrifs / ah which is currently still based only add data themselves and upload files online requirements. Although candidates mushrifs / ah will pass some other selection processes, the recommendations of the top leaders become more value every candidate mushrifs / ah listed. So that the electoral system is still subjective. This research aims to develop a decision support system mushrifs / ah to implement the Decision Support System (DSS) that mushrifs decision support systems can be more objective. There are several criteria that the reference of the decision support system mushrifs / ah. One method used to resolve the existing problems in some of these criteria is a method of WP (Weighted Product). This method of evaluating several alternatives to atribuat or a set of criteria, where each attribute each independently of one another. By applying the WP method combined with the concept of DSSD then the resulting value of Confusion matrix (recall, percision, f-measure and accuracy) is obtained by finding the value of a comparison between the test data with the data pattern. And the confusion matrix obtained value that gets results Accuracy 75.00%, 71.43% recall, precission 83.33% and 76.92% F-Measure.

scholarly journals Sistem Pendukung Keputusan Kelayakan Kredit pada PT. BPR Mitra Catur Mandiri Menggunakan Metode Credit Scoring

Repositor ◽  
2020 ◽  
Vol 2 (5) ◽  
pp. 649
Author(s):  
Haris Diyaul Fata ◽  
Gita Indah Marthasari ◽  
Yufis Azhar
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Matrix Method ◽  
Confusion Matrix ◽  
Credit Scoring ◽  
Accuracy Rate ◽  
Scoring Method ◽  
The Creation ◽  
Credit Worthiness

Abstrak Kredit adalah suatu cara yang dapat dilakukan untuk mendapatkan modal usaha. Tetapi terkadang pihak bank mengalami kesulitan dalam melakukan penentuan kredit, hal ini dikarenakan terdapat beberapa kriteria yang tidak terpenuhi oleh calon nasabah. Maka dibutuhkan suatu sistem yang dapat mempermudah petugas bank dalam melakukan penentuan kelayakan kredit, yaitu dengan membangun sistem pendukung keputusan kelayakan kredit menggunakan metode credit scoring. Dalam penentuan kredit, metode credit scoring melakukan perhitungan berdasarkan kriteria-kriteria yang ada, sehingga dapat dihasilkan rekomendasi diterima atau ditolaknya sebuah pengajuan kredit. Berdasarkan penelitian yang telah dilakukan, hasil pembuatan sistem pedukung keputusan kelayakan kredit menggunakan metode credit scoring ini adalah mempermudah petugas bank dalam melakukan penentuan kredit. Berdasarkan pengujian menggunakan metode confusion matrix, sistem ini mempunyai performa yang sangat baik dengan tinggkat akurasi 93%.Abstract Credit is a way that can be done to obtain business capital. But sometimes the bank has difficulty in determining credit, this is because there are several criteria that are not met by prospective customers. Then a system is needed to facilitate bank officers in determining credit worthiness, namely by building a creditworthiness decision support system using the credit scoring method. In determining credit, the credit scoring method calculates based on existing criteria, so that recommendations can be generated or rejected for a credit proposal. Based on the research that has been done, the results of the creation of a support system for credit feasibility decisions using the credit scoring method is to facilitate bank officers in making credit determinations. Based on testing using the Confusion Matrix method, this system has a very good performance with an accuracy rate of 93%.

scholarly journals Decision Support System dalam Menentukan Mahasiswa Bermasalah Menggunakan Metode Topsis

2020 ◽  
Vol 5 (1) ◽  
pp. 9-16
Author(s):  
Adinda Dhea Pramitha ◽  
Aniss Fatul Fu'adah ◽  
Agung Teguh Wibowo Almais ◽  
Laela Nurul Qomariyah
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Confusion Matrix ◽  
Topsis Method ◽  
Good Ability ◽  
F Measure

At present many old semester students are starting to be undisciplined in attending lectures, this is due to the increasing burden of their assignments causing the enthusiasm of students to relax. This can create serious problems in the department because it can affect the accreditation level of the department. The purpose of this journal, which is to help the department admins to determine students who have problems in the field of lectures, so that the department can find out how many problem students can affect the accreditation of majors. In this journal, we implement the Decision Support System for manufacturing the system. With the TOPSIS method for calculations on the system, and using the Confusion Matrix for testing the system. From testing using confusion matrix, it can be concluded that precision produces 75%, recall produces 75%, accuracy produces 73%, and f-measure produces 75%. This shows that the system has a pretty good ability because it has exceeded the value of 70%.  

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