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Derwin R Sina
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Computer Science & IT

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Journal : J-Icon : Jurnal Komputer dan Informatika

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Implementasi Metode Analisis Gap Dan Profile Matching Untuk Kelayakan Calon Debitur Di Koperasi Simpan Pinjam (Ksp) Kopdit Solidaritas Santa Maria Assumpta yelly y nabuasa; Adriana Fanggidae; Derwin R Sina; Arfan Y Mauko
J-Icon : Jurnal Komputer dan Informatika Vol 7 No 2 (2019): Oktober 2019
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v7i2.1652

Abstract

In granting credit to debtors, it must go through an assessment of whether the debtor is appropriate or not feasible. KSP Koprit Solidaritas has set policy standards in granting credit to accept or reject the risk of bad credit, namely assessing prospective borrowers who meet the conditions of character rating, ability to pay off credit, capital owned, collateral owned and socioeconomic conditions. In this study, the design and manufacture of decision support system applications were carried out using profile matching methods to assess the eligibility of prospective debtors. Profile Matching is used to determine the priority with the highest ranking, which is used as a suggestion from the right system in determining the best alternative. The test results using 60 data obtained an accuracy of 81.667% with an error rate of 18.333% which indicates that the decision support system is functioning optimally following the Profile Matching method.
IMPLEMENTASI CASE BASED REASONINGUNTUK MENDIAGNOSIS PENYAKIT TUBERKULOSIS MENGGUNAKANALGORITMA K-NEAREST NEIGHBOR Emanuel Tes Atok; Derwin R Sina; Dony M Sihotang
J-Icon : Jurnal Komputer dan Informatika Vol 7 No 2 (2019): Oktober 2019
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v7i2.1656

Abstract

Case-Based Reasoning produces a solution based on similarities to previous cases. New case solutions result from the placement of similarities with old cases. In this reseach the authors applied CBR to diagnose tuberculosis. System knowledge sources are obtained by collecting medical records of tuberculosis patients in 2014-2016. Calculation of similarity values using the K-Nearest Neighbor algorithm with a thereshold value of 80%. This system can diagnose 3 types of tuberculosis based on 25 symptoms. The system output consists of the type of tuberculosis based on the symptoms experienced by the patient, treatment solutions and presentation of similarities between new cases and old cases. Based on the results of testing with 51 cases the results: (a) testing with 3 new case scenarios obtained the accuracy of each system for data scenarios obtained by 31 training data (60% of 51 cases) and 20 test data (40% of 51 cases) accuracy is 63%, the second scenario accuracy obtained with 35 training data (70% of 51 cases) and 16 test data (30% of 51 cases) accuracy is 69.2% and the third scenario accuracy obtained with 41 training data (80% of 51 cases) and 10 test data (20% of 51 cases) accuracy is 90%. (b) The results of testing of the old cases in the case base obtained 100% accuracy of the system.
SISTEM CASE BASED REASONING UNTUK MENDIAGNOSIS PENYAKIT ANJING BERBASIS WEB Dwi C Djahilape; Derwin R Sina; Tiwuk Widiastuti
J-ICON : Jurnal Komputer dan Informatika Vol 4 No 1 (2016): Maret 2016
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v4i1.5194

Abstract

The design of medium for consultation purpose is firstly caused by the lack of society awareness of dogs’ disease, their responsibility to regularly take care of the pet when it sufferred a disease and the cost of care. This medium care is the application of Case Based Reasoning (CBR). CBR is kind of reasoning used to solve a new problem by adapting the solutions found in the previous cases through summing the similarities. In this research the Simple Matching Coefficient (SMC) method is employed to count the similarities. This Case Based Reasoning application will produce the output like kind of disease sufferered by dogs based on symptoms reported by the proprietor. Furthermore, the application serve you with the solution of medical care. This application is a web based with aims to facilitate the user to access the information needed easily. The system trial showing that the program can do the diagnose well according to symptoms reported. The result of the diagnose is also provided with the similarities percentage with the previous case. This aims to improve the level of validity and the accurateness of disease found in dogs.
Co-Authors Adriana Fanggidae Adriana Fanggidae Arfan Y Mauko Dwi C Djahilape Emanuel Tes Atok Sihotang, Dony Martinus Tiwuk Widiastuti yelly y nabuasa