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All Journal Jurnal Mantik Jurnal ICT : Information and Communication Technologies
LELIANA HARAHAP
AMIK Medicom
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering

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PREDICTION OF STUDENTS DROP OUT WITH SUPPORT VECTOR MACHINE ALGORITHM Sartika Dewi Purba; LELIANA HARAHAP; JONAS FRANKY RUDIANTO PANGGABEAN
Jurnal Mantik Vol. 6 No. 1 (2022): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

The quality of a university can be seen from the high level of student success and the low level of student failure. As for the cause of student failure is the case of drop out. To overcome these problems, predictions are made using the support vector machine method. The Support Vector Machine tries to find the optimal hyperplane where the two pattern classes can be separated maximally, the parameters used in the Support Vector Machine are only kernel parameters in one C parameter which gives a penalty on randomly classified data points. In the Support Vector Machine the weights (w) and biases (b) are global optium solutions from quadratic programming so that just running once will result in a solution that will always be the same for the same kernel and parameter choices. Through the implementation of the support vector machine, it is expected to get the parameters of the Support Vector Machine that are used correctly to obtain the best margin in predicting students dropping out.
Decision Support System for Choosing the Best Doctor at Sari Mutiara Hospital Using the Fuzzy Tsukamoto Method Leliana Harahap; Sartika Dewi Purba
Jurnal ICT : Information and Communication Technologies Vol. 12 No. 2 (2021): October, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

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Abstract

Doctors are medical personnel who are allowed to practice medical without having to have a specific specialty, and in the hospital there are several specialist doctors, one of which is an obstetrician who is an obstetrician and midwife who has an official title of Sp.OG. So far, the decision making on the selection of the best doctor carried out by the assessment team often faces problems in determining the best doctor candidate where the results obtained are ineffective in determining the best doctor which is decided by means of deliberation meetings. So of the many best doctor candidates who have met the criteria, not all will be the recipients of the best doctor candidates. This is because there is no objective method to make a quick choice based on the doctor's data which is correct according to the results of the deliberation meeting. By referring to the solution provided by Fuzzy Tsukamoto in helping to make a decision, an assessment team can quickly make a decision on the best doctor candidate as desired by comparing all the existing criteria. A decision support system is generally defined as a system that is capable of producing solutions and handling problems. Decision support systems are not intended to replace the role of decision makers, but rather to assist and support decision makers. This Fuzzy Tsukamoto method can determine the preference value of each alternative
Co-Authors Jonas Franky Rudianto Panggabean Sartika Dewi Purba