Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : Jurnal Informatika

PENERAPAN DECISION TREE C4.5 SEBAGAI SELEKSI FITUR DAN SUPPORT VECTOR MACHINE (SVM) UNTUK DIAGNOSA KANKER PAYUDARA Pakarti Riswanto; RZ. Abdul Aziz; Sriyanto -
Jurnal Informatika Vol 19, No 1 (2019): Jurnal Informatika
Publisher : IIB Darmajaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30873/ji.v19i1.1442

Abstract

In the field of medicine, the use of data mining has a quite important and evolutionary role that can change the perspective of doctors, practitioners and health researchers in the process of detecting breast cancer in a patient. There are 2 classification applications in it, namely the process of diagnosing (diagnosing) cancer cells that distinguishes between tumors (benign cancer) or malignant cancer and prognosis (prognosis) to determine the possibility of reappearance of cancer cells in patients who have been operated on in the future. Data mining aims to describe new findings in the dataset and explain a process that uses statistical, mathematical, artificial intelligence, and machine learning techniques to extract and identify useful information and related knowledge from the database.Classification with data mining can be done using several methods, namely Decision Tree, K-Nearest Neighbor, Naive Bayes, ID3, CART, Linear Discriminant Analysis, etc., which certainly have advantages and disadvantages of each. But in this study, the author focuses on the classification of data mining using the Support Vector Mechine and Deccision Tree algorithms.This study will analyze the Breast Cancer Wisconsin Original data set obtained from the UCI Machine Learning Repository (repository of research data) to classify breast cancer malignancies. This time the author correlates between the Decision Tree classifier algorithm which has good ability to process large databases as a feature selection, then with a proper and relevant SVM Method used in analyzing and diagnosing breast breast cancer patients because it has accurate results for existing problems and several bases . Keywords— Data Mining, diagnosis, Decision Tree, SVM Method
AUDIT SISTEM INFORMASI MENGGUNAKAN METODE FRAMEWORK COBIT 5 Selamat Soni Harsono Wijaya; RZ Abdul Aziz
Jurnal Informatika Vol 19, No 2 (2019): Jurnal Informatika
Publisher : IIB Darmajaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30873/ji.v19i2.1681

Abstract

Information is one of the most important factors at this time, especially for organizations that use information technology (IT) as a supporter of their business processes. Lampung Post is a company that uses IT to support its business processes. But in its development, technological progress is also used as an opportunity to commit crime in cyberspace or other media that are often known as cyber crime. Cyber crime is to take over the website and also change the contents of the website content that causes harm to the company and also company partners who are still in one group of companies. To maintain the security of corporate information systems, a technology or system with good information security management is needed to safeguard information assets and prevent activities that can harm the company. For this reason, an information system audit is needed to assess current and expected capability of corporate information technology governance. This research on auditing information systems uses the COBIT 5 framework to find solutions to improve corporate information technology governance systems and use a scale of 0-5 in determining the capability level assessment. The results of the information system audit show that the current value is on a scale of 3 (Established), while the value of the excpect is at level 5 (Optimizing).Keywords :  Audit, Capability Level, Framework COBIT 5 , Information Systems
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN KONSENTRASI BIDANG ILMU EKONOMI MENGGUNAKAN METODE WEIGHTED AVERAGE DAN FUZZY FIS TSUKOMOTO ( Studi Kasus Program Magister Manajemen IIB Darmajaya ) Suci Mutiara; Yulmaini -; RZ Abdul Aziz
Jurnal Informatika Vol 19, No 2 (2019): Jurnal Informatika
Publisher : IIB Darmajaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30873/ji.v19i2.1855

Abstract

Postgraduate IIB Darmajaya in Management program in its curriculum offers concentration subjects in the third semester. Concentrations in the field of economics are grouped into three concentrations namely marketing, human resources (HR) and finance (Finance). In the third-semester students are required to choose one concentration of the field of economics according to their competence. But the obstacle is often found in the choice of concentration in the field of economics is that many students still unable recognize their interests and abilities. Besides, many students who choose the concentration in the field of economics only follow the most specialization, but do not follow based on their abilities. According to that, it requires the tool to able to provide decision support in term of selecting concentrations based on predetermined considerations. The methods used in solving this problem are Weighted Average Method and Tsukomoto Fuzzy FIS Method with 4 (four) input variables and 3 (three) output variables. Input variables consist of subject values, interest values, motivation values , and abilities. While the output variable consists of marketing concentration, human resources (HR) and finance (Finance) The sample was taken from second semester students of Master of Management.The test results show that the recommendation for the selection of the right concentration for these students is Financial specialization with a Defuzzification value of 65.91 higher than Marketing and Human Resources specialization which is 64,69 and 64,59, respectively Keywords: Decision Support System, Weighted Average Method, Tsukomoto Fuzzy FIS Method, Concentration