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Journal : Tech-E

Comparison of Data Mining Methods Using the Naïve Bayes Algorithm and K-Nearest Neighbor in Predicting Immunotherapy Success Budi Harto; Rino Rino
Tech-E Vol 2 No 2 (2019): Tech-E
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1012.214 KB) | DOI: 10.31253/te.v2i2.139

Abstract

tumor or cancer is a disease that is a problem for people who are increasing every year. This disease in both the early and final stages requires attention because in this disease sufferers have a large risk of death. along with the rapid development of technology, we can use the technology to facilitate in all fields one of which is to predict success in a therapy. Data mining is one of the techniques used by the author in testing the dataset used in this study to get the best algorithm between Naïve Bayes and the K-Nearest Neighbor algorithm by using the Rapid Miner S tudio application and applying the best algorithm into the expected application or expert system. can help users predict the success of a therapy.
Application of Neural Network Methods Based on Genetic Algorithm for Breast Cancer Prediction Rino Rino
Tech-E Vol 1 No 1 (2017): Tech-E
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1062.737 KB) | DOI: 10.31253/te.v1i1.19

Abstract

Cancer is a major challenge for mankind. Cancer can affect various parts of the body. This deadly disease can be detected in people of all ages. However, the risk of cancer increases with increasing age. Breast cancer is the most common cancer among women, and form largest cause of death for women as well. Then there are problems in the detection of breast cancer, resulting in the patient experiencing unnecessary treatment and cost. Insimilar studies, there are several methods used but there are problems due to the shape of the cancer cells are nonlinear. Neural networks can solve these problems, but neural network is weak in terms of determining the value of the parameter, so it needs to be optimized. Genetic algorithm is one of the optimization methods is good, therefore the values ​​of the parameters of the neural network will be optimized by using a genetic algorithm so as to get the best value of the parameter. Neural Network-based GA algorithm has the higher accuracy value than just using Neural Network algorithm. This is evident from the increase in value for the accuracy of the model Neural Network algorithm by 95.42% and the accuracy of algorithm-based Neural Network algorithm GA (Genetic Algorithm) of 96.85% with a difference of 1.43% accuracy. So it can be concluded that the application of Genetic Algorithm optimization techniques to improve the accuracy values on Neural Network algorithm.
Analysis And Design Analysis And Design Of Decision Supporting Information System For Assessment Of Recruitment And Employees Management With Analytical Hierarchy Process (Ahp) Method In PT. Indo Porcelain Tri Hartati; Rino Rino
Tech-E Vol 2 No 1 (2018): Tech-E
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (508.904 KB) | DOI: 10.31253/te.v2i1.273

Abstract

Managing human resources in the company is very important where human resources are needed for the progress of the company, in most companies, of course, can utilize all the human resources obtained in accordance with the need to contribute in accordance with the needs of the company to achieve its goals. PT. Indo Porcelain is engaged in manufacturing with ceramic dining table products, such as glassware, bowls and dishes. Problems faced by PT. Indo Porcelain is the absence of an integrated information system, so that the employee recruitment process requires time in making selection decisions for prospective employees while at the same time hampering the company's internal control. Based on the concept and design, it can be concluded that it has been built "ANALYSIS AND DESIGN OF DECISION SUPPORT INFORMATION SYSTEM FOR ASSESSMENT OF EMPLOYEE RECRUITMENT AND MANAGEMENT USING ANALYTICAL HIERARCHY PROCESS (AHP) METHOD IN PT. INDO PORCELAIN" to assist HRD in making decisions. It can be concluded that the results of the implementation of this new system can help the management department more easily, efficiently and effectively. With the decision support system using the Analytical Hierarchy Process method, the recruitment process is faster and easier. Information on the results of recruitment obtained by company management becomes more structured so that the decision support process taken by the management can produce more accurate decisions.
The Comparison of Data Mining Methods Using C4.5 Algorithm and Naive Bayes in Predicting Heart Disease Rino Rino
Tech-E Vol 4 No 2 (2021): Tech-E
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v4i2.543

Abstract

Heart disease is a condition of the presence of fatty deposits in the coronary arteries in the heart which changes the role and shape of the arteries so that blood flow to the heart is obstructed. Data mining methods can predict this disease, some of the methods are C4.5 Algorithm and Naive Bayes which are often used in research.The data set in this research was obtained from the uci machine learning repository site, where the dataset has 3546 records and 13 attributes.The accuracy value of the Naïve Bayes algorithm has a high value of 81.40% compared to the C4.5 algorithm which only has an accuracy value of 79.07%. Based on the calculation results, it can be concluded that the Naïve Bayes Algorithm is a very good clarification because it has a value between 0.709 - 1.00.From conclusion above, the Naïve Bayes algorithm has a higher accuracy value than the C4.5 algorithm so the researchers decided to use the Naïve Bayes algorithm in predicting heart disease.
Monitoring Computer Activities with Cloud to Device Messaging (C2DM) Suwitno Witno; Rino Rino
Tech-E Vol 1 No 2 (2018): Tech-E
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (469.274 KB) | DOI: 10.31253/te.v1i2.42

Abstract

In a particular division, a supervisor needs to perform monitoring of the activities carried out at his employers to improve the performance of the work of his subordinates. Leaders are often not in place to monitor the activities of his subordinates in carrying out their responsibilities. One solution to overcome these problems is to supervise the use of their computer by means of push notification. By utilizing the technology of Cloud to Device Messaging (C2DM), supervisor can monitor computer activities of his employers anywhere. Given this research, is expected to help the supervisor in monitoring his employers despite not being in place. This may indirectly improve performance in a division. For further research can be developed monitoring in a real time.