I ketut Gede Darma Putra
Udayana University

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Content Based Image Retrieval Using Lacunarity and Color Moments Of Skin Diseases Triwayuni, I Gusti Ayu; Darma Putra, I Ketut Gede; Eka Pratama, I Putu Agus
Indonesian Journal of Electrical Engineering and Computer Science Vol 9, No 1: January 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v9.i1.pp243-248

Abstract

The research conducted contributed in the form of CBIR application which was developed using texture and color feature extraction in searching the contents information of an object of skin disease image. The textured feature is extracted using Lacunarity, while for color feature extraction using Color Moments as well as a combination of both methods. The results of color characteristic extraction test using Color Moments Method yielded images corresponding to 100% similarity percentages and experimentation of texture characteristic extraction using Lacunarity Method yielded images corresponding to a percentage of suitability of 25%, followed by a combined test of both methods and the normalization process produces images corresponding to a percentage of conformity of 60%.
Hypertension Expert System with C5.0 Algorithm and Fuzzy Logic Ardi Yasa, I Gusti Made Ngurah; Darma Putra, I Ketut Gede; Marini Mandenni, Ni Md Ika
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 7: July 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i7.pp5569-5677

Abstract

Expert System is a knowledge -based system which is its knowledge is coming from the experts itself. This system is expected to help users to take best decisions in solving the problems they face. This expert system can be applied in various field of knowledges. Medical field is one area where expert system is needed in case of taking decision, such as diagnosing and treatment.Hypertension is one of medical disease that can be diagnosed from looking at the patient’s physical characteristics and the patient’s lifestyle. Beside using the experts knowledge in diagnosing process, we also combine it with C5.0 algorithms and fuzzy logic to get precise result. C5.0 algorithm is used to create a decision tree based on the experts, while fuzzy logic used to categorize the type of hypertensive disease that suffered by the patient and increase the level of accuracy of the diagnosing system. The accuracy of the combination between c5.0 algorithm and fuzzy logic is about 97.19%.
Sketching Expert System for Crime Investigation Purposes Yudistira, Bagus; Darma Putra, I Ketut Gede; Oka Sudana, Anak Agung Kompyang
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 7: July 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i7.pp5655-5660

Abstract

The presence of police sketcher play an important role in making investigation in purpose of making arrestment to fugitive or suspect. The lacking presence of police sketcher is making a lack in investigation process, because lack of information gathered for the further process. This limitation is overcome by developing an expert system using gadget as a helping device to making sketch, with adding sketcher knowledge. Sketching method already been used since long time in process of investigation and effective making the result. The result of expert system on case given showing the system to real object which made sketching reach 85% of accuracy level.
Fuzzy Expert System for Tropical Infectious Disease by Certainty Factor Darma Putra, I ketut Gede; Prihatini, Putu Manik
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 6: October 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Communication between doctor and patient play an important role in determining the diagnosis of the illness suffered by the patient. Consultation time constraints led to insufficient information obtained to produce a diagnosis. This limitation is overcome by developing an expert system using fuzzy logic to represent the vagueness of symptoms experienced by patients and the certainty factor represents a relationship between the symptoms and disease. Fuzzy logic method begins with the acquisition of knowledge to produce the facts and rules, implication process, composition and defuzzification. The result of defuzzification used in the calculation of sequential and combined certainty factor which represent the belief percentage of diseases diagnosis that suffered by the patient. The results of the expert diagnosis with expert system for the given cases indicates the system, has the similarity diagnosis with the expert at 93.99%. DOI: http://dx.doi.org/10.11591/telkomnika.v10i6.1223