Retantyo Wardoyo

Segmentation on the Dental Periapical X-Ray Images for Osteoporosis Screening

Segmentation on the trabecular of dental periapical X-Ray images is very important for osteoporosis screening. Existing methods do not perform well in segmenting the trabecular of dental periapical in X-Ray images due to the presence of large amount of spurious edges. This paper presents a combination of tophat-bothat filtering, histogram equalization contrasting and local adaptive thresholding approach for automatic segmentation of dental periapical in X-Ray images. The qualitative evaluation is done by a dentist and shows that the proposed segmentation algorithm performed well the porous of trabecular features of dental periapical. The quantitative evaluation used fuzzy classification based on neural network to classify these features. It were found accuracy rate to be 99,96% for training set and around 65% for testing set for a dataset of 60 subjects.

PLANT RECOGNITION USING STEREO LEAF IMAGE USING GRAY-LEVEL CO-OCCURRENCE MATRIX

Adequate knowledge, such as information about the unique characteristics of each plant, is necessary to identify plant. Researchers have made plant recogni tion based on leaf characteristics. The leaf image- based plant recognition in view of different angles is a new challenge. In this study, the research on the p lant recognition was conducted based on leaf images resulted from 3D stereo camera. The 3D images are very influential in the development of computer vision t heory, which can provide more detailed information of an object. One of the information that can be obtai ned is about the position of the object in its imag e with the background as well as of the camera. One of the ways used to obtain such information is to calcula te the disparity. However, this method will only tell the position of the object compared to other objects wi thout that of range. Sum Absolute Different (SAD) is a method that can be used to find the disparity value. The SAD method does not require heavy computations and long process. Before calculating the disparity, all the images should be previously segmented. The objective of this segmentation is to separate all the objects from the background. Furthermore, filtering and polynomial transformation at the results of disparity is necess ary to improve the quality of resultant images. Furthermor e, 22 features were extracted using GLCM features (second order statistics) of images resulted from disparity improvement. The highest accuracy of match in the recognition of plant varieties was obtained at 50 cm distance a nd in the recognition of three plant varieties was 83.3%.

ELECTRE-Entropy method in Group Decision Support System Modelto Gene Mutation Detection

Application of Group Decision Support System (GDSS) can assist for delivering the decision of various opinions (preference) cancer detection based on the preferences of various expertise. In this paper we propose ELECTRE-Entropy for GDSS Modeling. We propose entropy weighting for each criteria under ELECTRE Method.ELECTRE is one method in Multi-Attribute Decision Making (MADM). Modeling of Group Decision Support Sytemapplyfor multi-criteria which the simulation data mutated genes that can cause cancer and solution recommended.

Modularity Index Metrics for Java-Based Open Source Software Projects

Open Source Software (OSS) Projects are gaining popularity these days, and they become alternatives in building software system. Despite many failures in these projects, there are some success stories with one of the identified success factors is modularity. This paper presents the first quantitative software metrics to measure modularity level of Java-based OSS Projects called Modularity Index. This software metrics is formulated by analyzing modularity traits such as size, complexity, cohesion, and coupling of 59 Java-based OSS Projects from sourceforge.net using SONAR tool. These OSS Projects are selected since they have been downloaded more than 100K times and believed to have the required modularity trait to be successful. The software metrics related to modularity in class, package and system level of these projects are extracted and analyzed. The similarities found are then analyzed to determine the class quality, package quality, and then combined with system architecture measure to formulate the Modularity Index. The case study of measuring Modularity Index during the evolution of JFreeChart project has shown that this software metrics is able to identify strengths and potential problems of the project.

Development of Copeland Score Methods for Determine Group Decisions

Voting method requires to determine group decision of decision by each decision maker in group. Determination of decisions by group of decision maker requires voting methods. Copeland score is one of voting method that has been developed by previous researchers. This method does not accommodate the weight of the expertise and interests of each decision maker. This paper proposed the voting method using Copeland score with added weighting. The method has developed of considering the weight of the expertise and interests of the decision maker. The method accordance with the problems encountered of group decision making . Expertise and interests of decision makers are given weight based on their expertises of decision maker contribution of the problems faced by the group to determine the decision. Decision making is the selection process of various alternative actions that might be chosen through a specific mechanism to make the best decision. The decision maker is done in order to achieve certain goals or objectives for solving problems. Organizational leaders rarely can solve the problem alone. Committees, working teams, project teams and task forces were formed in many organizations is approach to problem solving by group. GDSS is a computer-based interactive system to facilitate the achievement solution of problem by a group of decision makers. That is consistent with the statement of Turban (2005): A group decision support system (GDSS) is as interactive components of the facilities based system that solution of semi structured or unstructured problems by a group of decision makers in unstructured nature. GDSS was developed to address challenges to the quality and effectiveness of decision-making is done by more than one person (group of people). Issues that need to be highlighted in decision-making by a group of people, among others, is the number of decision-makers, the time should be allocated, and the increase the existing participants. GDSS provides support in solving the problem by providing a setting that supports communication for members who joined the group. The problem solving is done by a group of people who are members of the GDSS who need a voting method to obtain a group decision. Copeland score method is one method of voting to earn wages, which is a joint decision-making. So far, existing methods Copeland score considers that all of the decision maker has the same weight, but sometimes the decision maker has a different weight in determining a joint decision. For it is necessary to develop a method of voting with respect to the weight of each decision maker based on the level of expertise and interests to the problem.

Review of Image Compression and Encryption Techniques

In line with a growing need for data and information transmission in a safe and quick manner, researches on image protection and security through a combination of cryptographic and compression techniques begin to take form. The combination of these two methods may include into three categories based on their process sequences. The first category, i.e. cryptographic technique followed by compression method, focuses more on image security than the reduction of a size of data. The second combination, compression technique followed by the cryptographic method, has an advantage where the compression technique can be lossy, lossless, or combination of both. The third category, i.e. compression and cryptographic technologies in a single process either partially or in the form of compressive sensing(CS) provides a good data safety assurance with such a low computational complexity that it is eligible for enhancing the efficiency and security of data/information transmission.

E-Participation Modeling and Developing with Trust for Decision Making Supplement Purpose

ICT has been employed in various areas, including e-Participation to support citizen participation and achieve democracy ideal. Trust as a social behavior can be used as a method to model preferences and facilitate better participation and interaction in a decision making within a group of decision makers. In this paper we present literatures survey related to e-Participation and trust in computer science; we also proposed a Group Decision Support System model and application, which utilizes trust to support decisions in a collaborative team. In brief, the model is based on the synthesis of group members’ preferences following an appropriate aggregation procedure.

The Group Decision Support System to Evaluate the ICT Project Performance Using the Hybrid Method of AHP, TOPSIS and Copeland Score

This paper proposed a concept of the Group Decision Support System (GDSS) to evaluate the performance of Information and Communications Technology (ICT) Projects in Indonesian regional government agencies to overcome any possible inconsistencies which may occur in a decision-making process. By considering the aspect of the applicable legislation, decision makers involved to provide an assessment and evaluation of the ICT project implementation in regional government agencies consisted of Executing Parties of Government Institutions, ICT Management Work Units, Business Process Owner Units, and Society, represented by DPRD (Regional People’s Representative Assembly). The contributions of those decision makers in the said model were in the form of preferences to evaluate the ICT project-related alternatives based on the predetermined criteria for the method of Multiple Criteria Decision Making (MCDM). This research presented a GDSS framework integrating the Methods of Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Copeland Score. The AHP method was used to generate values for the criteria used as input in the calculation process of the TOPSIS method. Results of the TOPSIS calculation generated a project rank indicated by each decision maker, and to combine the different preferences of these decision makers, the Copeland Score method was used as one of the voting methods to determine the best project rank of all the ranks indicated by the desicion makers.

Feature extraction methods for batik pattern recognition: A review

Batik is one of the world’s cultural heritages with various decorative patterns. Each batik has its unique pattern characteristic such as color intensity, ornament visualisation and ornament size. Batik with a large-sized ornament and a high-intensity color on its background will result in a clear edge and easy-to-recognise ornaments. While batik with a small-sized ornament and a low-intensity color of the background will produce slight edge ornaments, thus it becomes difficult to recognise. In order to recognise any patterns of batik, some features that can represent each pattern are becomes necessary. Batik pattern features can be obtained from various methods of feature extraction. This paper will address various methods of feature extraction of batik for recognising batik patterns. These methods of feature extraction are categorised into several groups based on visual features produced by batik including feature extraction of color, texture formed in batik, and shape of batik ornament. The grouping of...

FUZZY RULE SURAM FOR CONTROL SYSTEM OF A SOLAR ENERGY WOOD DRYING CHAMBER

The paper reports used the fuzzy rule Suram for control system of a wood drying chamber with solar as source of energy. Rule suram based of fuzzy logic with variables of weather is temperature ambient and conditions of air is humidity ambient, it implemented for wood drying process. The membership function of variable of state represented in error value and change error with typical of triangle and trapezium map. Result of Analysis to reach 8 fuzzy rule to control the output system can be constructed in a number of way of weather and conditions of air. It used to minimum of the consumption of electric energy by heater. The rule suram used to stability and equilibrium of schedule of drying in chamber by control of temperature and humidity. The result of implemented of fuzzy rule suram with the modification of membership function in range [0.5, 1] represented approximate to he conditions riel.