Jakarta, Indonesia
Jakarta, Indonesia

Tarumanagara University is a university in Jakarta, Indonesia and one of the oldest private universities in Indonesia. The university has 4 campuses in Jakarta. Campus I and campus II is located in the metropolitan area of West-Jakarta, the campus III is in South-Jakarta. The future campus IV site is in Karawaci . Wikipedia.

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Haris D.A.,Tarumanagara University
Proceedings - ICACSIS 2014: 2014 International Conference on Advanced Computer Science and Information Systems | Year: 2014

Attacking is one of the popular tactics usually chosen by a soccer coach. With attacking effectively, chances to score goals can be enhanced as many as possible. Better attack needs good ball passing, and that is the purpose and focus of this research. Previous robotic soccer simulations employed simple weighting method with simple criteria and does not produce optimal ball passing. To overcome this problem this research proposes a set of criteria representing a more realistic situation. This set of criteria is formulated in and appropriate objective function which is optimized using pareto frontier and Normalized Normal Constraint. From the result of this experiment, it can be seen that this proposed method has a realibility of 20% higher that that of the previous method. And it has a better passing success rate with a 75% ball possession. Rather than that of the previous method with a 25% ball possession. © 2014 IEEE.

Handhayani T.,Tarumanagara University | Hiryanto L.,Tarumanagara University
Procedia Computer Science | Year: 2015

Intelligent Kernel K-Means is a fully unsupervised clustering algorithm based on kernel. It is able to cluster kernel matrix without any information regarding to the number of required clusters. Our experiment using gene expression of human colorectal carcinoma had shown that the genes were grouped into three clusters. Global silhouette value and davies-bouldin index of the resulted clusters indicated that they are trustworthy and compact. To analyze the relationship between the clustered genes and phenotypes of clinical data, we performed correlation (CR) between each of three phenotypes (distant metastasis, cancer and normal tissues, and lymph node) with genes in each cluster of original dataset and permuted dataset. The result of the correlation had shown that Cluster 1 and Cluster 2 of original dataset had significantly higher CR than that of the permuted dataset. Among the three clusters, Cluster 3 contained smallest number of genes, but 16 out of 21 genes in that cluster were genes listed in Tumor Classifier List (TCL). © 2015 The Authors. Published by Elsevier B.V.

Jap T.,Tarumanagara University | Tiatri S.,Tarumanagara University | Jaya E.S.,Tarumanagara University | Suteja M.S.,Tarumanagara University
PLoS ONE | Year: 2013

Online game is an increasingly popular source of entertainment for all ages, with relatively prevalent negative consequences. Addiction is a problem that has received much attention. This research aims to develop a measure of online game addiction for Indonesian children and adolescents. The Indonesian Online Game Addiction Questionnaire draws from earlier theories and research on the internet and game addiction. Its construction is further enriched by including findings from qualitative interviews and field observation to ensure appropriate expression of the items. The measure consists of 7 items with a 5-point Likert Scale. It is validated by testing 1,477 Indonesian junior and senior high school students from several schools in Manado, Medan, Pontianak, and Yogyakarta. The validation evidence is shown by item-total correlation and criterion validity. The Indonesian Online Game Addiction Questionnaire has good item-total correlation (ranging from 0.29 to 0.55) and acceptable reliability (α = 0.73). It is also moderately correlated with the participant's longest time record to play online games (r = 0.39; p<0.01), average days per week in playing online games (ρ = 0.43; p<0.01), average hours per days in playing online games (ρ = 0.41; p<0.01), and monthly expenditure for online games (ρ = 0.30; p<0.01). Furthermore, we created a clinical cut-off estimate by combining criteria and population norm. The clinical cut-off estimate showed that the score of 14 to 21 may indicate mild online game addiction, and the score of 22 and above may indicate online game addiction. Overall, the result shows that Indonesian Online Game Addiction Questionnaire has sufficient psychometric property for research use, as well as limited clinical application. © 2013 Jap et al.

Herwindiati D.E.,Tarumanagara University | Isa S.M.,Tarumanagara University
Lecture Notes in Electrical Engineering | Year: 2010

Principal Component Analysis (PCA) is a technique to transform the original set of variables into a smaller set of linear combinations that account for most of the original set variance. The data reduction based on the classical PCA is fruitless if outlier is present in the data. The decomposed classical covariance matrix is very sensitive to outlying observations. ROBPCA is an effective PCA method combining two advantages of both projection pursuit and robust covariance estimation. The estimation is computed with the idea of minimum covariance determinant (MCD) of covariance matrix. The limitation of MCD is when covariance determinant almost equal zero. This paper proposes PCA using the minimum vector variance (MVV) as new measure of robust PCA to enhance the result. MVV is defined as a minimization of sum of square length of the diagonal of a parallelotope to determine the location estimator and covariance matrix. The usefulness of MVV is not limited to small or low dimension data set and to non-singular or singular covariance matrix. The MVV algorithm, compared with FMCD algorithm, has a lower computational complexity; the complexity of VV is of order O(p 2). © 2010 Springer Science+Business Media B.V.

Hiryanto L.,Tarumanagara University
2013 International Conference on Quality in Research, QiR 2013 - In Conjunction with ICCS 2013: The 2nd International Conference on Civic Space | Year: 2013

University Course Timetabling Problem (UCTP) belongs to Constraint Satisfaction Problems (CSPs), which are the set of objects whose state must satisfy a number of constraints. The constraints, in this case, are related to characteristics and regulations of a particular university. Certainly, these will vary from one university to the other. A number of approaches have provided feasible and optimal solutions for UCTP. However, their solutions are still based certain university's constraints. Our approach has given another way to occupy various constraints for various universities. Dynamic Constraint Matching (DCM) consists of constraints logical formulation, collision matrix generation, and validation using the collision matrix. Our experiment, using 93 subjects offered in Faculty of Information Technology Tarumanagara University, has shown that all constraints, taken from the characteristics and regulations of the Faculty, can be formulated successfully. When DCM were integrated with Vertex Graph Coloring (VGC) as one of the guaranteed optimal solutions for UCTP, the approach results a course schedule that does not contain any hard or soft constraints violations. The processing time can be said fast, which is less than 1 minutes. © 2013 IEEE.

Kosasih W.,Tarumanagara University
ARPN Journal of Engineering and Applied Sciences | Year: 2016

This paper describes how to develop a decision support system for classifying production equipment by considering a Multi Criteria Decision Making (MCDM) Method for Productivity, Quality, Cost, Delivery, Safety (PQCDS) indicators based on its condition. The study was conducted by using fuzzy assessment approach. The purposes of this study are: to define each criterion of each indicator; to determine fuzzification of value of each criterion; to design appropriate fuzzy rule base; and to develop a decision support system. The Categories of equipment were divided into 3 classes, such as: critical, mayor, minor. In this study, fuzzy rules were designed based on expert's knowledge and experiences. Finally, the results were simulated and compared with conventional method. © 2006-2016 Asian Research Publishing Network (ARPN).

Herwindiati D.E.,Tarumanagara University
Proceedings of the 7th International Conference on Engineering Computational Technology | Year: 2010

Classification is one technique of data mining used to predict group membership based on information on one or more characteristics of data. The classification is not easy when more than one variable could be loaded the same information and the one of variables can be written as a near linear combination of the other variables. The reduction of dimension has to be applied in handling those problems of classification. Principal components analysis (PCA) is the most popular among the dimension reduction analysis which is used to transform the original set of variables into a smaller set of linear combinations that accounts for most of the original set variance. The first principal component is the combination of variables that explains the greatest amount of variation. The data reduction based on the classical PCA becomes unreliable if outliers are present in the data. The first component consisting of the greatest variation is often pushed toward the anomalous observations. PCA is classical approach widely used for application of dimension reduction. One disadvantage of PCA is the elaborate computation. The two dimensional Principal Component (2DPCA) was proposed by Yang et al for reducing of computational time of standard PCA. The interesting process of 2DPCA inspires author to experiment with the classification using the robust 2DPCA, when the anomalous observations are 'hidden' in a data set. This paper proposed the new measure of classification by combining of two advantages from two approaches; they are the two dimensional (2D) projection approaches and the robust approach. The robust minimizing vector variance is chosen for 2D projection of the general matrix data. Based on the several experiments, the MVV robust 2DPCA gives the promising results. © 2010 Civil-Comp Press.

Lina,Tarumanagara University
2010 The 2nd International Conference on Computer and Automation Engineering, ICCAE 2010 | Year: 2010

In this paper, we propose novel techniques of constructing appearance manifolds in eigen-space for robust recognition of 3D objects. Four models are presented in this paper: Constant Covariance method, Point Interpolation method, Covariance Interpolation method, and comparison with the well known Parametric Eigenspace method. The developed application is used to recognize 3D objects from images with various capturing conditions. Experimental results show that the proposed methods could accurately recognize 3D objects even from images which are influenced by geometric distortions and quality degradation effects. ©2010 IEEE.

Supartono F.X.,Tarumanagara University
IABSE Conference, Guangzhou 2016: Bridges and Structures Sustainability - Seeking Intelligent Solutions - Report | Year: 2016

This paper presents various aspects of the sustainable infrastructure development that is mandatory for civil engineers to promote or even be a leader in pioneering its implementation, particularly in concrete production and construction that is the topic of this paper. It can be a wide range of application from design, materials, construction method, cost effectiveness and durability, for which the engineers should be able to use their knowledge and abilities to manage their activity in harmony with the environment, as well as to inspire the optimism to create a sustainable infrastructure world. At the end of this paper, engineers are encouraged to learn from the past and think to the future, as well as to always update and improve the voluntary action plans on sustainable development, which will lead humanity and environment to coexist harmoniously.

Haris D.A.,Tarumanagara University | Sugito E.,SLJ Kuningan Jakarta
ICACSIS 2015 - 2015 International Conference on Advanced Computer Science and Information Systems, Proceedings | Year: 2015

Classcraft is a free online E-Learning system that using gamification concept. Educational role-playing game that teachers and students play together in the classroom. Classcraft is more than E-Learning. By using many of the conventions traditionally found in games today, students can level up, work in teams, and earn powers that have real-world consequences. Acting as a gamification layer around any existing curriculum, the game transforms the way a class is experienced throughout the school year. Past research about E-Learning system has become one of the authors of reference for the conduct of this study. This research involve a number of FTI Untar students. Data was collected through observation, questionnaires and interviews. The questionnaire was made based on the model of the Unified Theory of Acceptance and Use of Technology (UTAUT) that have been modified. Author perform data processing using techniques Partial Least Square (PLS) and using an application called SmartPLS. The study states that the factors that affect users using ClassCraft in general is an e-learning motivation, facilitating conditions, and behavioral intention. © 2015 IEEE.

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