Bangkalan, Indonesia
Bangkalan, Indonesia

Trunojoyo University is a public university located in the District Bangkalan , East Java province, Indonesia. University Trunojoyo to public universities under the Presidential Decree dated July 5, 2001. College was inaugurated on July 23, 2001 by President Abdurrahman Wahid. Wikipedia.

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Utami I.D.,Trunojoyo University
AIP Conference Proceedings | Year: 2016

Lean manufacturing was broadly implemented to reduce waste. This paper aims to design a simulation modelling to measure waste and cost reduction in lean manufacturing. This paper used integration of dynamic and agent based modelling to design a simulation model of waste measurement. The conceptual model was applied with data from a case study taken small and medium sized of Batik in Madura. A simulation model was then built to translate the conceptual model into a practical application. The simulation model was used to predict levels of total waste cost in different scenarios. The model was verified and validated through the construction simulation model with input from historical data from case study. This model aided decision makers in predicting level of waste cost by changing the value of variables in the interface on monitor. © 2016 Author(s).


Muntasa A.,Trunojoyo University
Journal of Information Processing Systems | Year: 2016

High dimensional space is the biggest problem when classification process is carried out, because it takes longer time for computation, so that the costs involved are also expensive. In this research, the facial space generated from homogeneous and non-homogeneous polynomial was proposed to extract the facial image features. The homogeneous and non-homogeneous polynomial-based eigenspaces are the second opinion of the feature extraction of an appearance method to solve non-linear features. The kernel trick has been used to complete the matrix computation on the homogeneous and non-homogeneous polynomial. The weight and projection of the new feature space of the proposed method have been evaluated by using the three face image databases, i.e., the YALE, the ORL, and the UoB. The experimental results have produced the highest recognition rate 94.44%, 97.5%, and 94% for the YALE, ORL, and UoB, respectively. The results explain that the proposed method has produced the higher recognition than the other methods, such as the Eigenface, Fisherface, Laplacianfaces, and O-Laplacianfaces. © 2016 KIPS.


Facial detection is a crucial stage in the facial recognition process. Misclassification during the facial detection process will impact recognition results. In this research, windowing system facial detection using the Gabor kernel filter and the fast Fourier transform was proposed. The training set images, for both facial and non-facial images, were processed to obtain the local features by using the Gabor kernel filter and the fast Fourier transform. The local features were measured using probabilistic learning vector quantization. In this process, facial and non-facial features were classified using label 1 and -1. The proposed method was evaluated using facial and non-facial image testing sets, which were taken from the MIT+CMU image database. The testing images were enhanced first before the detection process using four different enhancement methods: histogram equalization, adaptive histogram equalization, contrast limited adaptive histogram equalization, and the single-scale retinex method. The detection results demonstrated that the highest average accuracy was 83.44%. © IJTech 2017.


Muntasa A.,Trunojoyo University
International Journal on Electrical Engineering and Informatics | Year: 2016

This research proposed a new approach to recognize face image under various lighting expression. The Proposed method is started by generating of the Left Diagonal Matrix (LDM) and the Right Diagonal Matrix (RDM). Subsequently, the dimensionality reduction is conducted by using Two-Dimensional Eigenface of the LDM and the RDM. The results of dimensionality reduction are selected the maximum value based on the corresponding features. Finally, the geometric similarity measurement model is carried out to obtain the recognition rate. The proposed method was evaluated using three different facial image databases, which are the YALE, the ORL and the UoB face image databases. Two until six column features were used to measure the similarity between the training and the testing sets. Experimental results revealed that the proposed method produced 92.2%, 94%, and 94.7% recognition rate for the YALE, the ORL, and the UoB face image databases respectively. The proposed method was also compared to the other methods. On the ORL face image database, the comparison results show that the proposed method outperformed to the Eigenface, the Fisherface, and the Laplacianfaces but not for O-Laplacianfaces and Two-Dimensional Principal Component Analysis method. On the YALE and the UoB face image databases, the proposed method outperformed to the other appearance methods which are the Eigenface, the Fisherface, the Laplacianfaces, the O-Laplacianfaces and Two-Dimensional Principal Component Analysis methods. © 2016, School of Electrical Engineering and Informatics. All rights reserved.


Cahyani A.D.,Trunojoyo University
MATEC Web of Conferences | Year: 2016

Many researchers have attempted to utilize gamification to increase student engagement, motivation and achievement in the classroom with varying degrees of accomplishment. This research attempts to review of existing literature on the subject as well as the implementation of gamification on Language course. It aims to get better understanding of how gamification can efficiently be used in education. This analysis reveals that the underlying fact that make games engaging are already utilized in pedagogical practices. There are two important recommendations from this research. First, use gamified learning scenario as an activity, to encourage students trying new things and avoiding fear to make a mistakes. Secondly, the gamification in education setting needs students to participate deliberately to ensure the gamification retains the game-like nature. © Owned by the authors, published by EDP Sciences, 2016.


Numerous studies show that the implementation of Vendor Managed Inventory (VMI) benefits all members of the supply chain. This research develops model to prove the benefits obtained from implementing VMI to supplier-buyer partnership analytically. The model considers a two-level supply chain which consists of a single supplier and a single buyer. The analytical model is developed to supply chain inventory with probabilistic demand which follows normal distribution. The model also incorporates lead time as a decision variable and investigates the impacts of inventory management before and after the implementation of the VMI. The result shows that the analytical model has the ability to reduce the supply chain expected cost, improve the service level and increase the inventory replenishment. Numerical examples are given to prove them. © Owned by the authors, published by EDP Sciences, 2016.


Basuki A.,Trunojoyo University
MATEC Web of Conferences | Year: 2016

Since the nineties, companies have started to recognize the relevance of integrating sustainability in their corporate strategies. However, despite this increasing awareness, integrating sustainability in corporate strategy remains a challenge for many organisations due to the need of dealing with a wide range of issues. This research discusses more about the sustainable strategies selection in a SME and develops a model based on integrated multicriteria decision making (MCDM) methods to solve such problems. The developed model applies Entropy weighting method and Vikor algorithm to effectively analyze the weight of each sustainability criteria and to select the best sustainable strategies while capturing all subjective and objective criteria. A case study is illustrated to test the proposed model in a Batik SME. Results show that profits and facility requirements are the two most important criteria in sustainable strategies selection. This implies that during sustainable strategies selection, it is suggested that emphasis should be placed on revenue generation and facilities needed of the respective strategies. © Owned by the authors, published by EDP Sciences, 2016.


Muntasa A.,Trunojoyo University
Telkomnika (Telecommunication Computing Electronics and Control) | Year: 2014

Biometric researches have been interesting field for many researches included facial recognition. Crucial process of facial recognition is feature extraction. One Dimensional Linear Discriminant Analysis is one of feature extraction method is development of Principal Component Analysis mostly used by researches. But, it has limitation, it can efficiently work when number of training sets greater or equal than number of dimensions of image training set. This limitation has been overcome by using Two Dimensional Linear Discriminant Analysis. However, search value of matrix identity R and L by using Two Dimensional Linear Discriminant Analysis takes high cost, which is O(n3). In this research, the seeking of "Scatter between Class" and "Scatter within Class" by using Discriminant Analysis without having to find the value of R and L advance are proposed. Time complexity of proposed method is O(n2). Proposed method has been tested by using AT&T face image database. The experimental results show that maximum recognition rate of proposed method is 100%.


Muntasa A.,Trunojoyo University
International Review on Computers and Software | Year: 2015

In this research, the square diagonal matrix based on Two-Dimensional Linear Discriminant Analysis for Face recognition is proposed. The original image matrix is converted into the diagonal matrix and followed the same process by using the output become input. The results of the conversion are utilized as input on feature extraction using Two-Dimensional Linear Discriminant Analysis. The proposed method has been evaluated by using the YALE-A, the ORL and the University of Bern Face image databases. The experimental results show that, the proposed method outperformed to other methods, which are Eigen Faces, Fisher Faces, Laplacian Faces and Orthogonal Laplacian Faces methods. The highest recognition rates are 89.523%, 97% and 95.33% for the YALE-A, the ORL, and the University of Bern respectively. The usage of the dominant features has influenced the results of the recognition. It is proved that, the more the dominant features, the smaller error occurred. © 2015 Praise Worthy Prize S.r.l. - All rights reserved.


Fuad M.,Trunojoyo University
ICAMIMIA 2015 - International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, Proceeding - In conjunction with Industrial Mechatronics and Automation Exhibition, IMAE | Year: 2015

The key aspect to control the motion of manipulator intuitively is ability to map both joints on human and machine. This research proposes a method to interact with arm robot by using gesture based on skeleton image of user that is read from Kinect sensor. Velocity of each joint is defined by measuring angle rotation of every bone with respect to previous linked bone. Experiments has been carried out to manipulate SCORBOT-ER 9Pro with ability to handle 4 of 5 axises. © 2015 IEEE.

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