Guruh Fajar Shidik

Evaluation of Selection Policy with Various Virtual Machine Instances in Dynamic VM Consolidation for Energy Efficient at Cloud Data Centers

Various VM instances in Cloud Infrastructure provide flexibility for user to meet their computation requirements. However, this condition leads to the complex infrastructure that require numerous resources and consumes massive electricity due to the flexibility of VM instances. This paper concern in evaluate VM selection policy in Dynamic VM Consolidation. The study would evaluate our proposed method Constant Position Selection Policy (CPS) that compared with other VM Selection Policy such as Minimum Migration Time (MMT),Random Choice(RC) and Maximum Correlation (MC).Evaluation process of this study, measured the performance of Energy Consumption, SLAV, SLATAH, and PDMwith real workload trace data from PlanetLab VMs in various VM instances. Result the proposed method able to minimizing energy consumption of cloud data center in various VM instances with acceptable SLA

Multi color feature, background subtraction and time frame selection for fire detection

The importance of early fire detection can help in providing warnings and avoid disaster that led to the economic damage and loss of life. Fire detection techniques with conventional sensors have limitations, which require a long time to detect a fire, especially in a large room and cannot work in the open area. This study proposed a fire detection method, to detect the possibility of fire based on visual sensor using multi-color feature such as color, saturation, luminance, background subtraction and time frame selection for fire detection. The evaluation in this studies conducted by calculating the error rate of the fire detection.

A classification method of coconut wood quality based on Gray Level Co-occurrence matrices

Coconut tree grows rapidly in tropical region such as Indonesia. Coconut wood is used as alternative or complementary raw material for housing or making furniture. Abundant coconut trees are planted, however the utilization of coconut wood as raw material for furniture is still very rare in Indonesia. This is caused by the low quality of coconut wood, since it has not found adequate technology for the processing of coconut wood. This paper presents our experimental work on coconut wood quality classification using self-tuning MLP classifier (AutoMLP) and Support Vector Machine (SVM). For SVM classifier we used the LibSVM library, available in RapidMiner. The Gray-Level Co-occurrence Matrix (GLCM) is used to extract the texture features of coconut wood images. Experiment result shows that AutoMLP gives the best accuracy rate at 78.82%, which is slightly better than 77.06% of SVM.

Performance Enhancement of Image Clustering Using Singular Value Decomposition in Color Histogram Content-Based Image Retrieval

Abstract—This paper presents an enhancement of the performance of image clustering. K-Means has been chosen as our clustering technique. We applied Hue Saturation Value(HSV) color histogram as features to retrieve image information. Singular Value Decomposition (SVD) technique is employed to enhance the performance of image clustering by reducing features that not useful to be proceed in clustering process. We evaluated the image clustering using Recall, Precision, F-Measure and computational time. The obtained result indicates that SVD in HSV color histogram Content-Based Image Retrieval (CBIR) is promising. JCCE 2012 Vol.1(4): 317-320 ISSN: 2010-3743 DOI: 10.7763/IJCCE.2012.V1.82 http://www.ijcce.org/index.php?m=content&c=index&a=show&catid=25&id=74

Performance Analysis of Interface Bonding and Channel Bonding at Point to Point

In this research, we have done the experiment by applying interface bonding and channel bonding techniques using Point to Point topology on wireless 802 11n to achieve greater performance of network transmission compare with normal wireless link. Some of parameters are used to measure the performance of the proposed methods, such as delay, jitter, data loss rate and throughput that applied on TCP/UDP protocols. Some of experiment setup such as Different Packet Sizes and Directional Traffic Flows also conducted to measures the capability of proposed methods. The results showed that Channel Bonding has significant throughput improvement when applied at Point to Point connection used wireless 802 11n by optimizing the available bandwidth. Different result is obtained with Interface Bonding where the performance transmission is lower than normal link.