Operations Research, Mathematics, Computer Science and Statistics: The Relationships

Many people have difficulty in seeing any difference between Mathematics, Operations Research, Statistics, Computer Science and other disciplines while others are just plain confused. In this work, OR and its applications are being exposed and then compared in order to look into the relationships between OR, Mathematics, Computer Science, Statistics and other fields. It has been realized that all these areas of knowledge are also interrelated with other areas such as Engineering, Physics, Microbiology, Economics etc.

The Analysis Knowledge Management System Of Electronic Government South Tangerang Based On Usability Evaluation Using SUMI (Software Usability Measurement Inventory)

E-Government performance in the application of quality management information communication technology is very necessary. A website-based system is also used to improve the quality of services and community participation in development. The context that becomes the material that needs to be examined is public service, the quality of websites managed by the government and user satisfaction so that there is a two-way interaction between the government and the community. The purpose of this study consisted of three stages which were first to determine the role of E-government by utilizing technology to support the development of a reliable information system in South Tangerang Regency. The second is to find out the extent to which the system is used in South Tangerang E-government through Usability Evaluation using SUMI (Software Usability Measurement Inventory). The method used in this study is a method adopted from the Knowledge Management System Life Cycle. The stages of the method are Evaluate Existing Infrastructure, Form The KM Team, Knowledge Capture, Implement the KM system. The results of this study are in the form of usability values on the E-Government website of South Tangerang and usability testing which becomes a benchmark for the success of a system with score scores for 85 effectiveness categories, 81.5

Improving KNN by Gases Brownian Motion Optimization Algorithm to Breast Cancer Detection

In the last decade, the application of information technology and artificial intelligence algorithms are widely developed in collecting information of cancer patients and detecting them based on proposing various detection algorithms. The K-Nearest-Neighbor classification algorithm (KNN) is one of the most popular of detection algorithms, which has two challenges in determining the value of k and the volume of computations proportional to the size of the data and sample selected for training. In this paper, the Gaussian Brownian Motion Optimization (GBMO) algorithm is utilized for improving the KNN performance to breast cancer detection. To achieve to this aim, each gas molecule contains the information such as a selected subset of features to apply the KNN and k value. The GBMO has lower time-complexity order than other algorithms and has also been observed to perform better than other optimization algorithms in other applications. The algorithm and three well-known meta-heuristic algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Imperialist Competitive Algorithm (ICA) have been implemented on five benchmark functions and compared the obtained results. The GBMO+KNN performed on three benchmark datasets of breast cancer from UCI and the obtained results are compared with other existing cancer detection algorithms. These comparisons show significantly improves this classification accuracy with the proposed detection algorithm.

Evaluation of a Proposed Road in a Campus Network based on Ideal Flow

A proposed road project inside a campus that will have to down trees from its mini forest have attracted different public opinion among the faculty and students. In this paper, we would like to justify our view objectively based on transportation engineering point of view. The Ideal Flow Network (IFN) method was used to do the analysis because its source code is publicly available for clarification. The network data is based on previous study of Ateneo Traffic Group report. Two scenarios were set: based scenario that represents the current road network, and two proposed scenario that represents the current road network with additional proposed road in two ways and one way respectively. Analysis of the results show that the total network travel time of the proposed scenario are increased by 4.69% and 2.32% respectively for two ways and one-way scenarios. The network speed will be slightly improved by 0.03% in when the proposed road project is added in two ways. Thus, we failed to justify that the proposed network has better network performance.

Samawa Part of Speech Tagging using Brill Tagger

There exist 7,097 living languages in the world cited by Ethnologue. Most of them, however, do not exist on the Internet as the objects of research. It indicates the gap in language resources. One of them is Samawa language which has over 500,000 native speakers and is identified as endangered language by UNESCO. What we known about Samawa so far is a lack of information, tools, and resources to maintain its sustainability. This paper aims to contribute to NLP, a growing field of research, by exploring Samawa part of speech tagging problem using rule-based approach, i.e. Brill tagger. It has been trained on very limited data of Samawa corpus, which is 24,627 tokens including punctuation marks with 24 tags of our original tagset. K-fold cross-validation (k = 5 and k = 10) was applied to compare Brill’s performance with Unigram, HMM, and TnT. Brill tagger with the combination of default tagger, Unigram, Bigram and Trigram as baseline tagger achieve higher accuracy over 95% than others. It suggests that the Brill tagger can be used to extend Samawa corpus automatically.

Randomness of Poisson Distributed Random Number in the Queue System

In the queuing system, inter arrival variable and service time variable are probabilistic and its pattern follow a Poisson distribution. Simulations experiment for performance measurement of a queuing system required random data. In practice, random data is built using an application program. Pseudorandom data generated from application programs often have different patterns of randomness, although in each experiment simulated the same data distribution. Level of randomness may cause the results of simulation experiments experienced statistically significant deviations, especially on problems with stochastic variables. Statistical deviation can cause errors in interpreting the results of simulation experiments, especially in the assessment of the performance of the queuing system. It is required to evaluate whether the level of randomness of pseudorandom data effect on simulation results of performance measurement of a system. Simulation experiments on a simple queuing system (M / M / 1) was carried out by using a pseudorandom number generator. Application program used to generate pseudorandom numbers is Fortran90. The experimental results show that the greater the amount of pseudorandom data, the greater the statistical deviations occur, and the smaller the degree of randomness of data. This affects the results of the simulation system in which there is a probabilistic variable that require random data to conduct simulation

Usability Engineering and Evaluation of Usability In District Tourism And Culture Information Systems

So far, the potential of natural resources has not been fully managed by the government or the community. For that we need a mature tourist object planning either by visitors or by developers. Communities need information provided on a mobile basis that can be accessed anywhere. This information is inseparable from the role of technology that supports so that applications can be used by tourists who want to visit either in the form of an address or location. Applications that are worthy of use are applications that have been tested usefulness or called usability. To test a system requires a questionnaire which one of them is SUMI (Software Usability Measurement Inventory). This study uses a method adopted from usability engineering lifecycle. The results of this study in the form of assessment with several criteria, so the application is feasible to use.

Data Security Using Multi-bit LSB and Modified Vernam Cipher

Data security is one of the most important aspects of today's information era. Some methods are used to secure important data from hackers. The LSB is a steganographic algorithm that is often used to store data in the last bit. In order to improve the security, we combine steganography with cryptography enables. In this research LSB is modified using the multi-bit LSB model. Modifications are made to the bits of each character, the rotation by a certain amount can randomize the plaintext content before cryptographic algorithm, Vernam is performed. The bit on LSB can be inserted data as much as 1, 2, 3 or 4 - bit information. The calculation results of MSE and PSNR values indicate that the use of 1-bit LSB is superior to that of 2-, 3-, or 4-bit LSB.

Study of Scheduling in Programming Languages of Multi-Core Processor

Over the recent decades, the nature of multi core processors caused changing the serial programming model to parallel mode. There are several programming languages for the parallel multi core processors and processors with different architectures that these languages have faced programmers to challenges to achieve higher performance. In additional, different scheduling methods in the programming languages for the multi core processors have significant impact on efficiency of the programming languages. Therefore, this article addresses the investigation of the conventional scheduling techniques in the programming languages of multi core processors which allows researcher to choose more suitable programing languages by comparing efficiency than application. Several languages such as Cilk++، OpenMP، TBB and PThread were studied and their scheduling efficiency has been investigated by running Quick-Sort and Merge-Sort algorithms as well

A Two Microphone-Based Approach for Detecting and Identifying Speech Sounds in Hearing Support System

For people with hearing disabilities, not only would give them difficulties in going through their everyday lives but also sometimes could be life threatening. In this research we proposed a simple, yet robust approach for helping the hearing-impaired people in identifying the important sounds around them by using two microphones as input channel that could be worn around the person’s head as a substitute for their ears. This device then could be used to record the situation of the surroundings, and then the system would estimate the Direction of Arrival (DOA) of the sound sources, then detect and classify them using Support Vector Machine (SVM) into target speech or noise category. As the results, system’s classifier could produce FAR and FRR as low as 2%, in which 274 out of 280 samples were successfully classified as target speeches and 22 from the total of 27 noise samples were successfully classified as noise