Rahmat Hidayat

Combination Base64 Algorithm and EOF Technique for Steganography

The steganography process combines mathematics and computer science. Steganography consists of a set of methods and techniques to embed the data into another media so that the contents are unreadable to anyone who does not have the authority to read these data. The main objective of the use of base64 method is to convert any file in order to achieve privacy. This paper discusses a steganography and encoding method using base64, which is a set of encoding schemes that convert the same binary data to the form of a series of ASCII code. Also, the EoF technique is used to embed encoding text performed by Base64. As an example, for the mechanisms a file is used to represent the texts, and by using the two methods together will increase the security level for protecting the data, this research aims to secure many types of files in a particular media with a good security and not to damage the stored files and coverage media that used.

Analysis of Student Satisfaction Toward Quality of Service Facility

The development of higher education is very rapid rise to the tight competition both public universities and private colleges. XYZ University realized to win the competition, required continuous quality improvement, including the quality of existing service facilities. Amenities quality services is believed to support the success of the learning activities and improve user satisfaction. This study aims to determine the extent to which the quality of the services effect on user satisfaction. The research method used is survey-based questionnaire that measure perception and expectation. The results showed a gap between perception and expectations of the respondents have a negative value for each item. This means XYZ service facility at the university is not currently meet the expectations of society members. Three service facility that has the lowest index is based on the perception of respondents is a laboratory (2.56), computer and multimedia (2.63) as well as wifi network (2.99). The magnitude of the correlation between satisfaction with the quality of service facilities is 0.725 which means a strong and positive relationship. The influence of the quality of service facilities to the satisfaction of the students is 0.525 meaning that the variable quality of the services facility can explain 52.5% of the variable satisfaction. The study provided recommendations for improvements to enhance the quality of services facility at the XYZ university facilities.

Modeling Data Containing Outliers using ARIMA Additive Outlier (ARIMA-AO)

The aim this study is discussed on the detection and correction of data containing the additive outlier (AO) on the model ARIMA (p, d, q). The process of detection and correction of data using an iterative procedure popularized by Box, Jenkins, and Reinsel (1994). By using this method we obtained an ARIMA models were fit to the data containing AO, this model is added to the original model of ARIMA coefficients obtained from the iteration process using regression methods. This shows that there is an improvement of forecasting error rate data.

IOWA Unemployment Insurance Claimants: A Comparison between α-Sutte Indicator and Other Forecasting Methods

This UI program if it isn’t managed well so that can affect the insurance company performance and can make the company loss. One of the ways to know the development of this insurance claim for each month is that by forecasting the people who are interested in this insurance. The aim of this study is forecasting unemployment insurance claimants in IOWA, USA. This research uses ARIMA, NNETAR, Robus Exponensial Smooting, Theta Model, and α-Sutte Indicator forecasting method. The use of this method is intended to be compared the level of accuracy from various forecasting methods. To see the quality of the forecast, so that it will be used a comparison based on MSE score. The lower MSE Score, the better accuracy level that they have. The result of this study is α-Sutte Indicator is more appropriate in forecasting data unemployment insurance claim in IOWA. The accuracy level of α-Sutte Indicator is better if it is compared to any other methods.

Technology of Web GIS and Mobile GIS for Airport Business Area Development

Indonesia has 296 airports officially managed by the government, covering 13 airports managed by PT Angkasa Pura I, 13 airports are managed by PT Angkasa Pura II, 53 airports are managed by the National Army (TNI), 178 airports are managed by Airport Operator Unit of the Ministry of Transportation and lastly, 39 airports are managed by UPT Local Government. Using technology of web GIS and mobile GIS for airport business area development, help User in determining the airport in Indonesia that have the potential based on the local APBD and the local PDRB, in airport area and the potential of local business area development, more flexible and timely, that is real-time and provide easy-to-use information, can be visualized by mapping thematic, labeling, symbolizing, querying and preparing summary reports. Keywords—web GIS; mobile GIS; airport business area

Analysis of Technology Acceptance Model (TAM) on E-Learning System

Advances in science and technology, especially Information and Communication Technology (ICT) more positive impact for the advancement of education today. Various advantages of e-learning to encourage the use of e-learning has become a necessity these days is no longer a necessity or compulsion. Utilization of e-learning in the learning process was already inevitable. This study aims to find a picture of the successful implementation of e-learning based on user acceptance within the University XYZ.. User acceptance can predict the level of utilization of the technology in the future. The method used in Copyright

Using K-Means Clustering to Cluster Provinces in Indonesia

K-Means Clustering (KMC) is a technique used in performing data groupings. The data classification procedure is based on the degree of membership of each member. The purpose of this study is to group the existing Provinces in Indonesia based on Population Density, School Participation Rate, Human Development Index, and Open Unemployment Rate using K-Means Clustering. The result reveals 5 large clusters in each center in South Sumatra, Lampung, DKI Jakarta, Central Java, and West Kalimantan.

eConf: an Information System to Manage the Conference

Along with the development of times, there is a growing need for internet among the society. This is not limited to the world of education, somehow. In the world of education, especially higher education, if a lecturer wants to increase his/her rank, he/she needs some publications either in the form of journals, books, or seminar proceedings. One of publications a lecturer commonly does is a seminar both national and international seminars. In conducting the seminar registration, it requires an information system that can accommodate the registrants data. Therefore, the purpose of this study is to design a web-based conference information system (eConf). This information system was developed using SDLC (System Development Life Cycle) method.