Bens Pardamean

Lightweight Virtualization in Cloud Computing for Research

With the advancement of information technology and the wide adoption of the Internet, cloud computing has become one of the choices for researchers to develop their applications. Cloud computing has many advantages, particularly the ability to allocate on-demand resources without the need to build a specialized infrastructure or perform major maintenance. However, one of the problems faced by the researcher is the availability of computer tools to perform research. Docker is a lightweight virtualization for developers that can be used to build, ship, and run a range of distributed applications. This paper describes how Docker is deployed within a platform for bioinformatics computing.

EXPERT-SYSTEM BASED MEDICAL STROKE PREVENTION

Stroke always comes unexpected and the general public is not usually aware of its symptoms. Individual s who have had their first stroke with permanent dama ge could become an economic burden to their family and a social burden to the society due to their unp roductive nature. Stroke could be prevented and its risk factors have been identified. Through a stroke prev ention information system, the user could be made more aware of stroke risks and symptoms. An expert syste m would be able to direct and motivate users to kee p themselves healthy therefore preventing first and r ecurrent strokes. The expert system is built using an inference engine that provides stroke risk level ba sed on information provided by the user. Informatio n collected are self measured blood pressure, cigaret tes consumed, amount of physical activity and body mass index. Users are presented with suggested preventiv e tasks to reduce their stroke risk.

Model of Human Resources for Health Information Systems

One of the crucial aspects of health development is human resources due to its role in both management and implementation of the health care system. The implication of this situation is the need for proper information and data collection. Human Resources for Health Information System (HRHIS) works as a tool in collecting such information. The fragmented business process posed a substantial challenge towards any effort in integrating HRHIS with Health Information System (HIS) Data Bank. However, through the simultaneous utilization of Service Oriented Architecture (SOA) method for model integration, Health Level Seven (HL 7) for standard data exchange, and Extensible Markup Language (XML) for standard data formatting, this study managed to construct a system model that integrated HRHIS with HIS Data Bank. The model was created subsequently enable the accuracy of HRHIS information.

SCHOOL INFORMATION SYSTEMS DESIGN FOR MOBILE PHONES

School Information System (SIS) is an academic information system developed and implemented for a private school with a purpose to improve the effici ency of information retrieval for students, parents and school authority. One of the initial problems with SIS implementation was that it depended on the availability of computers and internet access. With slow internet connections, authentication process could be time consuming, especially if a website implements various external scripts to improve visual quali ty. Due to these reasons, as well as the fact that Blac kBerry is one of the most popular smartphones in Indonesia, the developers decided to design a simpl er but more powerful system that would resolve Blackberry Mobile SIS problems. The mobile SIS was designed, implemented and evaluated to provide a perfect solution for problems related to ease-of-ac cess. The Mobile SIS facilitates students and paren ts in obtaining academic information anytime, anywhere and without the need for repeated authentication, via BlackBerry mobile connection. Mobile SIS also offers faster loading time relative to traditional websi te access. Using the push technology service, SIS coul d now provide students and parents in getting the l atest information every time new information gets dissemi nated.

Cloud Computing for Genome-Wide Association Analysis

With the increasing availability and affordability of genome-wide genotyping and sequencing technologies, biomedical researchers are faced with increasing computational challenges in managing and analyzing large quantities of genetic data. Previously, this data intensive research required computing and personnel resources accessible only to large institutions. Cloud computing allows researchers to analyze their data without a local computing infrastructure. We evaluated the feasibility of cloud computing for association analysis of genome-wide data. Our approach utilized the MapReduce model which divides the analysis into independent units and distributes the work to a computing cloud. We evaluated our approach by modeling the relationships between genetic variants and disease in a simulated genome-wide association study. We generated several data sets of 100,000 subjects and various number of genetic variants, and demonstrated that our analysis approach is scalable and provides an attractive alternative to establishing and maintaining a local computing cluster.

Hybrid support vector regression in electric load during national holiday season

This paper studies non-parametric time-series approach to electric load in national holiday seasons based on historical hourly data in state electric company of Indonesia consisting of historical data of the Northern Sumatera also South and Central Sumatra electricity load. Given a baseline for forecasting performance, we apply our hybrid models and computation platform with combining parameter of the kernel. To facilitate comparison to results of our analysis, we highlighted the results around MAPE-based and R2-based techniques. In order to get more accurate results, we need to improve, investigate, also develop the appropriate statistical tools. Electric load forecasting is a fundamental aspect of infrastructure development decisions and can reduce the energy usage of the nation.

A Bayesian hierarchical model for identifying significant polygenic effects while controlling for confounding and repeated measures

Abstract Genomic studies of plants often seek to identify genetic factors associated with desirable traits. The process of evaluating genetic markers one by one (i.e. a marginal analysis) may not identify important polygenic and environmental effects. Further, confounding due to growing conditions/factors and genetic similarities among plant varieties may influence conclusions. When developing new plant varieties to optimize yield or thrive in future adverse conditions (e.g. flood, drought), scientists seek a complete understanding of how the factors influence desirable traits. Motivated by a study design that measures rice yield across different seasons, fields, and plant varieties in Indonesia, we develop a regression method that identifies significant genomic factors, while simultaneously controlling for field factors and genetic similarities in the plant varieties. Our approach develops a Bayesian maximum a posteriori probability (MAP) estimator under a generalized double Pareto shrinkage prior. Through a hierarchical representation of the proposed model, a novel and computationally efficient expectation-maximization (EM) algorithm is developed for variable selection and estimation. The performance of the proposed approach is demonstrated through simulation and is used to analyze rice yields from a pilot study conducted by the Indonesian Center for Rice Research.

The Implementation of Online Learning for Early Detection of Cervical Cancer

Cervical cancer is the second leading type of cancer causing death among women in Indonesia. The mortality rate caused by cervical cancer could be reduced through an early detection program, which would require the training of healthcare workers in educating women in Indonesia. The aim of this study was to develop an online learning management system prototype that is suitable for educating both the public and medical personnel about early detection of cancer based on model of previous study result. The research method utilized the Analysis, Design, Development, Implementation, Evaluation (ADDIE) framework as an approach of System Development Life Cycle (SDLC). The study produced an online Learning Management System (LMS) to assist in the efforts of early detection of cervical cancer.

The development of blended-learning teaching portfolio course using TBL approach

Thisarticlewaswrittentodevelopateachingportfoliothathelpslecturersmaximizethebenefitsof blendedlearning,acombinationofin-personandonlinelearning,throughtheuseofTeam-Based Learning(TBL)teachingandlearningapproach.StudiesshowthatTBLcanprovideopportunitiesin developingteamworkcapabilitiesandenhancingactivelearning,whichareeffectsthatcouldremedy theweaknessesofimplementingblendedlearning.Ablendedteachingportfoliowasdevelopedfor anInternationalHumanResourceManagementcoursethatconsistedofacourseoverview,graduate competency,a syllabus, coursematerial resources, a teachingscenario, a readingassurance test, midterm/finalexams,studentassignments,assessmentoflearningoutcomes,andacoursequality improvementsheet.Eachitemwasconstructedbasedonthecharacteristicsofthecourse.Theportfolio wasconsideredavaluabletoolforlecturerstomanageablended-learningcoursethatcanhelpstudents inachievinghigherscoresandinmotivatingthemtoreadcoursematerialspriortoclasssessions. KEywoRDS E-learning, Face to Face, In Person, Learning Management System, Online Learning, Readiness Assurance Process, Syllabus, Team Based Learning

Changing colorectal cancer trends in Asians.

Dear Editor: Colorectal cancer represents one of the leading causes of cancer mortality worldwide. Rapid changes in socioeconomic and lifestyle habits in many Asian countries may be contributing to the notable increase in the incidence of colon and rectal cancers. Recently, significant progress has been made in understanding genetic susceptibility to colorectal cancer and gene–environment interactions, although limited studies are focused on Asians and generalizability across diverse Asian subpopulations are still needed. Furthermore, given varying health care resources and stages of economic development in different countries, the optimal population-based screening strategy remains an active area of discussion throughout Asia. Summarized here is a description of the changes in risk factors for colorectal cancer among Asian populations and some approaches to screening and early detection that have been considered across various countries in the region.