Computer-based Data Processing Research Articles

Multiuser Based Savings And Loans Information System

The increasingly rapid development of computer technology provides convenience for humans in carrying out life activities, this has resulted in the use of computers being an alternative taken by various agencies because it is considered to provide more advantages than disadvantages. Computers are tools to improve performance in various fields. In solving data processing problems at the KSU " DANA MANDIRI " Cooperative, based on the survey carried out, the author tried to change the manual or conventional data processing program into a computer-based data processing program, namely by using the Visual Foxpro 9.0 program. This change aims to provide comfort for operators in carrying out their work. With old programs, conventionally inputting data still takes a long time and when searching for data you still have to look for codes one by one because it cannot be done automatically. With these problems the author tries to formulate the problem, namely "How to make a data processing program to save borrow at KSU " DANA MANDIRI " using the Visual Foxpro 9.0 programming language. The savings and loan data processing process can be accessed quickly and precisely and provides a more attractive appearance. In solving this problem the author tried to collect data related to savings and loan data. In designing a new system, several stages are carried out including data design. Table creation, ERD creation, DFD and normalization. In processing the savings and loan data, it is hoped that it can help with problems that arise at the KSU " DANA MANDIRI " Cooperative and the program created of course still has several weaknesses and shortcomings, this is possible because the author still has little knowledge and experience in programming issues. Suggestions and criticism really help the author to further develop knowledge in this field.

Sistem Informasi Data Pemantauan Wilayah Setempat Kesehatan Ibu Dan Anak ( KIA)

Computer-based data processing has developed greatly. In health institutions such as community health centers, the role of information technology can no longer be separated. Almost all community health centers currently implement computer-based systems to manage health-related data, such as maternal and child health (KIA). With a computerized system, we can provide good and fast service and present information effectively and efficiently. This requires the ability of human resources to master and follow developments in science and technology; the development of science is always followed by technological advances which are needed in data processing, namely by using computer tools and programs, data processing will be carried out well and the results Perfect.

A Topic Modeling and Sentiment Analysis Model for Detection and Visualization of Themes in Literary Texts

Despite the growing emergence of new computer analytic software programs, the adoption and application of computer-based data mining and processing methods remain sparse in literary studies and analyses. This study proposes a text analytics lifecycle to detect and visualize the prevailing themes in a corpus of literary texts. Two objectives are to be pursued: First, the study seeks to apply a Topic Modeling approach with selected algorithms of LDA, LSI, NMF, and HDP that can effectively detect the recurring topics about the major themes developed in the dataset. Second, the project aims to apply a Sentiment Analysis model that can analyze the polarity of writers’ discourse on the detected thematic topics with the algorithms of Vader and TextBlob. The implementation of Topic Modeling has detected six thematic topics of sex, family, revolution, imprisonment, intellectual, and death. The adoption of the Sentiment Analysis model also revealed that the feelings attached to all the identified themes are largely negative sentiments expressed towards socio-political issues.

PENERAPAN DATA MINING PEMASARAN PRODUK MENGGUNAKAN METODE CLUSTERING

This study aims to build a data mining application that is able to classify products marketed by companies to find out the products needed for the following month. This application groups non-hierarchical data which is designed to divide existing data into two or more groups so that the same data can be entered into other groups. In this study, the data used is data from PT Cipta Niaga Semesta Mayora Group and the method used is clustering. Data mining is computer-based data processing to gain knowledge. By using data mining, processing sales data at PT Cipta Niaga Semesta Mayora Group becomes easier and gains useful knowledge to take steps to face competition. For this reason, the company's management foresight is needed in choosing technology to help work so that the costs incurred are proportional to the company's opinion. The development of this framework is completed through several stages starting with the first data collection, followed by the second stage of application design, the third stage of the four stages of program development and program implementation. Using data mining applications can help PT Cipta Niaga Semesta categorize the products it sells so that the company can predict the product inventory needed for the following month. So with the new information the company can find out what products customers want.

Cwepr – A Python package for analysing cw-EPR data focussing on reproducibility and simple usage

Reproducibility is at the heart of science. Nevertheless, with the advent of computer-based data processing and analysis, most spectroscopists have a hard time fully reproducing a figure from last year’s publication starting from the raw data. Unfortunately, this renders their work eventually unscientific. To change this, we need to develop analysis tools that relieve their users from having to trace each processing and analysis step. Furthermore, these tools need to be modular, extendible, and easy to use in order to get used. To this end, we present here the open-source Python package cwepr based on the ASpecD framework for reproducible analysis of spectroscopic data. This package follows best practices of both, science and software development. Key features include an automatically generated gap-less record of each individual processing and analysis step from the raw data to the final published figure. Additionally, it provides a powerful user interface requiring no programming skills of the user. Due to its code quality, modularity, and extensive documentation, it can be easily extended and is actively developed by spectroscopists working in the field. We expect this approach to have a high impact in the field and to help fighting the looming reproducibility crisis in spectroscopy.

Sistem Informasi Perpustakaan Berbasis website

School libraries must be built and developed properly in order to provide a service to students, library admins, and leaders in finding a book reference. This information service can also be done well and can be seen in the ease of members to get accurate and fast information, so from changing the form of data processing that is still manual to computer-based data processing is one of the innovations to overcome delays in information and difficulty processing detailed data collection of existing books. The Diponegoro Majenang Middle School library is still using the manual method, there is no website or application program that can process class data, member data, loan and return transactions, loan transaction reports, returns and late returns. is due on the due date for returning to the library. The method used in making this website-based library information system is the waterfall method which consists of several stages, namely Analysis, Design, Coding, Testing and Maintenance. With the development of data communication technology, school library information systems can be built as a means of online library information systems (website-based).

SISTEM INFORMASI PENGOLAHAN DATA PASIEN PADA PUSKESMAS TENAM MUARA BULIAN

Pusat Kesehatan Masyarakat (Puskesmas) is a provider of public health services to always provide fast, precise and accurate health services. Pusat Kesehatan Masyarakat (Puskesmas) have the main function to provide medical services in the form of perfect care and treatment to the community Data processing is a function of administrative activities used by agencies or offices to provide information services to organizations to deal with many managements. This health center is the object of this research, because at this time the patient data processing system is still manual, this is due to the absence of an integrated data processing system and mechanism and the limited facilities and infrastructure of information services that are produced not as expected. The author tries to find a solution to the problem in processing this data by implementing a computer-based data processing system

A Novel Preprocessing Method for Dynamic Point-Cloud Compression

Computer-based data processing capabilities have evolved to handle a lot of information. As such, the complexity of three-dimensional (3D) models (e.g., animations or real-time voxels) containing large volumes of information has increased exponentially. This rapid increase in complexity has led to problems with recording and transmission. In this study, we propose a method of efficiently managing and compressing animation information stored in the 3D point-clouds sequence. A compressed point-cloud is created by reconfiguring the points based on their voxels. Compared with the original point-cloud, noise caused by errors is removed, and a preprocessing procedure that achieves high performance in a redundant processing algorithm is proposed. The results of experiments and rendering demonstrate an average file-size reduction of 40% using the proposed algorithm. Moreover, 13% of the over-lap data are extracted and removed, and the file size is further reduced.

Design of cost-efficient Glucose meter

A blood glucose metre is a small, portable device that measures blood glucose levels. To avoid long-term complications from diabetes, careful blood glucose control is required. New blood glucose metres have a small size, a large memory capacity, blood glucose manipulation techniques, and computer-based data processing capabilities.The Glucose Detection System is implemented in tandem with an improved Op-based Potentiostat and an automatic test system. This project's goal is to investigate an improved OP-based Three-Electrode Potentiostat that can be used in an Electrochemical Glucose Biosensor device to achieve comparable measurement accuracy. This Project enables us to make the Glucometer Cost-Efficient, Affordable and Easy to Use. They hold a lot of promise in the field of bio-detection on the go systems for use in health care and biomedicine.

Pelatihan Pengolahan Data Berbasis Komputer Bagi Peneliti Pemula

Based on the observations we conducted on the students, it can be concluded that most students faced difficulties in processing research data to complete the thesis. This was due to the lack of students' understanding of research methodology and statistics as well as the students’ minimum ability to use the help of a data processing application in a computer, such as SPSS. Based on this problem, we took an initiative to carry out a community service program specifically for students who were conducting research with the theme "Computer-based Data Processing Training for Novice Researchers". The target of this activity was the final year students of STAIN BENGKALIS who were in the process of completing a thesis. The ultimate goal of this activity is: a) To improve the students' understanding of statistical science. b) To improve the students' data processing ability in using one of the research data processing software, especially SPSS.

‘Just playing around with Excel and pivot tables’ - the realities of data-driven schooling

ABSTRACT Schools now face considerable pressure to be using educational data to inform decision-making and become more efficient. Key to this rise of the ‘data-driven’ school is the increased use of digital technologies – with computer-based data processing fuelling hopes for the technology-driven ‘smart schooling’ and a general ‘datafication’ of education. Against this background, the present paper explores the realities how data-work is taking place within individual schools with the aid of digital technologies. In particular, it draws on empirical data generated from in-depth ethnographic studies of digital data practices within three secondary schools in the Australian state of Victoria. Using concepts from the sociology of numbers, the paper takers these empirical findings to develop productive and relational accounts of the predominant ways that data work was being carried out within these schools. In contrast to the idea of ‘Big Data’, schools were most often found to be engaging in small-scale, improvised forms of spreadsheet work. The paper considers the social, cultural and political reasons underpinning schools’ reliance on such forms of ‘small data’ – particularly in contrast to the more sophisticated, automated and continuous forms of data analysis that are now available.

Abbreviation Detection in Vietnamese Clinical Texts

Abbreviations have been widely used in clinical notes because generating clinical notes often takes place under high pressure with lack of writing time and medical record simplification. Those abbreviations limit the clarity and understanding of the records and greatly affect all the computer-based data processing tasks. In this paper, we propose a solution to the abbreviation identification task on clinical notes in a practical context where a few clinical notes have been labeled while so many clinical notes need to be labeled. Our solution is defined with a semi-supervised learning approach that uses level-wise feature engineering to construct an abbreviation identifier, from using a small set of labeled clinical texts and exploiting a larger set of unlabeled clinical texts. A semi-supervised learning algorithm, Semi-RF, and its advanced adaptive version, Weighted Semi-RF, are proposed in the self-training framework using random forest models and Tri-training. Weighted Semi-RF is different from Semi-RF as equipped with a new weighting scheme via adaptation on the current labeled data set. The proposed semi-supervised learning algorithms are practical with parameter-free settings to build an effective abbreviation identifier for identifying abbreviations automatically in clinical texts. Their effectiveness is confirmed with the better Precision and F-measure values from various experiments on real Vietnamese clinical notes. Compared to the existing solutions, our solution is novel for automatic abbreviation identification in clinical notes. Its results can lay the basis for determining the full form of each correctly identified abbreviation and then enhance the readability of the records.
 Keywords: Electronic medical record, Clinical note, Abbreviation identification, Semi-supervised learning, 
 Self-training, Random forest.

Best practice data life cycle approaches for the life sciences

Throughout history, the life sciences have been revolutionised by technological advances; in our era this is manifested by advances in instrumentation for data generation, and consequently researchers now routinely handle large amounts of heterogeneous data in digital formats. The simultaneous transitions towards biology as a data science and towards a ‘life cycle’ view of research data pose new challenges. Researchers face a bewildering landscape of data management requirements, recommendations and regulations, without necessarily being able to access data management training or possessing a clear understanding of practical approaches that can assist in data management in their particular research domain. Here we provide an overview of best practice data life cycle approaches for researchers in the life sciences/bioinformatics space with a particular focus on ‘omics’ datasets and computer-based data processing and analysis. We discuss the different stages of the data life cycle and provide practical suggestions for useful tools and resources to improve data management practices.

Machine intelligence: a chimera

The notion of computation has changed the world more than any previous expressions of knowledge. However, as know-how in its particular algorithmic embodiment, computation is closed to meaning. Therefore, computer-based data processing can only mimic life’s creative aspects, without being creative itself. AI’s current record of accomplishments shows that it automates tasks associated with intelligence, without being intelligent itself. Mistaking the abstract (computation) for the concrete (computer) has led to the religion of “everything is an output of computation”—even the humankind that conceived the computer. The hypostatized role of computers explains the increased dependence on them. The convergence machine called deep learning is only the most recent form through which the deterministic theology of the machine claims more than what it actually is: extremely effective data processing. A proper understanding of complexity, as well as the need to distinguish between the reactive nature of the artificial and the anticipatory nature of the living are suggested as practical responses to the challenges posed by machine theology.

One hundred years of cross-country mobility prediction in Germany

AbstractThe potential for cross-country mobility (CCM) by vehicles has increasingly become an integral part of tactical planning for military operations and depends on a multitude of parameters. A comprehensive trafficability forecast requires the analysis of terrain, including slope, land cover and soil properties, and weather, as well as specific vehicle parameters. Terrain and weather interactions were recognized as important for the first time during World War I, when all types of vehicle would frequently bog down in muddy ground. The lessons learned influenced the orientation of future German military geology. During World War II, German military geologists and engineers prepared their first CCM maps. However, these often lacked a consistent format and standardized analysis. During the Cold War, the US Army carried out extensive research to create empirical mobility models based on physical properties and trafficability tests. These results were incorporated into the production of CCM maps. Present day computer-based data processing and analysis have opened up the possibility of enhancements to trafficability forecasting and thus make a vital contribution to providing the armed forces with advice on exercises and operations.

Best practice data life cycle approaches for the life sciences

Throughout history, the life sciences have been revolutionised by technological advances; in our era this is manifested by advances in instrumentation for data generation, and consequently researchers now routinely handle large amounts of heterogeneous data in digital formats. The simultaneous transitions towards biology as a data science and towards a ‘life cycle’ view of research data pose new challenges. Researchers face a bewildering landscape of data management requirements, recommendations and regulations, without necessarily being able to access data management training or possessing a clear understanding of practical approaches that can assist in data management in their particular research domain. Here we provide an overview of best practice data life cycle approaches for researchers in the life sciences/bioinformatics space with a particular focus on ‘omics’ datasets and computer-based data processing and analysis. We discuss the different stages of the data life cycle and provide practical suggestions for useful tools and resources to improve data management practices.

Analisis Penerimaan Mahasiswa Terhadap Sistem Informasi Akademik (SIAKAD) dengan Metode Technology Acceptance Model (TAM)

Computer based data processing is expected to improve user performance, but the computer was not completely accepted by individuals. STMIK AKAKOM in one of their activities applied information technology to SIAKAD that provides some features for learning activities on campus
 The analysis of SIAKAD acceptance by students using the technology acceptance model (TAM), with partial least square , is to know how the behavior of SIAKAD users as the end user? It would be related to usefulness (PU), ease of use (PEOU), attitude toward using (ATU), and behavioral intention to use (BITU).
 From the analysis of data, the results is mention that there were a positive and significant influence between the variables. Technology acceptance factors that inflict attitude to use SIAKAD by student in their learning activities is the ease of use and usefulness )

Best practice data life cycle approaches for the life sciences.

Throughout history, the life sciences have been revolutionised by technological advances; in our era this is manifested by advances in instrumentation for data generation, and consequently researchers now routinely handle large amounts of heterogeneous data in digital formats. The simultaneous transitions towards biology as a data science and towards a 'life cycle' view of research data pose new challenges. Researchers face a bewildering landscape of data management requirements, recommendations and regulations, without necessarily being able to access data management training or possessing a clear understanding of practical approaches that can assist in data management in their particular research domain. Here we provide an overview of best practice data life cycle approaches for researchers in the life sciences/bioinformatics space with a particular focus on 'omics' datasets and computer-based data processing and analysis. We discuss the different stages of the data life cycle and provide practical suggestions for useful tools and resources to improve data management practices.

A spatial filtering velocimeter for solid particle velocity measurement based on linear electrostatic sensor array

A novel spatial filtering velocimeter for solid particle velocity measurement in gas-solid flow system is presented based on a Linear Electrostatic Sensor Array (LESA) in the paper. The fundamental spatial filtering principle of the LESA is theoretically described, and a differential filter based on two LESAs is further proposed to remove the pedestal component of the output signal from the LESA. Thus solid particle velocity can be measured by determining the central frequency of the periodic output signal of the differential filter. A spatial filtering velocimeter consisting of a measurement head, seven-channel differential amplifiers and a computer-based data acquisition and processing system is designed and its performance is evaluated on a purpose-built gravity-fed particle flow rig and a belt rig, respectively. Experimental results show that the system repeatability is within ±5.4% over the velocity range of 1.72–3.91 m/s for a particle concentration range 0.011–0.163 m3/m3.

Computer-based monitoring of the polishing processes using LabView

Despite of an extensive scientific research regarding the polishing technologies of a variety of materials, the mechanisms and interactions of the single components in the process are still not fully understood. In order to facilitate the research activities in the field of polishing the usage of computer-based data acquisition and analysis is recommended. A high data rate provides the researcher an appropriate density of information which can be used to enhance the evaluation of stated hypothesis. This is normally based on various inspection methods which only take place after the processing of the sample, e.g. white light interferometry and scanning electron microscopy. A solution for further elaborating the scientific insight on the removal mechanisms and relevant interactions during the process and enhancing the process stability and reproducibility is the monitoring of the significant chemical, mechanical and thermal indicators. Therefore, a variety of sensors and measurement devices are installed and used to gather data during the process duration (e.g. pH value, conductivity, polishing work, coefficient of friction). The amount of different devices and high data rates requires a computer-based tool to realise an adequate online process monitoring. Thus, a monitoring tool based on the LabView environment was implemented which enables the researcher to use the whole opportunities of computer-based data processing. Examples of the functionality are given for the validation of the polishing behaviour of silicon nitride.