Fast Information Research Articles

User Requirements and Quality Assessment on Shoe Size and Fit Recommendation

Online shoppers often have to find reference conversion by manual method, standalone systems, asking sales agents, and browsing the internet. However, these methods that did not provide fast and seamless information on size and fit, and what more by different brands. This study was conducted to identify user requirements for shoe sizing and fitting based on standard size conversion (US, UK, Euro), brand and type. A survey (n=62) was conducted with online shoppers to determine functional and non-functional requirements for the shoe size and fit recommendation mobile application. Subsequently, a mobile application was developed based on the output, followed by 15 user satisfaction tests (n=50) to assess its quality using 9 task scenarios. An interview was then conducted to obtain richer user feedback. The analysis showed more than 90% of users evaluated the application as easy to use, had a pleasant interface, had the intention of using it, would recommend it to others, and were satisfied with the overall application. The mean analysis showed a score of 4.6, which indicates that most of the participants were satisfied with the application. The interview results suggested the application to add brand recommendations and customize features for children’s shoes. These open opportunities for future work to improve the acceptance and quality of the application. Users who wish to buy shoes online could benefit from the application by finding the right fit based on foot size, shoe brand and type easily using their smartphone.

Ergosterol and polyphenol contents as rapid indicators of orchardgrass silage safety

The ergosterol (ERG) has been proposed as a potential indicator of fungal contamination, along with polyphenol content analysis to predict silage safety. Despite efforts in controlling fungal growth in silage, mycotoxin co-contamination represents a possible risk for animal and human health. Modern analytical techniques determine a multitude of fungal metabolites contaminating feed. Nonetheless, these methods require sometimes arduous sample pre-treatment, long separation times, and expensive standard compounds to identified contaminants. Thus, the goal of this study was to suggest a rapid analysis of ERG and polyphenol contents to assess silage hygienic quality in ten orchardgrass varieties ensiled without and with biological and chemical additives. The determination of ERG on samples was performed by high-performance liquid chromatography using UV detection and UV/Vis spectrophotometry to determine the polyphenol content. Statistically significant differences (P < 0.05) between varieties, years and silage additives were found. Bepro was the unique variety that did not present ERG in the first cut in 2012. ERG content increased in the first cut in 2013 using biological additives as well as ERG and polyphenol contents in the first cut in 2013 using chemical additives compared with untreated silage. In addition, biological and chemical additives used in this study did not satisfactorily reduce the content of ERG and polyphenols in silage grass. Consequently, our results provide fast information about the progressive fungal contamination of grass silage. To our knowledge, it is the first time that the presence of ERG and polyphenols is determined in ten different orchardgrass varieties treated without and with additives. In general, ERG and polyphenol contents showed to be good indicators of orchardgrass silage safety.

Robust automated backbone triple resonance NMR assignments of proteins using Bayesian-based simulated annealing

Assignment of resonances of nuclear magnetic resonance (NMR) spectra to specific atoms within a protein remains a labor-intensive and challenging task. Automation of the assignment process often remains a bottleneck in the exploitation of solution NMR spectroscopy for the study of protein structure-dynamics-function relationships. We present an approach to the assignment of backbone triple resonance spectra of proteins. A Bayesian statistical analysis of predicted and observed chemical shifts is used in conjunction with inter-spin connectivities provided by triple resonance spectroscopy to calculate a pseudo-energy potential that drives a simulated annealing search for the most optimal set of resonance assignments. Termed Bayesian Assisted Assignments by Simulated Annealing (BARASA), a C++ program implementation is tested against systems ranging in size to over 450 amino acids including examples of intrinsically disordered proteins. BARASA is fast, robust, accommodates incomplete and incorrect information, and outperforms current algorithms – especially in cases of sparse data and is sufficiently fast to allow for real-time evaluation during data acquisition.

THE DESIGN OF ONLINE SMART APPLICATION SIRISKA (WORK RISK MAPPING SYSTEM): A STUDY OF OIL PALM HARVESTING WORKERS IN PTPN IV ADOLINA PLANTATION

Background: National Social Security Agency for Employment (BPJS Ketenagakerjaan) in North Sumatra has noted since January 2021 there were 1,272 work accident cases in North Sumatra. Work accident prevention data with a scientific approach already has adequate information, but the digitalization era 4.0 prioritizes fast availability of information, where all entities in the industrial environment are always connected and can share information with each other. By using fast information it will make it easier for decision maker to make faster decisions and control actions in work safety and health issues. Method: The type of research was the System Development Life Cycle (SDLC) method in 9 afdelings with a total of 219 oil palm harvesters. Results: This application is the final process of the research, namely evaluating the results of the test and the feasibility of implementing the application for use by workers. Conclusion: This Android-based application can help map the risks of near misses and work accidents, making it easier for companies to record data on near misses and work accidents. In addition, the data input process by workers can be carried out quickly because the data input is done in real time

Gold Nanotriangle-Assembled Nanoporous Structures for Electric Field-Assisted Surface-Enhanced Raman Scattering Detection of Adenosine Triphosphate.

A reliable, rapid, cost-effective, and simple method for the detection of biomolecules would greatly promote the research of analytical detection of single molecules. A nanopore-based analytical technique is promising for detecting biomolecules. Conventional electrochemical nanopores cannot distinguish biomolecules precisely because of their fast translocation speed and limited electrochemical information. Therefore, it is highly desirable to develop electrochemical surface-enhanced Raman scattering (SERS) nanopores to obtain multidimensional information. Herein, we designed and fabricated gold nanotriangle (AuNT)-assembled porous structures at the tip of a glass capillary using dithiol adenosine triphosphate (ATP) aptamers as cross-linking molecules. The AuNTs exhibited an edge length of 57.3 ± 6.2 nm and thickness of about 15 nm. The gold nanoporous structure (GPS) showed a strong ion rectification even at a high concentration of electrolyte (2 M) and a high SERS activity. Based on these designed structures, SERS and electrochemistry techniques were combined to control the rapid movement of ATP to the vicinity of the GPS by an applied potential of +1 V, where ATP was concentrated by ATP aptamers and the molecular signals were amplified by SERS. As a result, the GPS successfully detected ATP at a concentration as low as 10-7 M.

Estimation and Mapping Above-Ground Mangrove Carbon Stock Using Sentinel-2 Data Derived Vegetation Indices in Benoa Bay of Bali Province, Indonesia

Carbon dioxide (CO2) is one of the greenhouse gases that causes global warming with the highest concentration in the atmosphere. Mangrove forests can absorb CO2 three times higher than terrestrial forests and tropical rainforests. Moreover, mangrove forests can be a source of Indonesian income in the form of a blue economy, therefore an accurate method is needed to investigates mangrove carbon stock. Utilization of remote sensing data with the results of the above-ground carbon (AGC) detection model of mangrove forests based on multispectral imaging and vegetation index, can be a solution to get fast, cheap, and accurate information related to AGC estimation. This study aimed to investigates the best model for estimating the AGC of mangroves using Sentinel-2 imagery in Benoa Bay, Bali Province. The random forest (RF) method was used to classified the difference between mangrove and non-mangrove with the treatment of several parameters. Furthermore, a semi-empirical approach was used to assessed and map the AGC of mangroves. Allometric equations were used to calculated and produced AGC per species. Moreover, the model was built with linear regression equations for one variable x, and multiple regression equations for more than one x variable. Root Mean Square Error (RMSE) was used to assess the validation of the model results. The results of the mangrove forests area detected in the research location around 1134.92 ha, with an Overall Accuracy (OA) of 0.984 and a kappa coefficient of 0.961. This study highlights that the best model was the combination of IRECI and TRVI vegetation indices (RMSE: 11.09 Mg/ha) for a model based on red edge bands. Meanwhile, the best results from the model that does not use the red edge band were the combination of TRVI and DVI vegetation indices (RMSE: 13.63 Mg/ha). The use of red edge and NIR bands is highly recommended in building the AGC model of mangrove forests because they can increase the accuracy value. Thus, the results of this study are highly recommended in estimating the AGC of mangrove forests, because it has been proven to be able to increase the accuracy value of previous studies using optical images.

BIRDIE: A data pipeline to inform wetland and waterbird conservation at multiple scales

IntroductionEfforts to collect ecological data have intensified over the last decade. This is especially true for freshwater habitats, which are among the most impacted by human activity and yet lagging behind in terms of data availability. Now, to support conservation programmes and management decisions, these data need to be analyzed and interpreted; a process that can be complex and time consuming. The South African Biodiversity Data Pipeline for Wetlands and Waterbirds (BIRDIE) aims to help fast and efficient information uptake, bridging the gap between raw ecological datasets and the information final users need.MethodsBIRDIE is a full data pipeline that takes up raw data, and estimates indicators related to waterbird populations, while keeping track of their associated uncertainty. At present, we focus on the assessment of species abundance and distribution in South Africa using two citizen-science bird monitoring datasets, namely: the African Bird Atlas Project and the Coordinated Waterbird Counts. These data are analyzed with occupancy and state-space models, respectively. In addition, a suite of environmental layers help contextualize waterbird population indicators, and link these to the ecological condition of the supporting wetlands. Both data and estimated indicators are accessible to end users through an online portal and web services.Results and discussionWe have designed a modular system that includes tasks, such as: data cleaning, statistical analysis, diagnostics, and computation of indicators. Envisioned users of BIRDIE include government officials, conservation managers, researchers and the general public, all of whom have been engaged throughout the project. Acknowledging that conservation programmes run at multiple spatial and temporal scales, we have developed a granular framework in which indicators are estimated at small scales, and then these are aggregated to compute similar indicators at broader scales. Thus, the online portal is designed to provide spatial and temporal visualization of the indicators using maps, time series and pre-compiled reports for species, sites and conservation programmes. In the future, we aim to expand the geographical coverage of the pipeline to other African countries, and develop more indicators specific to the ecological structure and function of wetlands.

Fast UAV path planning in urban environments based on three-step experience buffer sampling DDPG

The path planning of Unmanned Aerial Vehicle (UAV) is a critical issue in emergency communication and rescue operations, especially in adversarial urban environments. Due to the continuity of the flying space, complex building obstacles, and the aircraft's high dynamics, traditional algorithms cannot find the optimal collision-free flying path between the UAV station and the destination. Accordingly, in this paper, we study the fast UAV path planning problem in a 3D urban environment from a source point to a target point and propose a Three-Step Experience Buffer Deep Deterministic Policy Gradient (TSEB-DDPG) algorithm. We first build the 3D model of a complex urban environment with buildings and project the 3D building surface into many 2D geometric shapes. After transformation, we propose the Hierarchical Learning Particle Swarm Optimization (HL-PSO) to obtain the empirical path. Then, to ensure the accuracy of the obtained paths, the empirical path, the collision information and fast transition information are stored in the three experience buffers of the TSEB-DDPG algorithm as dynamic guidance information. The sampling ratio of each buffer is dynamically adapted to the training stages. Moreover, we designed a reward mechanism to improve the convergence speed of the DDPG algorithm for UAV path planning. The proposed TSEB-DDPG algorithm has also been compared to three widely used competitors experimentally, and the results show that the TSEB-DDPG algorithm can archive the fastest convergence speed and the highest accuracy. We also conduct experiments in real scenarios and compare the real path planning obtained by the HL-PSO algorithm, DDPG algorithm, and TSEB-DDPG algorithm. The results show that the TSEB-DDPG algorithm can archive almost the best in terms of accuracy, the average time of actual path planning, and the success rate.

Mapping of Limestone Potential Using Landsat 8 Satellite Imageryin Some Areasof Timpeh

Limestone potential is important information that can be obtained from remote sensing data which has advantages and speed in processing results. Remote sensing is a technology that can overcome the problemof measuring data for fast and accurate information. This research was carried out in some areas of the Timpeh sub-district,andDharmasraya districtusing Landsat 8-OLI imagery with the aimof1) identifying the potential of limestone using the Band Ratio method. 2) How to apply remote sensing in mapping the potential of limestoneusing Landsat 8 Oli imagery.&#x0D; This research was carried out in several stages, namely Pre Processing which included radiometric correction and atmospheric correction, image cropping according to the research area, and processing whichincluded making geological maps, making landform maps, making maps of river flow patterns and vegetationindex maps and limestone identification using the RGB band ratio method (5/4;6/3;4/2).&#x0D; The results of field identification in potential limestone areas, where the RGB (Red Green Blue)composite of the band ratio 5/4;6/3;4/2 shows that the presence of limestone is characterized by the appearanceof greenish-brown colored objects. The average pixel value for limestone with a band ratio of 5/4 is 2.475, for a6/3 ratio is 1.275 and for a 4/3 ratio is 0.788. In this study, the potential area of limestone in the research areawasfound,whichwas approximately 2352,14564 ha.

Advances in brain-computer interface based on high-frequency steady-state visual evoked potential

Steady-state visual evoked potential (SSVEP) has been widely used in the research of brain-computer interface (BCI) system in recent years. The advantages of SSVEP-BCI system include high classification accuracy, fast information transform rate and strong anti-interference ability. Most of the traditional researches induce SSVEP responses in low and middle frequency bands as control signals. However, SSVEP in this frequency band may cause visual fatigue and even induce epilepsy in subjects. In contrast, high-frequency SSVEP-BCI provides a more comfortable and natural interaction despite its lower amplitude and weaker response. Therefore, it has been widely concerned by researchers in recent years. This paper summarized and analyzed the related research of high-frequency SSVEP-BCI in the past ten years from the aspects of paradigm and algorithm. Finally, the application prospect and development direction of high-frequency SSVEP were discussed and prospected.

IDENTIFICATION OF LAND COVER OF SURFACE TEMPERATURE IN KOTA PARIAMAN USING LANDSAT IMAGERY 8-OLI

Remote sensing is a technology that can overcome data measurement problems for fast and accurate information. This research was carried out in Pariaman City using Landsat 8-OLI imagery with the aim of 1) knowing the identification of land cover based on the classification SNI:7645 (2014) based on Landsat 8-OLI imagery in the Pariaman City area in 2020 2) knowing the identification of surface temperature in the Pariaman City area in 2020. The research was conducted in serval stages, namely pre-processing of image data, selecting band combinations, cutting area studies, image classification, and testing accuracy. At surface temperature using Landsat 8-OLI imagery in 2020, surface temperature values ​​are obtained from the results of thermal band processing. The results of the classification of Landsat 8-OLI images in Pariaman City produce 5 land cover classes, namely water bodies, rice fields, settlements, mixed gardens, and shrubs. This research conducted a classification accuracy test using a confusion matrix accuracy test table. Land cover supervised maximum likelihood method the overall accuracy value is 86.66 %. The results of the surface temperature value in Pariaman City in 2020 obtained the highest temperature value of 30ºC and the lowest surface temperature of 23ºC.

Residue-Level Characterization of Antibody Binding Epitopes Using Carbene Chemical Footprinting.

Characterization of antibody binding epitopes is an important factor in therapeutic drug discovery, as the binding site determines and drives antibody pharmacology and pharmacokinetics. Here, we present a novel application of carbene chemical footprinting with mass spectrometry for identification of antibody binding epitopes at the single-residue level. Two different photoactivated diazirine reagents provide complementary labeling information allowing structural refinement of the antibody binding interface. We applied this technique to map the epitopes of multiple MICA and CTLA-4 antibodies and validated the findings with X-ray crystallography and yeast surface display epitope mapping. The characterized epitopes were used to understand biolayer interferometry-derived competitive binding results at the structural level. We show that carbene footprinting provides fast and high-resolution epitope information critical in the antibody selection process and enables mechanistic understanding of function to accelerate the drug discovery process.

Evaluation of BISON metallic fuel performance modeling against experimental measurements within FIPD and IMIS databases

Simulations were conducted using the BISON fuel performance code on an automated process to read initial and operating conditions from two databases—the Fuels Irradiation and Physics Database (FIPD) and Integral Fast Reactor Materials Information System (IMIS) database. These databases contain metallic fuel data from the Experimental Breeder Reactor-II (EBR-II) and the Fast Flux Test Facility (FFTF). The work demonstrates use of an integrated framework to access EBR-II fuel pin data for evaluating fuel performance models contained within BISON to predict fuel performance of next-generation metallic fuel systems. Between IMIS and FIPD, there is enough information to conduct 1,977 unique EBR-II metallic fuel pin histories from 29 different experiments, and 338 pins from FFTF MFF-3 and MFF-5 with varying levels of details between the two databases. Each of these fuel performance histories includes a high-resolution power history, flux history, coolant channel flow rates, and coolant channel temperatures, and new model developments in BISON since the initial demonstration of this integrated framework. Fission gas release (FGR), cumulative damage fraction, fuel axial swelling, FCCI wastage thickness, cladding profilometry, and burnup were all simulated in BISON and compared to post-irradiation examination (PIE) results to evaluate BISON fuel performance modeling. Implementation of new fuel performance models into a generic BISON input file coupled with IMIS and FIPD yielded results with a better representation of physics than the initial evaluation of the integrated framework. Cladding profilometry, FGR, and fuel axial swelling were found to be in good agreement with PIE measurements for most of the pins simulated. The chosen mechanical contact solver was found to significantly impact the axial fuel swelling and cladding strain predictions when used in conjunction with the U-Pu-Zr hot-pressing model since it bound the fuel to prevent further swelling and increased hydrostatic stresses. This work suggests that fuel performance modeling in BISON under steady-state conditions represents the PIE data well and should be reassessed when new PIE data become available in IMIS and FIPD databases and when improved physical models to better capture fuel performance are added to BISON.

PERANCANGAN SISTEM INFORMASI PERTANIAN BERBASIS WEB PADA DINAS PANGAN, TANAMAN PANGAN DAN HORTIKULTURA

&lt;p&gt;&lt;em&gt;This study aims to design an agricultural information system using the MySQL database programming language at the Riau Province food, agriculture and horticultural service by using the Design Unified Modeling Language (UML) modeling, one of the advantages of this system is the availability of fast information services. For agencies, this is the right way to share programs or services not only to employees but also to the public directly. The fact is that this information information system not only provides information online, but also with service value. It is hoped that the system that the authors develop This can be a place of service for all agencies, so that the design can be useful for the food, food plants and horticulture office of Riau province to develop the official website.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Keywords&lt;/em&gt;&lt;/strong&gt;&lt;em&gt;: Agricultural Information Systems, Website&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;This study aims to design an agricultural information system using the MySQL database programming language at the Riau Province food, agriculture and horticultural service by using the Design Unified Modeling Language (UML) modeling, one of the advantages of this system is the availability of fast information services. For agencies, this is the right way to share programs or services not only to employees but also to the public directly. The fact is that this information information system not only provides information online, but also with service value. It is hoped that the system that the authors develop This can be a place of service for all agencies, so that the design can be useful for the food, food plants and horticulture office of Riau province to develop the official website.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt; &lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Keywords&lt;/em&gt;&lt;/strong&gt;&lt;em&gt;: Agricultural Information Systems, Website&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;&lt;br /&gt;&lt;/em&gt;&lt;/p&gt;

ANALISIS PELAKSANAAN LAYANAN SAPA PUSTAKAWAN ONLINE DI PERPUSTAKAAN IAIN KUDUS

The Sapa Pustakawan Online Service is an online-based information search service at the IAIN Kudus Library. The service utilizes Telegram's social media as a service medium for users. This study aims to analyze how the application of the Sapa Pustakawan Online service at the IAIN Kudus Library. This research was conducted using a qualitative research approach with a descriptive type of research. The data collection methods used in this study include observation, interview methods, and literature study methods. The observation method is used to make observations on service activities by librarians to users in the telegram group Sapa Pustakawan Online at IAIN Kudus Library. Then, the interview method was used to extract research data from the Head of the IAIN Kudus Library and the librarian at the IAIN Kudus Library regarding the application of the Sapa Pustakawan Online service. The method of collecting data through literature study is extracting data by using literature sources that are in accordance with the research theme. From the research, it can be concluded that the Sapa Pustakawan Online service is able to provide easy information search services, fast information search services, and capable information search services.

PEMENUHAN INFORMASI AKADEMIK SISWA MELALUI APLIKASI BRAINLY

The increasingly sophisticated technology is used as a teaching and learning process to meet the academic needs of students. Like the SMPN 25 Bekasi school which allows its students to use gadgets to help with their learning needs. This study aims to determine whether there is a relationship between the Brainly Application on the fulfillment of students' academic information. This research method uses a quantitative approach. Total population of 1,232 students. Sampling was done by proportional sampling by distributing 92 questionnaires. The theory in this study is the fulfillment of information needs. Data analysis used product moment using SPSS version 22 program. The results showed that the brainly application as complete and concise information had a percentage of 95% because it was used as an effective learning medium for learning methods, because there was complete and concise learning information. The value of the brainly application relationship as specific and fast information obtained results 84% of students strongly agree. This is evidenced by a strong correlation value of 0.424. Brainly application as an interaction obtained 82% this is evidenced by a strong correlation value of 0.438. Likewise with the brainly application as a dependency, the results obtained are 79%, this is evidenced by a strong correlation value of 0.605.&#x0D; &#x0D; Keywords: Learning, Information Needs, Academic Students.

Classification of Predicting Customer Ad Clicks Using Logistic Regression and k-Nearest Neighbors

Nowadays, conventional marketing techniques have changed to online (digital) marketing techniques requiring internet access. Online marketing techniques have many advantages, especially in terms of cost efficiency and fast information delivery to the public. Therefore, many companies are interested in online marketing and advertising on social media platforms and websites. However, one of the challenges for companies in online marketing is determining the right target consumers since if they target consumers who are not interested in buying the product, the advertising costs will be high. One use of online advertising is clicks on ads which is a marketing measurement of how many users click on the online ad. Thus, companies need a click prediction system to know the right target consumers. And different types of advertisers and search engines rely on modeling to predict ad clicks accurately. This paper constructs the customer ad clicks prediction model using the machine learning approach that becomes more sophisticated in effectively predicting the probability of a click. We propose two classification algorithms: the logistic regression (LR) classifier, which produces probabilistic outputs, and the k-nearest neighbors (k-NN) classifier, which produces non-probabilistic outputs. Furthermore, this study compares the two classification algorithms and determines the best algorithm based on their performance. We calculate the confusion matrix and several metrics: precision, recall, accuracy, F1-score, and AUC-ROC. The experiments show that the logistic regression algorithm performs best on a given dataset.

Rancang Bangun Sistem Informasi Monitoring Marketing Penerimaan Mahasiswa Baru

Industry 4.0 requires various parties to follow the changes. Effective and efficient makes the main focus on industry 4.0, although LP3I Tasikmalaya already has a system, but it still does not meet the demands of user needs and industry 4.0 competition. Telleselling, MCV, and WA-Blast, are the activities of the presenters of LP3I Tasikmalaya which should have been facilitated by the system but in the field they use Googgle Sheets because the system is considered not to meet the needs and makes it difficult. The aim of the research is to designing and building an information system for Monitoring Marketing in LP3I Tasikmalaya, so that it can address potential data storage problems, update potential data, thereby providing fast and accurate information in the Marketing Division. The collection method uses observation and interviews while the development of the system used is the waterfall model, which consists of stages: analysis, design, coding, and testing, as well as tools in designing the system are DFD (Data Flow diagram). The implementation uses software, namely Android Studio and MySQL Servers. The result of this research is a Digital Marketing Information System that can simplify the process of information on the Marketing Division of LP3i Tasikmalaya in real time.

RANCANG BANGUN SISTEM INFORMASI MADING DIGITAL BERBASIS WEB PADA SMK BANII SAALIM BANDAR LAMPUNG

Wall magazine (Maiding) is a means of dissemination of information in the educational world. Despite the urgent need for fast and accurate information, today's media security is still poorly maintained, affecting the ability of students to receive information. Therefore, schools need information media and media to disseminate information quickly and accurately. Digital learning media help manage information so students receive more up-to-date information. The research methodology was carried out in three phases. In the preliminary phase, data collection was conducted through literature surveys, direct observations, and journal archives from similar surveys. The analysis phase includes a system analysis of the current bulletin board system and any bulletin boards to be created. The system development model uses the Extreme Programming Model or XP. The system is designed using the Unified Modeling Language (UML). The results of the research have led to a digital madding system that allows schools to more easily communicate information, allowing students to submit information directly through his website for Digital Wall Magazine. Meanwhile, schools can control the information coming in and decide what information is made public. Information is updated her once a week or as needed to ensure students have the most up-to-date information.

DESIGN OF WIRELESS POINT TO POINT NETWORK IN SERIGENI NEW VILLAGE, KAB. OGAN KOMERING ILIR

The technology that is developing at this time can certainly make it easier and maximize in doing various things in daily life, including in terms of accessing various information and data using an internet network media so that we can access data and information from outside with ease. The computer network project then began to feel the benefits. When a computer network is created, everyone can work more optimally and can do many processes without wasting a lot of time. The results of the computer network project then produce a program called Batch Processing (continuous process). This program allows multiple users to use multiple computers to work on multiple programs and jobs at the same time. The existence of technology helps humans in solving various problems in everyday life to get fast, precise and accurate information. Packet Tracer is a simulator of Cisco network tools that is often used as a medium of learning and training, and also in the field of computer network simulation research. Packet Tracer is usually used by Cisco Networking Academy students through Cisco Certified Network Associate (CCNA) certification. The function of the Packet Tracer is to design a system or network topology that will be applied to the real world / work, because if we design a computer network topology without the help of an application like this, it can be expensive. That's why Cisco made an application like this so that people can learn without the need for expensive fees. To overcome these problemsThe technology that is developing at this time can certainly make it easier and maximize in doing various things in daily life, including in terms of accessing various information and data using an internet network media so that we can access data and information from outside with ease. The computer network project then began to feel the benefits. When a computer network is created, everyone can work more optimally and can do many processes without wasting a lot of time. The results of the computer network project then produce a program called Batch Processing (continuous process). This program allows multiple users to use multiple computers to work on multiple programs and jobs at the same time. The existence of technology helps humans in solving various problems in everyday life to get fast, precise and accurate information. Packet Tracer is a simulator of Cisco network tools that is often used as a medium of learning and training, and also in the field of computer network simulation research. Packet Tracer is usually used by Cisco Networking Academy students through Cisco Certified Network Associate (CCNA) certification. The function of the Packet Tracer is to design a system or network topology that will be applied to the real world / work, because if we design a computer network topology without the help of an application like this, it can be expensive. That's why Cisco made an application like this so that people can learn without the need for expensive fees. To overcome these problems