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ComTech: Computer, Mathematics and Engineering Applications
Published by Universitas Bina Nusantara
ISSN : 20871244     EISSN : 2476907X     DOI : -
Core Subject : Science, Education, Engineering,
Computer Science & IT Engineering Mathematics
The journal invites professionals in the world of education, research, and entrepreneurship to participate in disseminating ideas, concepts, new theories, or science development in the field of Information Systems, Architecture, Civil Engineering, Computer Engineering, Industrial Engineering, Food Technology, Computer Science, Mathematics, and Statistics through this scientific journal.
Arjuna Subject : -
Articles 6 Documents
 1 
Search results for , issue "Vol. 11 No. 2 (2020): ComTech" : 6 Documents clear
The Effect Analysis of Braden Scale on Pressure Ulcer in Community-Dwelling Older Adults Desri Kristina Silalahi; Husneni Mukhtar; Sheizi Prista Sari; Eka Afrima Sari; Dandi Trianta Barus
ComTech: Computer, Mathematics and Engineering Applications Vol. 11 No. 2 (2020): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v11i2.6237

Abstract

The research aimed to analyze the Braden Scale on the incidence of compressive wounds in elderly people who lived in homes, whether they were or not under the supervision of health workers. The research was analytic with a cross-sectional study. With the purposive sampling technique, the data collection was carried out from several areas in Bandung from October to November 2017. Moreover, the analysis used was multiple regression to see the effect of the Braden Scale on pressure ulcers. The multiple linear regression model was also tested. The results show that 48,22% of pressure ulcer factors can be influenced by sensory perception, humidity, activity, mobility, nutrition, and friction. Sensory perception, activity and friction have significant influence on incidence of pressure ulcers. Meanwhile, the humidity, mobility, and nutrition do not significantly influence it.
Udayana University International Student Management: A Business Process Reengineering Approach Cokorda Rai Adi Pramartha; Ni Putu Sri Harta Mimba
ComTech: Computer, Mathematics and Engineering Applications Vol. 11 No. 2 (2020): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v11i2.6383

Abstract

The research had two aims. First, it presented an overview and progress in understanding the current business process in the international program of Udayana University, which had a long queue for processing student admission documents. Second, it described how Business Process Reengineering (BPR) helped to improve the educational management services. Multiple interviews and a Forum Group Discussion (FGD) with the stakeholders were conducted. The reviews of the available documents, the current business process, and related complaint records were also carefully performed. The results show that the currently running batch processing system is a major challenge. The proposed solution reengineers the current business process and implements an information technology tool as a driver by digitizing the proposed solutions. The new business process leads to an improvement in processing the international student application from more than 60 days to only 29 days. Moreover, the proposed business process can minimize the opportunity loss of more than Rp3,8 billion annually.
Forecasting and Mapping Coffee Borer Beetle Attacks Using GSTAR-SUR Kriging and GSTARX-SUR Kriging Models Henny Pramoedyo; Arif Ashari; Alfi Fadliana
ComTech: Computer, Mathematics and Engineering Applications Vol. 11 No. 2 (2020): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v11i2.6389

Abstract

The research aimed to use Generalized Space Time Autoregressive (GSTAR) and GSTARX modeling with the Seemingly Unrelated Regression (SUR) approach and combine them with the Kriging interpolation technique in an unobserved location. The case study was coffee borer beetle forecasting in Probolinggo Regency, East Java, Indonesia, with Watupanjang Village as the unobserved location. The results show that GSTAR-SUR Kriging and GSTARX-SUR Kriging models can predict coffee borer beetle attacks in unobserved areas with high accuracy. It is indicated by the Mean Absolute Percentage Error (MAPE) values of less than 10%. The addition of exogenous variables (rainfall) into the model is proven to improve the accuracy of the model. The Root-Mean-Square Error (RMSE) value of the GSTARX-SUR Kriging model is smaller than the GSTAR-SUR Kriging model. The structure of the model produced from the research, GSTARX-SUR (1,[1,12])(10,0,0), can be used as a reference in modeling coffee borer beetle attacks in other regencies. Map of forecasting coffee borer beetle attack shows that the spread of coffee borer beetle attack is spatial clustering with the attack center located in the eastern region of Probolinggo Regency.
Volatility Fitting Performance of QGARCH(1,1) Model with Student-t, GED, and SGED Distributions Didit Budi Nugroho; Bintoro Ady Pamungkas; Hanna Arini Parhusip
ComTech: Computer, Mathematics and Engineering Applications Vol. 11 No. 2 (2020): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v11i2.6391

Abstract

The research had two objectives. First, it compared the performance of the Generalized Autoregressive Conditional Heteroscedasticity (1,1) (GARCH) and Quadratic GARCH (1,1) (QGARCH)) models based on the fitting to real data sets. The model assumed that return error follows four different distributions: Normal (Gaussian), Student-t, General Error Distribution (GED), and Skew GED (SGED). Maximum likelihood estimation was usually employed in estimating the GARCH model, but it might not be easily applied to more complicated ones. Second, it provided two ways to evaluate the considered models. The models were estimated using the Generalized Reduced Gradient (GRG) Non-Linear method in Excel’s Solver and the Adaptive Random Walk Metropolis (ARWM) in the Scilab program. The real data in the empirical study were Financial Times Stock Exchange Milano Italia Borsa (FTSEMIB) and Stoxx Europe 600 indices over the daily period from January 2000 to December 2017 to test the conditional variance process and see whether the estimation methods could adapt to the complicated models. The analysis shows that GRG Non-Linear in Excel’s Solver and ARWM methods have close results. It indicates a good estimation ability. Based on the Akaike Information Criterion (AIC), the QGARCH(1,1) model provides a better fitting than the GARCH(1,1) model on each distribution specification. Overall, the QGARCH(1,1) with SGED distribution best fits both data.
Finding Biomarkers from a High-Dimensional Imbalanced Dataset Using the Hybrid Method of Random Undersampling and Lasso Masithoh Yessi Rochayani; Umu Sa'adah; Ani Budi Astuti
ComTech: Computer, Mathematics and Engineering Applications Vol. 11 No. 2 (2020): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v11i2.6452

Abstract

The research conducted undersampling and gene selection as a starting point for cancer classification in gene expression datasets with a high-dimensional and imbalanced class. It investigated whether implementing undersampling before gene selection gave better results than without implementing undersampling. The used undersampling method was Random Undersampling (RUS), and for gene selection, it was Lasso. Then, the selected genes based on theory were validated. To explore the effectiveness of applying RUS before gene selection, the researchers used two gene expression datasets. Both of the datasets consisted of two classes, 1.545 observations and 10.935 genes, but had a different imbalance ratio. The results show that the proposed gene selection methods, namely Lasso and RUS + Lasso, can produce several important biomarkers, and the obtained model has high accuracy. However, the model is complicated since it involves too many genes. It also finds that undersampling is not affected when it is implemented in a less imbalanced class. Meanwhile, when the dataset is highly imbalanced, undersampling can remove a lot of information from the majority class. Nevertheless, the effectiveness of undersampling remains unclear. Simulation studies can be carried out in the next research to investigate when undersampling should be implemented.
Implementation of Microservices Architecture on E-Commerce Web Service Juan Andrew Suthendra; Magdalena Ariance Ineke Pakereng
ComTech: Computer, Mathematics and Engineering Applications Vol. 11 No. 2 (2020): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v11i2.6453

Abstract

The research aimed to make e-commerce web services using a microservices architecture. Web service was built using Representational State Transfer Protocol (REST) with Hypertext Transfer Protocol (HTTP) method and JavaScript Object Notation (JSON) response format. Meanwhile, the microservices architecture was developed using Domain-driven Design (DDD) approach. The research began by analyzing e-commerce business processes and was modeled using Unified Modeling Language (UML) based on business process analysis. Next, the bounded context was used to make a small responsible service for a function. The Programming language used to make the system was Go programming language with Go-kit tool and apply database-per-service pattern for data management. The system also applied the concept of containerization using Docker as the container platform and using API Gateway to manage each endpoint. Last, the evaluation process was carried out using the Postman application by testing each endpoint based on the white-box testing method. Based on the results of the evaluation process, the e-commerce web service can work as expected. The results also show that the system has a high level of resilience. It means that the system has a low level of dependencies between services and adapts to future changes.

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