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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 1,585 Documents
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Spatial Modeling of Fixed Effect and Random Effect with Fast Double Bootstrap Approach Wigbertus Ngabu; Henny Pramoedyo; Rahma Fitriani; Ani Budi Astuti
ComTech: Computer, Mathematics and Engineering Applications Vol. 14 No. 1 (2023): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v14i1.8033

Abstract

The use of panel data on spatial regression has many advantages. However, testing the spatial dependency and parameter presumption generated in spatial regression of panel data becomes inaccurate when applied to regions with large numbers of small spatial units. One method of overcoming problems of small spatial unit sizes is the bootstrap method. The research aimed to combine cross-section and time-series panel data. The analysis was performed to extract information based on observations modified by the influences of space or location, known as spatial analysis of panels. The influence of location effects on spatial analysis was presented in the form of weighting. The research applied the Fast Double Bootstrap (FDB) method by modeling poverty rates on Flores Island. The results of the Hausman test show the right model, which is a random effect. Meanwhile, spatial dependency testing concludes spatial dependence and poverty modeling in Flores Island, which is more likely to be the Spatial Autoregressive Random (SAR) model. SAR random effect in modeling value has R2 of 77,38% and does not meet the normality assumption. SAR effect in modeling the FDB approach can explain the diversity of poverty rate in the Flores Island with 88,64% and meets residual normality assumptions. The analysis with the FDB approach on spatial panels shows better results than the common spatial panels.
Data-Driven Approach for Credit Risk Analysis Using C4.5 Algorithm Muhammad Iqbal; Syahril Efendi
ComTech: Computer, Mathematics and Engineering Applications Vol. 14 No. 1 (2023): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v14i1.8243

Abstract

Credit risk is bad credit, resulting in bank losses due to non-receipt of disbursed funds and unacceptable interest income. However, credit services still have to be done to achieve profit. The absence of an approach that can assist in making policies to reduce credit risk makes the risk opportunities even more significant. So, data processing techniques are needed that produce information to be used as the basis for policies in triggering credit risk with data mining. The research presented an application of data mining as a credit risk approach considering the ability of data mining techniques to extract data into useful information with the C4.5 algorithm. The research used a sample of 30 data banks with 6 factors (credit growth, net interest margin, type of bank, capital ratio, company size, and bank compliance level). Credit risk was evaluated by making a decision tree and a RapidMiner test application. The results show that credit growth is the main factor causing credit risk, followed by bank compliance level, net interest margin, and capital ratio. Based on the results obtained, the C4.5 algorithm can be used in analyzing credit risk with results that are easy to understand and can be used as useful information for banks.
A Robust Optimizing Reverse Logistics Model for Beef Products Using Multi Depot Vehicle Routing Problem Paduloh Paduloh; Taufik Djatna
ComTech: Computer, Mathematics and Engineering Applications Vol. 14 No. 1 (2023): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v14i1.8397

Abstract

Beef is a perishable product and requires special handling. Demand for beef also fluctuates quite high and is heavily influenced by various religious events and traditions in Indonesia. Under these conditions, for various reasons, beef products are returned from customers to distributors. An increase in the number of products returned from customers leads to high costs and the risk of product damage. The research created an optimization model for product distribution and product recall from customers with minimal costs and risks. The research applied a clustering method using the Density-Based Spatial Clustering (DBSCAN) algorithm to determine the density of customers’ locations and the number of orders. Optimization of distance and distribution and withdrawal costs applied Multi Depot Vehicle Routing Problem (MDVRP) and Mixed Integer Linear Programming (MILP) mathematical modeling. The results indicate three customer clusters with one noise, with the most potential customers in cluster 1. From this condition, product delivery optimization is based on the distance and number of shipments from the two central warehouses. Optimization uses of MDVRP and MILP to model and make company-owned trucks more profitable at high rental truck replacement costs. The research produces a robust model for changes in the truck number and capacity based on sensitivity analysis.
The Implementation of Control Charts as a Verification Tool in a Time Series Model for COVID-19 Vaccine Participants in Pontianak Nurfitri Imro'ah; Nur'ainul Miftahul Huda; Abang Yogi Pratama
ComTech: Computer, Mathematics and Engineering Applications Vol. 14 No. 1 (2023): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v14i1.8462

Abstract

Vaccines are the primary weapon used to stop the outbreak, especially amid the COVID-19 pandemic. Thus, supplying vaccines to control the COVID-19 pandemic is essential, especially in minimizing the incidence and achieving herd immunity to break the chain of COVID-19. West Kalimantan has taken firm anticipatory steps to prevent COVID-19 in the form of a vaccination program in Indonesia. The highest vaccination achievement occurs in Pontianak City, the province’s capital. The research analyzed data on vaccine participants in Pontianak using time series analysis. In addition, the residuals from the time series model were used as observations in constructing the control chart. The research also analyzes the accuracy of the time series model using the Individual Moving Range (IMR) control chart. The results show that the ARIMA model (5,0,2) is the best because it fulfills the assumption of white noise. However, the ARIMA (5,0,2) model is inaccurate in making predictions because the residuals from the ARIMA (5,0,2) model are out of control (based on the IMR control chart). Hence, it is necessary to evaluate in determining the time series model. It can be analyzed using a control chart. Therefore, measuring the model’s accuracy on the best model is essential in predicting several subsequent periods.
Lightweight Design and Finite Element Analysis of Brake Lever for Motorcycle Application Agus Puji Prasetyono; Aan Yudianto; I Wayan Adiyasa
ComTech: Computer, Mathematics and Engineering Applications Vol. 14 No. 1 (2023): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v14i1.8604

Abstract

A lightweight component design contributes to the overall optimization of a system to be more effective and efficient. Then, it can lead to the contribution of a carbon footprint reduction. The research aimed to propose a novel lightweight brake lever design for motorcycle applications and numerically investigate its performance by comparing the proposed design with different utilized materials. The subject of the research was an optimized brake lever for motorcycle application. The materials used were aluminum alloy, structural steel, and titanium alloy. A Finite Element Method (FEM) analysis was employed to investigate the proposed brake lever design. Three proposed designs were introduced with the mass reduction in each optimization up to 50,9% of reduced mass. Maximum stress was observed on the most optimized design with a value of 297 MPa. The strain and total deformation were also investigated among the components. In the result, the stress-strain graph shows that the most optimized brake lever experiences the highest stress with the highest strain value. Furthermore, the highest safety factor is achieved with the utilization of titanium alloy, reaching the value of 6,28 for preliminary design and 3,1 for the most optimized component. However, the lightest component can be obtained using aluminum alloy.
Prediction Model for Tourism Object Ticket Determination in Bangkalan, Madura, Indonesia Fifin Ayu Mufarroha; Akhmad Tajuddin Tholaby; Devie Rosa Anamisa; Achmad Jauhari
ComTech: Computer, Mathematics and Engineering Applications Vol. 14 No. 2 (2023): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v14i2.7992

Abstract

One of the regencies in Madura, namely Bangkalan, with its local wisdom and beautiful landscapes has the potential to become a tourism center. However, there may be a decrease in the number of visits caused by some factors. The research used the time series method to build a prediction model for tourist attraction entrance tickets. The model development aimed to estimate the number of tourist attraction visits in the future. The right model was needed to get the best prediction results. Least square, Holt-Winter, Seasonal Autoregressive Integrated Moving Average (SARIMA), and Rolling were chosen as the models. Data collection related to the number of tourist objects was carried out directly at the Tourism Office to obtain valid data. Using data on visitors to tourist attractions in Bangkalan Regency from 2015 to 2019, the results of measuring errors using Mean Absolute Percentage Error (MAPE) and Root Mean Squared Error (RMSE) are obtained. The error measurement results show that the Holt-Winter model has the lowest error rate of 5% and RMSE of 307,1198. Based on these calculations, the Holt-Winter model is the best model for determining tourist attraction entrance tickets. The ranking of the error measurement results from the highest to the lowest are Holt-Winter, Rolling, SARIMA, and Least Square methods.
Smart Shrimp Farming Using Internet of Things (IoT) and Fuzzy Logic Michael Johan; Suharjito Suharjito
ComTech: Computer, Mathematics and Engineering Applications Vol. 14 No. 2 (2023): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v14i2.8981

Abstract

In the case of ponds with Litopenaeus Vannamei shrimp, water quality parameters play a significant role in shrimp growth. Leveraging technology enhances water quality to optimize growth and survivability in the shrimp farming industry. The research aimed to empower local farmers with smart shrimp farming technologies, including Information Technology (IT), such as the Internet of Things (IoT), and Fuzzy Logic. The research also involved a comparison between Litopenaeus Vannamei shrimp in two different aquariums: one serving as a control group and the other implementing IoT and Fuzzy Logic for a period of 30 days. The initial Litopenaeus Vannamei shrimp stocking was 135 shrimps for control aquariums and 132 for experimental aquariums. Then, the research used Arduino ESP 8266, Raspberry Pi 3, and SciKit-Fuzzy library to record and process the data. Through the application of IoT and Fuzzy Logic, the research successfully increases survivability by 6%, specific growth rate by 28%, and length by 8% in 30 days compared to conventional methods. The results highlight the potential use of technology in Litopenaeus Vannamei shrimp farming. The proposed system’s hardware and software architecture can be easily scaled to accommodate the needs of Litopenaeus Vannamei shrimp farmers with multiple ponds, offering flexibility and adaptability.
Mobile-Based Car Diagnostic Application Using Onboard Diagnostic-II Scanner Karto Iskandar; Alfred Tambayong; Muhammad Rafif Fawwaz Mulya; Steven Cendra Elfanlie; Maria Grace Herlina
ComTech: Computer, Mathematics and Engineering Applications Vol. 14 No. 2 (2023): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v14i2.9138

Abstract

Mobile applications today serve as versatile tools across diverse sectors, enhancing human productivity through specialized software on electronic devices. Implementation of the mobile application can also be applied to vehicles, with inspection and checking functions assisted by the Onboard Diagnostic-II (OBD-II) scanner. The research aimed to develop an integrated mobile application that utilized the OBD-II scanner and Data Acquisition System (DAS) to monitor vehicle health and provide timely service reminders. Vehicle information was taken by the DAS process into a Diagnostic Trouble Code (DTC) from the vehicle itself. The method applied the waterfall model, which consisted of communication, planning, modeling, construction, and evaluation. The problem analysis and requirements gathering for developing the application involves the interview method and Google Forms-generated questionnaires with 101 responses. Then, the research used OBD-II series ELM327 and ELM 327 IC devices for testing. The research results in an application developed for vehicle diagnostics using a recommendation system through notifications that provide vehicle health information and service time reminders to users. This application consists of eight modules, with the main module being able to provide recommendations for vehicle owners. These recommendations are helpful for users to maintain the health of their vehicles regularly. Further research is recommended to enhance the development of the application, aiming to create a more comprehensive user interface.
The One-Dimensional (1D) Numerical Model: An Application to Oxygen Diffusion in Mitochondria Cell Gandhi Napitupulu; Achmad Nagi; Mutiara Rachmat Putri; Ivonne Milichristi Radjawane
ComTech: Computer, Mathematics and Engineering Applications Vol. 14 No. 2 (2023): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v14i2.9705

Abstract

The first model of oxygen transport was formulated by August Krogh. However, the investigations conducted have yet to yield a complete analytical model and a widely applicable solution for One-Dimensional (1D) network construction. The research sought to provide numerical and analytical solutions for the oxygen transfer model in mitochondrial cells to enable researchers to estimate the molecular dynamics and diffusion characteristics in mitochondrial cells. The oxygen diffusion process in mitochondria was modeled with ID numerical models. The numerical models used to solve the equations were explicit and implicit. The explicit model consisted of Forward Time Center Space (FTCS) and DuFort-Frankel. Meanwhile, the implicit model had Crank-Nicholson and Laasonen. The numerical solutions of the explicit and implicit were divided into four scenarios with a variation of Δt and compared with the analytical solutions. The results show that the Laasonen method is the best in describing the diffusion process. The best scenario with the lowest slope value and small Root Mean Square Error (RMSE) value is scenario 2 (Δt = 3,33E-4 s and Δx = 2,00E-5 cm). The numerical model and analytical solution show that the time required to reach a steady state is 0,7 s. It indicates oxygen exchange in two sides of the mitochondrial cell after 0,7 s.
Fuzzy C-Means in Content-Based Document Clustering for Grouping General Websites Based on Their Main Page Contents Sri Probo Aditiyo; Eni Sumarminingsih; Rahma Fitriani
ComTech: Computer, Mathematics and Engineering Applications Vol. 14 No. 2 (2023): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v14i2.9732

Abstract

The research aimed to use Fuzzy C-Means clustering in content-based document clustering to classify general websites based on their content. The data used were a table ranking of the most visited websites for Indonesia, taken from https://dataforseo.com/top-1000-websites/ on September 24th, 2022. The research was conducted with two different cases using Fuzzy C-Means clustering, which had two different iteration parameter values, namely 100 and 200 in maximum iteration. The research results on Fuzzy C-Means clustering in content-based document clustering are based on the two cases. These different maximum iteration parameters result in a different amount of website name data in the cluster. They are formed in the first and second clusters only. However, in the other clusters, the numbers are all the same. The results of the cluster research are validated using the silhouette coefficient, with case no. 1 and no. 2 values being 0,977783879 and 0,977788457. The use of Fuzzy C-Means clustering in content-based document clustering has an excellent performance when this method is applied to group general websites based on their content. With that result, content-based clustering can be also applied in other cases. Hence, the results can be considered to be applied to other cases for content-based clustering in the future.

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