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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. 13 No. 1 (2022): ComTech" : 6 Documents clear
The Implementation of Knowledge Management System (KMS) Evaluation Model in Improving Employee Performance: A Case Study of the State Electricity Company Wahyu Budianto; Wahyu Sardjono
ComTech: Computer, Mathematics and Engineering Applications Vol. 13 No. 1 (2022): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v13i1.6873

Abstract

Employee performance has a crucial role in running a company. Thus, efforts to improve employee performance are vital to be conducted and evaluated. The research aimed to assess the Knowledge Management System (KMS) evaluation model implemented at PT Perusahaan Listrik Negara (PLN) (Persero), a state electricity company, and found the factors and indicators to improve employee performance. The research applied a survey that collected data through a summative evaluation by using a questionnaire. The population in the research was 100 employees in PT PLN (Persero). The sampling technique was a probability, namely purposive sampling. Then, the results were examined using the SPSS program to measure the relationship of the variables under study. The collected data were also analyzed quantitatively using descriptive and inferential statistics. The analysis results show that people, process, and technology positively affect employee performance. Thus, based on the results, it can be concluded that the three main elements of KMS have a positive impact on the performance of the employees of PT PLN (Persero). It is suggested that the company takes care of their people, process, and technology to improve its performance considering the findings. It is expected that the management of PT PLN (Persero) can develop and optimize the factors that affect employee performance in using KMS for sustainable company decisions.
Discovering the Optimal Number of Crime Cluster Using Elbow, Silhouette, Gap Statistics, and NbClust Methods Noviyanti T. M. Sagala; Alexander Agung Santoso Gunawan
ComTech: Computer, Mathematics and Engineering Applications Vol. 13 No. 1 (2022): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v13i1.7270

Abstract

In recent years, crime has been critical to be analyzed and tracked to identify the trends and associations with crime patterns and activities. Generally, the analysis is conducted to discover the area or location where the crime is high or low by using different clustering methods, including k-means clustering. Even though the k-means algorithm is commonly used in clustering techniques because of its simplicity, convergence speed, and high efficiency, finding the optimal number of clusters is difficult. Determining the correct clusters for crime analysis is critical to enhancing current crime resolution rates, avoiding future incidents, spending less time for new officers, and increasing activity quality. To address the problem of estimating the number of clusters in the crime domain without the interference of humans, the research carried out Elbow, Silhouette, Gap Statistics, and NbClust methods on datasets of Major Crime Indicators (MCI) in 2014−2019. Several stages were performed to process the crime datasets: data understanding, data preparation, cluster modelling, and cluster validation. The first two phases were performed in the R Studio environment and the last two stages in Azure Studio. From the experimental result, Elbow, Silhouette, and NbClust methods suggest a similar number of optimum clusters that is two. After validating the result using the average Silhouette method, the research considers two clusters as the best clusters for the dataset. The visualization result of Silhouette method displays the value of 0,73. Then, the observation of the data is well-grouped. It is placed in the correct group.
The Application of C4.5 Algorithm for Selecting Scholarship Recipients Fristi Riandari; Sarjon Defit
ComTech: Computer, Mathematics and Engineering Applications Vol. 13 No. 1 (2022): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v13i1.7307

Abstract

The scholarship program is one of the promotional techniques used by many universities, and the right scholarship award will certainly be an attraction for many people. STMIK Pelita Nusantara is one of the universities that organizes a scholarship program. In the current difficult economic conditions, the scholarship program is the target of many prospective students who want to continue their education in higher education. However, the absence of tools to process large amounts of data make determining scholarship recipients less effective and time-consuming. This situation is seen by the fact that some students are still unable to maintain the scholarships they receive. In the research, a classification model was proposed using the C4.5 algorithm approach by utilizing past data to facilitate the decision making of the scholarship program. This classification process produced a decision tree that could be used as a decision-making tool. Scholarships were awarded based on several criteria: academic potential, vocational potential, parents’ income, number of dependents, and employment status. Based on the data processing results of students who apply for scholarships in 2020 with predetermined criteria, the highest root is obtained. It consists of node 1 for academic potential, node 1.1 for vocational potential, and node 1.2 for parental income. The resulting decision tree model is expected to help to make decisions quickly and on target.
The Solution of Non-Linear Equations System Containing Interpolation Functions by Relaxing the Newton Method Nur Rokhman; Erwin Eko Wahyudi; Janoe Hendarto
ComTech: Computer, Mathematics and Engineering Applications Vol. 13 No. 1 (2022): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v13i1.7322

Abstract

Many world phenomena lead to nonlinear equations systems. For some applications, the non-linear equations which construct the non-linear equations system are interpolation functions. However, the interpolation functions are usually not represented as mathematical expressions but as computer programs in specific programming languages. The research proposed using the relaxed Newton method to solve the non-linear equations system that contained interpolation functions. The interpolation functions were represented in the R programming language. Then, the experiment used the Spline interpolation function to construct a two-dimensional non-linear equations system. Eleven initial guesses, maximum of ten-time iterations, and 10-7 precision were applied. The solution of the non-linear equations system and the iteration needed on each initial guess were observed. The experiment shows that the proposed method works well for solving the non-linear equations system constructed by Spline interpolation functions. By observing the initial guesses used in the experiment, there are four possible results: true solution, spurious solution, false solution, and no solution. Applying 11 initial guesses have five initial guesses resulting in true solutions, one initial guess in spurious solution, three initial guesses in false solutions, and one initial guess in no solution. The discussions imply that this method can be generalized to the three-dimensional non-linear equations system or higher dimensions.
The Asset Management and Tracking System for Technical and Vocational Education and Training (TVET) Institution Based on Ubiquitous Computing Totok Sulistyo; Karmila Achmad; Ida Bagus Irawan Purnama
ComTech: Computer, Mathematics and Engineering Applications Vol. 13 No. 1 (2022): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v13i1.7342

Abstract

Generally, Technical and Vocational Education and Training (TVET) has numerous types of assets used for conducting various skill-based learning activities. The failure to properly manage the TVET assets can lead to inefficient operation and administration, such as difficulty in tracking the history of the asset, location, and users. The research solved the problems by developing and implementing asset management and tracking system based on ubiquitous cloud computing for movable and fixed assets. The research activities were conducted in Politeknik Negeri Balikpapan, one of ten state-owned TVET institutions in Indonesia. This system was accessed using a web and mobile application. Quick Response (QR) code was used for asset identification to make a mobile device read the code with their built-in camera. Meanwhile, the geolocation was attached to provide the spatial information of assets’ whereabouts. Then, the research adopted the 5W1H question principle, so all aspects of asset management were collected and understood. The results show that the system helps TVET to keep track of their equipment and vital inventories in realtime. Moreover, the implementation of the system has a great impact administratively and ease in delivering instantaneous data and assets history for decisionmaking to internal and external asset auditors.
Prediction of Undergraduate Student’s Study Completion Status Using MissForest Imputation in Random Forest and XGBoost Models Intan Nirmala; Hari Wijayanto; Khairil Anwar Notodiputro
ComTech: Computer, Mathematics and Engineering Applications Vol. 13 No. 1 (2022): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v13i1.7388

Abstract

The number of higher education graduates in Indonesia is calculated based on their completion status. However, many undergraduate students have reached the maximum length of study, but their completion status is unknown. This condition becomes a problem in calculating the actual number of graduates as it is used as an indicator of higher education evaluation and other policy references. Therefore, the unknown completion status of the students who have reached the maximum length of study must be predicted. The research compared the performance of Random Forest and Extreme Gradient Boosting (XGBoost) classification models in predicting the unknown completion status. The research used a dataset containing 13.377 undergraduate students’ profiles from the Higher Education Database (PDDikti), Ministry of Education, Culture, Research, and Technology. The dataset was incomplete, and the proportion of missing data was 20,9% of the total data. Because missing data might lead to prediction bias, the research also used MissForest imputation to overcome the missing data in the classification modelling and compared it to Mean/Mode and Median/Mode imputation. The results show that MissForest outperforms the other two imputations in both classifiers but requires the longest computation time. Furthermore, the XGBoost model with MissForest is significantly superior to the Random Forest model with MissForest. Hence, the best model chosen to predict the completion status is XGBoost with MissForest imputation.

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