Nusantara Jurnal of Computer Application

Application of K-Means Clustering Method in Semester I Value Data Clustering Until Semester IV

2022-01-24T17:38:23+07:00

In the Informatics Study Program there is a concentration which is divided into 2 parts which students will choose when entering semester V. The problem that often occurs is that some students sometimes choose concentration instead of seeing the results of the scores obtained during semesters I to IV, and there are some who choose majors because he followed his friends. This is what causes students to often be unprepared at the end of the semester. Therefore, it is necessary to analyze the value of semester I to semester IV obtained by students to help recommend to students which concentration to choose. The analysis is carried out by applying the K-Means Clustering Method, which will produce 2 groups, namely Software Engineering and Network Infrastructure. The K-Means Clustering method has the ability to group large amounts of data with relatively fast and efficient computation time. The Semester I to Semester IV Value Data Grouping application was made using Visual Basic .Net programming language and SQL Server 2008 database by applying one of the data mining methods used was K-Means Clustering. The grouping is done based on student score data obtained from Semester I to Semester IV (data attached). From this data, grouping is done into 2 groups, namely Cluster C1 Software Engineering and Cluster C2 Network Infrastructure. With this application, it can assist the Study Program in providing recommendations and also material for consideration to students in choosing a major whether Software Engineering or Network Infrastructure. Based on the results of the tests that have been carried out, the application of the K-Means Clustering Method in Grouping Semester Value Data has been successfully carried out, and can provide information based on 2 groups, namely Cluster C1 (Software Engineering) and Cluster C2 (Network Infrastructure), and the functionality of the application has been running. as expected.

Employee Performance Assessment Application Using AHP Weighting with Moora Method (Study Case: PT. Astra Honda Motor Bengkulu)

2022-01-24T17:38:23+07:00

At PT. Astra Honda Motor conducts employee performance appraisals every year. The assessment is carried out annually where each employee will be given a score which is divided into 2 categories, namely the Work Outcome Category and the Process and Work Attitude Category. In the performance appraisal process, it is still done manually using the provided form so that errors often occur in providing final results in employee performance appraisals and also take a long time. The AHP method and the Moora method are one of the methods of decision support systems, where the AHP method is used to determine the weights for each assessment criteria, while the Moora method is used to calculate employee performance appraisals through the stages of employee performance appraisal applications at PT. Astra Honda Motor Bengkulu was created to help make it easier to manage employee data and evaluate employee performance. This employee performance appraisal application can help process employee performance appraisal data at PT. Astra Honda Motor Bengkulu and can provide information on the results of employee performance appraisals based on the calculation of the Moora Method and the Weighting Criteria of the AHP Method. Based on the employee performance appraisal test data as many as 13 people, the results of the employee performance appraisal who have the highest score are Anita with the results of the Moora Method 55.94. Based on the black box testing that has been done, the results show that the functionality of the application runs as expected and the application is able to display the results of employee performance assessments through the stages of the Moora Method.

Comparisonal Analysis of K-Means and Fuzzy . Algorithm C-Means in Clasterization of Poor Population Data at Rawa Makmur

2022-01-24T17:38:23+07:00

Rawa Makmur Village is one of the villages located in Muara Bangkahulu District, Bengkulu City. So far, the process of processing data on the poor at the Rawa Makmur Village Office is still done manually, namely by conducting a survey of each resident, and providing an assessment of whether the population is categorized as poor or not. However, because the data collection process is still manual, it is difficult for the Rawa Makmur Village to manage the data because it takes a long time. Therefore, a system development was carried out by creating applications that could simplify the process of managing data for the poor in Rawa Makmur Village. The application for clustering data for the poor in Rawa Makmur Village was made using the Visual Basic .Net programming language and SQL Server 2008 database by applying two data mining methods, namely the K-Means Algorithm and the Fuzzy C-Means Algorithm. The grouping is done based on the income and the number of the insured from the data obtained at the Rawa Makmur Village Office. Based on the processing time, the Fuzzy C-Means Algorithm is faster than the K-Means Algorithm in the data clustering process because the K-Means Algorithm has repeated iterations until the final cluster result is found while the Fuzzy C-Means does not have iterative iterations. Based on the results of clusters on the data of the poor as many as 440 people, there are differences in cluster results where the K-Means Algorithm has Cluster 1 (65 people), Cluster 2 (334 people), Cluster 3 (41 people), while the Fuzzy C-Means Algorithm has Clusters. 1 (147 people), Cluster 2 (136 people), Cluster 3 (157 people). From the results of the comparative analysis between the K-Means Algorithm and the Fuzzy C-Means Algorithm, it is found that the K-Means Algorithm is more recommended for classifying poor population data than the Fuzzy C-Means Algorithm because the average value of each cluster does not differ too much, and is still significant according to with data on the poor

Quality of Service (QOS) Analysis of Video Services Youtube Stream on Wireless Network

2022-01-24T17:38:23+07:00

The Indonesian Evangelical Christian Church (GKII) Tebeng Bengkulu is a place of worship for Christians who use internet network services to support the ongoing process of worship activities. With the increasing need for internet, especially on Youtube video streaming, there is a need for network analysis at the Tebeng Bengkulu Indonesian Evangelical Christian Church (GKII) Worship Building to determine the Quality of Service (QoS) on the Wireless network at the Indonesian Evangelical Christian Church (GKII) Tebeng Bengkulu. This study uses the Action Research method. QoS measurement carried out at the Indonesian Evangelical Christian Church (GKII) Tebeng Bengkulu using Wireshark software. The method used to measure QoS parameters is by connecting the server computer device to the internet via a wireless network and then streaming YouTube videos during the worship procession. Meanwhile, to find out the performance of the internet network at the Indonesian Evangelical Christian Church (GKII) Tebeng Bengkulu. Measurements were made on the parameters of QoS, delay, jitter, packet lost, and throughput, based on the results of the research, the internet network at the Indonesian Evangelical Christian Church (GKII) Tebeng Bengkulu was in the medium category

Application of Moora Method in Teacher Performance Assessment at SMKN 3 Bengkulu City

2022-01-24T17:38:23+07:00

Every school must have a Teacher Performance Assessment (PKG), one of which is SMK Negeri 3 Bengkulu. At this school, teacher performance assessments are carried out annually based on predetermined criteria. However, in the assessment process it is still done manually, the impacts that occur are errors in giving grades and differences in understanding between teachers because they feel less satisfied and inaccurate grades, causing instability in the teaching and learning process as well as gaps between teachers in schools. The teacher performance assessment application at SMK Negeri 3 Bengkulu City is an application that is used to facilitate the process of managing teacher performance assessment data in schools, where this application is made using the Visual Basic .Net programming language and SQL Server 2008r2 database. In this application, one of the Decision Support System Methods (DSS) has been applied, namely the Moora Method, so that the final result of the evaluation of teacher performance assessment is based on the calculation of the Moora Method. This can be used as an alternative in helping the school to add additional benchmarks for evaluating teacher performance assessment through the Moora Method approach which is calculated computerized so that the final score for each teacher will be made a ranking of the highest value to the lowest value. Based on the results of black box testing, the functionality of the teacher performance appraisal application at SMK Negeri 3 Bengkulu City has been running as it should and is able to display the final results of the teacher performance assessment based on the Moora Method process.