Article Per Year (5 Year)
p-Index From 2021 - 2026
0.817
P-Index
This Author published in this journals
All Journal ILKOM Jurnal Ilmiah INCODING: Journal of Informatics and Computer Science Engineering Jurnal Media Computer Science
Beti, Ila Yati
Unknown Affiliation
Computer Science & IT

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 5 Documents
Search

 1 
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN KARYAWAN TERBAIK MENGGUNAKAN SIMPLE ADDITIVE WEIGHTING Beti, Ila Yati
ILKOM Jurnal Ilmiah Vol 11, No 3 (2019)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v11i3.480.252-259

Abstract

Human Resources is an important asset in the company to be able to achieve company goals, the selection of the best employees is a way that companies do to motivate employee performance. Company leaders usually have difficulty in evaluating employee performance with various assessment indicators available. This results in decisions that are not objective, to be able to process the best employee selection data that is more accurate and more objective results. Then the Decision Support System is needed in the selection of the best employees. In this study there were 25 Alternative Employees who had met the best employee selection requirements that were processed using the Simple Additive Weighting method and based on 5 assessment criteria, namely the criteria of loyalty, responsibility, behavior / ethics, cooperation, and attendance. From the results of the calculation of the SAW method obtained a top 10 ranking and also obtained that employee work loyalty is very influential on the calculation results with a weight of 30% of the overall weight.
Decision Support System For Recommending Expertise Programs Using Ahp Method Setiawan, Alfin; Asnawati, Asnawati; Beti, Ila Yati
Jurnal Media Computer Science Vol 4 No 1 (2025): Januari
Publisher : Fakultas Ilmu Komputer Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v4i1.7533

Abstract

SMK Negeri 3 Kota Bengkulu is a Vocational High School located in Bengkulu Province. At SMK Negeri 3 Kota Bengkulu there are 5 (five) Expertise Programs that can be selected by new students including Culinary, Fashion, Beauty and Spa, Computer Network and Telecommunication Engineering (TJKT) and Broadcasting and Film. Every new student who wants to register must choose one of the expertise programs available at SMK Negeri 3 Bengkulu City. The decision support system in providing recommendations for expertise programs using AHP Method can help provide recommendations for expertise programs that are appropriate and in accordance with the assessment criteria for prospective new students and can be used as a forum to assist schools for recommending the expertise programs of prospective new students at SMK Negeri 3 Bengkulu City. A decision support system for recommending expertise programs using the AHP Method is built web-based applications that can be accessed offline. Based on system testing that has been carried out, it can be concluded that the functional of the decision support system application for recommending expertise programs using AHP Method has run well and has successfully carried out AHP Method process on prospective student value data according to the school year and provides information on the results of the expertise program recommendations for each prospective student.
A Decision Support System For The Selection Of The Best Employees At CV. Adiguna By Applying The Preferences Selection Index Method Putra, Repal Kesatria; Yupianti, Yupianti; Beti, Ila Yati; Lianda, Deri
Jurnal Media Computer Science Vol 2 No 1 (2023): Januari
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v2i1.3440

Abstract

Technological Developments at this time, competition in the business world is getting tougher, to support this, companies must also improve their quality. On CV. Adiguna to increase the resources of his employees in improving the quality of his company is of course supported and influenced by the performance of employees who are competent in their field. Where in CV. Adiguna of Bengkulu City in giving awards to the best employees every year so far it is still done manually, this can certainly increase the enthusiasm of employees at work and always run a business by fulfilling several criteria set by CV Adiguna of Bengkulu City. Therefore to provide an objective assessment of employee performance, a Decision Support System is needed to select the best employees and provide rewards to employees, then to support the above, it is necessary to implement several Decision Support Systems at CV Adiguna of Bengkulu City based on the criteria that have been determined by the management of CV Adiguna of Bengkulu City. Decision support system for selecting the best employees at CV Adiguna of Bengkulu City by applying the Preferences Selection Index method is a desktop-based application that has implemented the Preferences Selection Index (PSI) method. This application can be used to assist in the process of selecting the best employees on CV Adiguna of Bengkulu City uses 5 predetermined criteria, then the assessment of these 5 criteria is processed using the Preferences Selection Index (PSI) method to produce a ranking that will be used to determine the best employee. Based on the results of the tests that have been carried out, it can be concluded that the decision support system for selecting the best employees at CV Adiguna of Bengkulu City by applying the Preferences Selection Index method is able to run well and can overcome data input errors besides that calculations are done manually with those carried out by the application producing the same output.
Application Of Mamdani Fuzzy Logic To Predict Rice Pest Attacks On Bp3 Bingin Kuning Reynaldi, Abdillah Ahmad; Sapri, Sapri; Beti, Ila Yati
Jurnal Media Computer Science Vol 4 No 2 (2025): Juli
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v4i2.8930

Abstract

The Agricultural and Fisheries Extension Centre (BP3) Bingin Kuning is an agricultural extension centre that carries out activities related to agricultural extension preparation, evaluation, management, and development across various sectors. Every year, BP3 Bingin Kuning collects data on temperature, humidity, rainfall, and the number of attacks by each type of pest that occurs. The application of Mamdani fuzzy logic to predict rice pest infestations at BP3 Bingin Kuning can help in obtaining information on rice pest infestations each year, serve as a basis for evaluating measures to address future pest infestations, and assist farmers in addressing potential pest infestations earlier, thereby supporting BP3 Bingin Kuning in its agricultural extension activities. Based on test data under conditions of 24°C temperature, 90% relative humidity, and 295 mm rainfall in 2024, the pest type with the highest predicted attack frequency is the Keong Mas pest. Based on the system testing conducted, it can be concluded that the functionality of the Mamdani fuzzy logic application for predicting rice pest attacks at BP3 Bingin Kuning is functioning well and capable of displaying pest attack prediction results in accordance with the stages of the Mamdani fuzzy logic system.
Implementasi Metode K-Means Clustering Untuk Pengelompokan Data Penjualan Pada Minimarket Remaja Kampus Bengkulu Aprinsa, Roki; Siswanto, Siswanto; Beti, Ila Yati
INCODING: Journal of Informatics and Computer Science Engineering Vol 2, No 2 (2022): INCODING OKTOBER
Publisher : Mahesa Research Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34007/incoding.v2i2.302

Abstract

Campus Youth Minimarket is one type of business in the field of selling daily necessities. For decision making in determining the amount of product inventory that can be adjusted to market demand, the Campus Youth Minimarket has not used the system and is still calculated manually. Therefore, this research was conducted with the aim of implementing the K-means Clustering method in grouping sales data at the Bengkulu Campus Youth minimarket. So that it can easily determine and classify high, medium and low product sales. The implementation of the system uses the PHP programming language and MySQL database and the method used in this research is the waterfall method. After the K-means process was carried out at the Campus Youth Minimarket with 15 data data tests, 3 clusters of goods were obtained, namely cluster 1 as a high sales cluster with 7 items, cluster 2 with moderate sales of 4 items and 4 items in a low sales cluster. Based on the results of processing 278 data on sales of goods in December 2021 at the Campus Youth Minimarket using the K-Means Clustering Method, the results of the grouping of product sales levels at the Bengkulu Campus Youth Minimarket were 3 clusters. Namely cluster 1 group with a high level of product sales with a total of 54 product data, cluster 2 with a moderate level of product sales with 165 types of products and cluster 3 with a low level of product sales with 51 total products. Based on the data cluster, it can be used as a reference by the Campus Youth Minimarket for the following month's product inventory. Which product clusters that have a high level of sales have a high or stable number of orders as before. Then product clusters with low sales levels, then the amount of product inventory for the next is reduced so that there is no accumulation of products in the warehouse and experiencing expiration.
Co-Authors Aprinsa, Roki Asnawati Asnawati Lianda, Deri Putra, Repal Kesatria Reynaldi, Abdillah Ahmad S Siswanto sapri sapri Setiawan, Alfin Yupianti, Yupianti