Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal EDUMATIC: Jurnal Pendidikan Informatika
Siagian , Yessica
Unknown Affiliation
Computer Science & IT Education

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Sistem Forecasting Permintaan Tempe menggunakan Metode Weighted Moving Average Meliani, Sefty; Siagian , Yessica; Ananda, Ricki
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.25632

Abstract

Information systems are created in stores in order to easily process data and produce the information needed quickly, accurately, precisely, effectively, and efficiently, reducing spending costs. The purpose of this study is to produce a forecasting system for tempeh demand to suit consumer needs when marketed. This type of research is research and development using the waterfall model. This model consists of stages of analysis, design, implementation, and testing. The analysis was conducted to obtain the needed data regarding tempeh using the weighted moving average (WMA) method. While we make this design, such as flowcharts, use cases, and data flow diagrams, Furthermore, the implementation of the women's tempeh factory was carried out, and testing was carried out using black box testing. The data we use is request data from September 29, 2023, to December 23, 2023. Our findings show that the mean absolute percentage error (MAPE) to predict tempeh demand is 3.83%; this result is quite small, so the accuracy rate obtained is 96.17%. In addition, the results of the system we developed are also in accordance with the results of manual calculations. This is also evidenced by the absence of errors that occur after testing using black box testing. So that this system can be used to manage tempeh, it is ready to be marketed by the female tempeh factory.
Sistem Pendukung Keputusan menggunakan Metode Topsis untuk Seleksi Guru Terbaik Fransiska, Rani; Siagian , Yessica; Rohminatin, Rohminatin
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.25747

Abstract

The process of selecting the best teachers is an important aspect of ensuring optimal quality of education in a school. However, the selection process for the best teachers at SMPN 5 Kisaran often faces obstacles such as subjectivity, lack of efficiency, and lack of transparency. This research aims to produce a decision support system using the TOPSIS method to increase objectivity and effectiveness in the teacher selection process, as well as contribute to improving the quality of education. This research is a development type using waterfall, including analysis, design, coding, testing, and implementation stages. The analysis stage is to identify system requirements, the design stage is to determine the system interface, the coding stage is to build the system, and the testing stage is to validate its functionality using a black box. Teacher performance data was collected through interviews, observation, and documentation studies. Teacher performance data will be analyzed using the TOPSIS method, which involves stages of weighting criteria, calculating relative scores, and ranking teachers based on the highest scores. The results of our findings are in the form of a decision support system application for selecting the best teachers. The test results show that this system is running well and by the design and model that has been planned. With this system, it can help SMPN 5 Kisaran in selecting the best teachers.
Co-Authors Fransiska, Rani Meliani, Sefty Ricki Ananda Rohminatin, Rohminatin