cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Arrianda Mardhika Adif
Contact Email
jmraahome@gmail.com
Phone
+6287895670026
Journal Mail Official
infeb03@gmail.com
Editorial Address
Kampus UNAND Limau Manis Padang
Location
Kota padang,
Sumatera barat
INDONESIA
Jurnal Informatika Ekonomi Bisnis
Published by Asia Pacific Network for Sustainable Agriculture, Food and Energy
ISSN : 27148491     EISSN : 27148491     DOI : https://doi.org/10.37034/infeb
Core Subject : Economy,
Economics, Econometrics & Finance
The Jurnal Informatika Ekonomi Bisnis (INFEB) is an interdisciplinary journal. It publishes scientific papers describing original research work or novel product/process development. The objectives are to promote an exchange of information and knowledge in research work, and new inventions/developments on the use of Informatics in Economics and Business. This journal is useful to researchers, engineers, scientists, teachers, managers, and students who are interested in keeping a track of original research and development work being carried out in the broad area of informatics in economics and business through a scholarly publication.
Arjuna Subject : Ilmu Ekonomi, Ekonometrika dan Keuangan (semua kategori) - Ilmu Ekonomi, Ekonometrika dan Keuangan (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 2, No. 1 (March 2020)" : 5 Documents clear
Prediksi Optimal dalam Produksi Bata Merah Menggunakan Metode Monte Carlo Zalmadani, Hendro; Santony, Julius; Yunus, Yuhandri
Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 1 (March 2020)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (353.701 KB) | DOI: 10.37034/infeb.v2i1.11

Abstract

The availability of red bricks on the market is a problem that must be addressed. Because the availability of red brick affects sales revenue. The purpose of this research in the Small and Medium Micro Business of the Red Brick City of Pariaman is to predict the production of red bricks to find out income and find out the next production. So this research can make it easier for business owners to find out how much it will cost for the next production cost. The data used in this study are production data from 2017 to 2019 which are processed using the Monte Carlo method. Based on the results of production prediction testing that has been done, it is found that the average accuracy is 90%. With the results of a high degree of accuracy, the application of the monte carlo method is considered to be able to predict production annually. Making it easier for business owners to determine the costs incurred in the next production process.
Kinerja Karyawan Ditinjau dari Kepuasan Kerja, Kecerdasan Emosional dan Stres Kerja Rahmadani, Sari; Moeins, Anoesyirwan; Yulasmi
Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 1 (March 2020)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (294.077 KB) | DOI: 10.37034/infeb.v2i1.14

Abstract

This study aims to determine how much influence job satisfaction, emotional intelligence, and work stress on employee performance at PT. Padang Broad Bay. The method of collecting data through surveys and distributing questionnaires. The sample was 144 respondents and the analytical method used was regression analysis and correlation analysis. Based on the results of multiple regression analysis, the equation Ŷ = 21.790 + 0.256X1 + 0.615X2 - 0.482X3 is obtained. There is a positive and significant effect between job satisfaction (X1) on employee performance (Y), with a tcount of thitung 3.697 or a significantly smaller level than alpha (0,000 <0.05). Then there is a positive and significant effect between emotional intelligence (X2) on employee performance (Y), with a tcount of thitung 8.426 or a significantly smaller level than alpha (0,000 <0.05). Furthermore there is a negative and significant effect between work stress (X3) on employee performance (Y), with t hitung -3,697 or a significant level smaller than alpha (0,000> 0.05). Finally there is a significant influence between job satisfaction (X1), emotional intelligence (X2) and work stress (X3) together on employee performance (Y). There is also a strong relationship between each of these variables with a count of fhitung 75.486 or significantly smaller levels from alpha (0,000 <0.05).
Analisis Kinerja Karyawan Ditinjau dari Gaya Kepemimpinan, Disiplin Kerja, dan Motivasi Kerja Prinaldi; Elfiswandi; Ismuhadjar
Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 1 (March 2020)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (290.147 KB) | DOI: 10.37034/infeb.v2i1.16

Abstract

This study aims to find out how much the analysis of employee performance in terms of work discipline, work motivation and leadership style at Kodim 0307 Tanah Datar. Data collection methods through surveys and questionnaires. Total sample of 121 respondents. The analytical method used is regression analysis and correlation analysis. Based on the results of multiple regression analysis, the equation Ŷ = 7.054 + 0.426 X1 + 0.186 X2 + 0.274 X3. There is a positive and significant influence between leadership style (X1) on employee performance (Y), with t count 0.426 or significantly lower than alpha (0.000<0.05). Then a positive and significant effect between work discipline (X2) on employee performance (Y), with a t count of 0.186 or a significant level smaller than alpha (0.012<0.05). There is a positive and significant influence between work motivation (X3) on employee performance (Y), with tcount 0.274 or significantly lower than alpha (0.001>0.05) and significant influence between leadership style (X1), work discipline (X2 ) and work motivation (X3) together on employee performance (Y) as well as a strong relationship between each of these variables with f count 28,534 or a significantly smaller level than alpha (0,000 <0.05).
Pemetaan Promosi dalam Penjaringan Calon Mahasiswa Menggunakan Algoritma Backpropagation Kurniawan, Mhd Hary; Defit, Sarjon
Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 1 (March 2020)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (430.35 KB) | DOI: 10.37034/infeb.v2i1.17

Abstract

Promotion requires a large fee if it is not targeted when doing it. Backpropagation is an excellent method of dealing with the problem of recognizing complex patterns. Backprogation neural network each unit in the input layer is connected to each unit in the hidden layer. Student data from 2014 to 2018 is a comparison point. The results of testing of this method are calculations using a sample value of 5 years before using a comparative value of 2014 to 2018 totaling 602 data. This research uses 5-5-1 architecture, epoch 2000 and learning rate so that the data accuracy reaches 71% with an error value of 0.0099. The results of this study are 16 districts that become promotion recommendations. Ordering of forecasting the highest number of students to the smallest number of students, so it can be concluded that this method is very useful in mapping promotions.
Objektivitas Sumber Daya Dosen Menggunakan Metode Weight Product Putra, Deri Marse; Nurcahyo, Gunadi Widi
Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 1 (March 2020)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (273.777 KB) | DOI: 10.37034/infeb.v2i1.20

Abstract

Lecturers as one of the human resources who have an important role in higher education activities need to be maintained the quality of their performance. One of the activities carried out is evaluating and ranking lecturers to improve the quality of performance. There needs to be a Decision Support System that can help in assessing and evaluating lecturer performance. One method in decision support is the Weight Product Method. The purpose of this research is to create a decision support system to determine the best lecturers and rank of each lecturer. The subjects of this study were lecturers at Putra Indonesia University YPTK Padang using a data sample of 5 lecturers. Data collection techniques used in this study were observation and interviews. Comparison of the results of calculations carried out manually with the results of calculations using the Weight Product method of 5 sample data used found the best lecturer with a vector V value of 0.0819. This decision support system was created using the PHP programming language and MySQL database. So that this research is more efficient because the time required in the calculation is shorter and produces the best lecturer choice that matches the criteria.

Page 1 of 1 | Total Record : 5

 1 

Filter by Year

2020 2020


Reset
Filter By Issues
All Issue Vol. 7, No. 4 (December 2025): Accepted Vol. 7, No. 3 (September 2025) Vol. 7, No. 3 (September 2025): Accepted Vol. 7, No. 2 (June 2025) Vol. 7, No. 1 (March 2025) Vol. 6, No. 4 (December 2024) Vol. 6, No. 3 (September 2024) Vol. 6, No. 2 (June 2024) Vol. 6, No. 1 (March 2024) Vol. 5, No. 4 (December 2023) Vol. 5, No. 3 (September 2023) Vol. 5, No. 2 (June 2023) Vol. 5, No. 1 (March 2023) Vol. 4, No. 4 (December 2022) Vol. 4, No. 3 (September 2022) Vol. 4, No. 2 (June 2022) Vol. 4, No. 1 (March 2022) Vol. 3, No. 4 (December 2021) Vol. 3, No. 3 (September 2021) Vol. 3, No. 2 (June 2021) Vol. 3, No. 1 (March 2021) Vol. 2, No. 4 (December 2020) Vol. 2, No. 3 (September 2020) Vol. 2, No. 2 (June 2020) Vol. 2, No. 1 (March 2020) Vol. 1, No. 4 (December 2019) More Issue