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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. 3 (September 2020)" : 5 Documents clear
Prediksi Tingkat Ketersediaan Stock Sembako Menggunakan Algoritma FP-Growth dalam Meningkatkan Penjualan Aditiya, Rahmad; Defit, Sarjon
Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 3 (September 2020)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (397.076 KB) | DOI: 10.37034/infeb.v2i3.44

Abstract

Large data sets can be processed to become useful information, one of the data that can be processed is sales transaction data at UD. Smart Aliwansyah, which will become important information to increase sales. This study aims to find the pattern of product purchases to predict the level of availability of staple foods so as to increase sales. The data that is processed in this study uses the sales transaction data of goods obtained from the sales invoice of UD. Smart Aliwansyah, North Sumatra Tax Village. Based on these data, with the provision that a minimum of 2 types of goods in 1 transaction is examined using a data mining technique in association with the FP-Growth algorithm with a confidence value of 75% and a minimum support of 20%. The tools used by Rapidminer 9.4 are to obtain product purchasing patterns which are used as information to predict the level of stock availability. The result of the sales data processing process is the association rule. Association Rule is obtained in the form of a relationship between goods sold together with other goods in a transaction. From this pattern, it can be recommended to the shop owner as information for preparing basic food stocks to increase sales results. This research is very suitable to be applied to determine the patterns of consumer spending such as the relationship of each item purchased by consumers, so this research is appropriate for use by grocery stores.
Simulasi Monte Carlo dalam Memprediksi Tingkat Pendapatan Advertising Mulyana Putra, Beni
Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 3 (September 2020)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (441.011 KB) | DOI: 10.37034/infeb.vi0.45

Abstract

Fulfilling consumer needs is the goal of every business. Owned business capital will affect the readiness to serve consumer demand. The purpose of this study is to predict the level of advertising revenue at Vand Advertising Printing in order to facilitate business owners in preparing business strategies quickly and optimally. This research data is income data from January 2017 to December 2019 which is modeled using the Monte Carlo method. Income level prediction will be carried out annually. Based on the results of the tests that have been done, it is found that the system used to predict the level of advertising revenue with an average accuracy of 90%. The high level of accuracy means that the application of the Monte Carlo method is considered able to predict the level of advertising revenue each year. So that it can make it easier for business owners to choose the right business strategy to increase advertising revenue.
Simulasi Monte Carlo dalam Memprediksi Disribusi Kopi Starbuck Irawan, Dedi; Sumijan; Nurcahyo , Gunadi Widi
Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 3 (September 2020)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (327.454 KB) | DOI: 10.37034/infeb.vi0.46

Abstract

Distributing and marketing Starbuck coffee is a very important part of the company PT Vision Logistik Transindo in increasing a profit. Starbuck is a company originating from the United States headquartered in Seattle, Washington, and already has the world's largest coffee shop with 20,336 stores in 61 countries, including Indonesia. In distribution management it is very necessary to determine the Starbuck coffee needed, so that customer demand can be fulfilled. This study conducted data on Starbucks coffee distribution from 2017 to 2019. The data processing in this case uses the Monte Carlo algorithm to predict the distribution of Starbuck coffee. In accelerating data processing, this study applies a Web-based program with the PHP programming language (Hypertext Processor). The result of the test is to get the predicted results of Starbuck coffee with an accuracy level of 90%. So that the results obtained can help the company PT.Vision Logistik Transindo in increasing distribution in the coming year.
Simulasi Monte Carlo dalam Prediksi Tingkat Penjualan Produk HPAI Dari, Rahmatia Wulan
Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 3 (September 2020)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (317.344 KB) | DOI: 10.37034/infeb.vi0.48

Abstract

Predicting sales is an important aspect of sales development. Sales prediction simulation is an estimate about calculating the level of product sales in a certain period. The research objective was to predict the level of sales of HPAI products at HNI Halal Mart. The data used is sales data for HPAI products from 2017 to 2019 which are processed using the Monte Carlo method. Based on the results of testing the prediction of the sales level of HPAI products, an average accuracy of 84,5% is obtained, making it easier in the decision making process and helping in choosing a good business strategy.
Simulasi Monte Carlo dalam Memprediksi Tingkat Lonjakan Penumpang Mardiati, Dina
Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 3 (September 2020)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (396.9 KB) | DOI: 10.37034/infeb.vi0.49

Abstract

Tri Arga Travel is a company engaged in transportation services. The company really prioritizes the quality of service to consumers. So that on holidays there is usually a surge in passengers that cannot be predicted by the company. This greatly affects service to passengers. The purpose of this research is to predict the surge rate of PT. Tri Arga Travel, making it easier for the leadership of PT. Tri Arga Travel to take a policy when there is a surge in passengers in the future. The data used in this study is data on the number of passengers in 2017, 2018, and 2019 with the aim of padang-perawang. Then, the data is processed using the Monte Carlo method. The Monte Carlo method is a simulation method that uses random numbers obtained from the Linear Congruential Generator (LCG) to predict the rate of passenger spike in the following year by utilizing the previous year's passenger data. The results obtained from testing the Monte Carlo simulation can be seen that in July it is predicted that there will be a surge in passengers with an average level of accuracy of 86.74%. With a fairly high level of accuracy, the application of the Monte Carlo method can be used as a recommendation to predict the level of passenger spikes and also help in improving services to prospective passengers of PT. Tri Arga Travel.

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