Jurnal Informatika Ekonomi Bisnis
Jurnal Informatika Ekonomi Bisnis adalah Jurnal Nasional, yang didedikasikan untuk publikasi hasil penelitian yang berkualitas dalam bidang Informatika Ekonomi dan Bisnis, namun tak terbatas secara implisit. Jurnal Informatika Ekonomi Bisnis menerbitkan artikel secara berkala 4 (empat) kali setahun yaitu pada bulan Maret, Juni, September, dan Desember. Semua publikasi di jurnal ini bersifat terbuka yang memungkinkan artikel tersedia secara bebas online tanpa berlangganan.
Jurnal Informatika Ekonomi Bisnis sebagai media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis dalam bidang informatika ekonomi dan bisnis. Sebagai bagian dari semangat menyebarluaskan ilmu pengetahuan hasil dari penelitian dan pemikiran untuk pengabdian pada masyarakat luas, serta sebagai sumber referensi akademisi dalam bidang informatika ekonomi dan bisnis.
Articles
283 Documents
<![CDATA[Optimalisasi Penggunaan Lahan Perkebunan Kelapa Hibrida Menggunakan K-Means Clustering ]]>
<![CDATA[Henky Andema]]>;
<![CDATA[Sarjon Defit]]>;
<![CDATA[Yuhandri Yunus]]>
<![CDATA[ Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 2 (2020) ]]>
Publisher : <![CDATA[SAFE-Network ]]>
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DOI: 10.37034/infeb.v2i2.23
<![CDATA[Plantations are the main source of income for farmers in Indragiri Hilir Regency. This plantation is the plantation sector most widely cultivated by farmers is a coconut plantation. The best grouping of coconut cultivation areas is important in developing farmers' income. This study aims to help the Plantation Office in the process of making the best decision areas for planting coconut, especially hybrid coconut. The data used in this study is the data of hybrid coconut plantations in 2018. Data processing in this study uses the K-Means Clustering method with the number of 3 Clusters namely Cluster 0 (C0) Less Potential, Cluster 1 (C1) Enough Potential, Cluster 2 (C2) Very Potential for planting hybrid coconuts. The results of the clustering process with 2 iterations stated that for Cluster 0 there were 7 village data, for Cluster 1 there were 1 village data, and for Cluster 2 there were 2 village data.]]>
<![CDATA[Sistem Informasi Inventory dengan Metode Economy Order Quantity dan Reorder Point pada Persediaan Barang Dagang ]]>
<![CDATA[Febria Sylvana]]>;
<![CDATA[Hari Marfalino]]>
<![CDATA[ Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 2 (2020) ]]>
Publisher : <![CDATA[SAFE-Network ]]>
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DOI: 10.37034/infeb.v2i2.35
<![CDATA[CV. Muaro Radio is a trading company that meets the needs of the community for the needs of electronic goods. All traded goods are imported from distributors in the form of not built up. So it takes time to assemble (production) before being marketed. This process will hamper sales if the goods are not available. So, this research helps companies in maintaining the stability of the availability of goods in order to increase sales. The method used is Economy Order Quantity and Reorder Points. The data that is processed is inventory data and the sale of goods every day. The results of this study can maintain the supply of goods very well in managing stock of goods. So this research is very helpful for CV. Muaro Radio in increasing the company's revenue.]]>
<![CDATA[Sistem Pemasaran, Transaksi dan Persediaan Barang dengan Komputerisasi Berbasis Web ]]>
<![CDATA[Fanni Handayani]]>
<![CDATA[ Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 2 (2020) ]]>
Publisher : <![CDATA[SAFE-Network ]]>
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DOI: 10.37034/infeb.v2i2.38
<![CDATA[Azwa Perfume is a goods trading business. Goods that are traded are various types of perfume. At this time Azwa Perfume's trading income is difficult to grow with the lack of increasing variety of buyers. So this research was carried out to build a system that can introduce types of perfume globally and real time data processing. The method used is to build an online system by applying Economic Order Quantity (EOQ) and Reorder Point (RP) to maintain supply stability. The results of this study can further introduce the types of perfume online and buyers can place orders online. The inventory can be controlled at any time so that every buyer who needs a type of perfume can be served quickly and precisely. So this research really helps in marketing, sales transactions and controlling inventory very well.]]>
<![CDATA[Pemetaan Wilayah Potensial Terhadap Penjualan Sepeda Motor Honda Menggunakan K-Means Clustering ]]>
<![CDATA[Zulrahmadi]]>
<![CDATA[ Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 2 (2020) ]]>
Publisher : <![CDATA[SAFE-Network ]]>
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DOI: 10.37034/infeb.v2i2.41
<![CDATA[Indragiri Hilir regency consists of land and water which are divided into 20 districts, 39 sub-districts and 197 villages. Looking at the geographical condition of Indragiri Hilir Regency, motorcycle sales companies need to know the areas that have potential for motorcycle sales. Grouping potential areas is important in increasing sales profit for the company. This study aims to help PT. Capella Dinamik Nusantara in making the decision to increase sales to be more significant, promotion and marketing techniques were more targeted towards Honda motorcycle sales in the mapped areas. The data used in this study are Honda motorcycle sales data from 2017 to 2019. Data processing in this study uses the K-Means Clustering method with 3 clusters, namely Cluster 0 (C0) Less Potential, Cluster 1 (C1) Enough Potential, Cluster 2 (C2) Has the potential to sell Honda motorcycles. The result of the grouping process with 2 iterations states that for Cluster 0 there are 5 regions, for Cluster 1 there are 3 regions, and for Cluster 2 there are 2 regions.]]>
<![CDATA[Akurasi dalam Memprediksi Penetapan Besaran Anggaran Proposal Pendapatan dan Belanja Universitas Menggunakan Metode Monte Carlo ]]>
<![CDATA[Yogo Turnandes]]>
<![CDATA[ Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 2 (2020) ]]>
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DOI: 10.37034/infeb.v2i2.42
<![CDATA[The Institute for Research and Community Service at the University of Lancang Kuning has the mandate in research and service activities which are the two dharmas of the Tri Dharma of Higher Education. The purpose of this study is to predict the determination of the budget amount for the University Income and Expenditure Budget (APBU) proposal approved at LPPM Unilak for the following year. Thus, it will make it easier for the LPPM leadership to make decisions on the acceptance of APBU proposals that are approved quickly and optimally. The data used in this research is APBU research and service proposal data approved in 2018 to 2020 which is processed using the monte carlo method. The APBU proposal budget prediction will be carried out every year. Based on the results of tests that have been carried out with the monte carlo method, it is found that the system used to predict the amount of APBU proposal budget approved in 2019 with an average accuracy of 84% and in 2020 with an average accuracy of 73%. Then with a fairly high level of accuracy, the application of the Monte Carlo method is considered to be able to predict the amount of the APBU proposal budget that is approved by each faculty each year.]]>
<![CDATA[Prediksi Tingkat Ketersediaan Stock Sembako Menggunakan Algoritma FP-Growth dalam Meningkatkan Penjualan ]]>
<![CDATA[Rahmad Aditiya]]>;
<![CDATA[Sarjon Defit]]>
<![CDATA[ Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 3 (2020) ]]>
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DOI: 10.37034/infeb.v2i3.44
<![CDATA[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.]]>
<![CDATA[Simulasi Monte Carlo dalam Memprediksi Tingkat Pendapatan Advertising ]]>
<![CDATA[Beni Mulyana Putra]]>
<![CDATA[ Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 3 (2020) ]]>
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DOI: 10.37034/infeb.vi0.45
<![CDATA[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.]]>
<![CDATA[Simulasi Monte Carlo dalam Memprediksi Disribusi Kopi Starbuck ]]>
<![CDATA[Dedi Irawan]]>;
<![CDATA[Sumijan]]>;
<![CDATA[Gunadi Widi Nurcahyo]]>
<![CDATA[ Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 3 (2020) ]]>
Publisher : <![CDATA[SAFE-Network ]]>
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DOI: 10.37034/infeb.vi0.46
<![CDATA[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.]]>
<![CDATA[Simulasi Monte Carlo dalam Prediksi Tingkat Penjualan Produk HPAI ]]>
<![CDATA[Rahmatia Wulan Dari]]>
<![CDATA[ Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 3 (2020) ]]>
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DOI: 10.37034/infeb.vi0.48
<![CDATA[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.]]>
<![CDATA[Simulasi Monte Carlo dalam Memprediksi Tingkat Lonjakan Penumpang ]]>
<![CDATA[Dina Mardiati]]>
<![CDATA[ Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 3 (2020) ]]>
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DOI: 10.37034/infeb.vi0.49
<![CDATA[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.]]>
