cover
Contact Name
Prof. Dr. H. Jufriadif Na`am, S.Kom, M.Kom
Contact Email
jufriadifnaam@upiyptk.ac.id
Phone
+6287895670026
Journal Mail Official
infeb@upiyptk.ac.id
Editorial Address
Kampus Universitas Putra Indonesia YPTK Padang Jl. Raya Lubuk Begalung Padang, Sumatera Barat - 25221
Location
Kota padang,
Sumatera barat
INDONESIA
Jurnal Informatika Ekonomi Bisnis
ISSN : 27148491     EISSN : -     DOI : https://doi.org/10.37034/infeb
Core Subject : Economy,
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 7 Documents
Search results for , issue "Vol. 3, No. 3 (2021)" : 7 Documents clear
Optimalisasi Penggunaan Anggaran dalam Menunjang Proses Tri Darma Pendidikan pada Perguruan Tinggi Frinosta, Ewif
Jurnal Informatika Ekonomi Bisnis Vol. 3, No. 3 (2021)
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v3i3.78

Abstract

Higher education has an obligation to carry out education, research, and community service based on the tridarma of higher education. Adi Karya Technical Academy (ATAK) is one of the private universities in Kerinci Regency, and also has a vision and mission that is in line with tridharma. To support the tridharma process of education in ATAK, it use of the budget needs to be optimized. Optimize the use of the budget, one processes that possible to do predictions budget's utilization. The data processed is the use of the 2017, 2018 and 2019 budgets at ATAK Universities. The result predections use budget's get it from simulation process the monte carlo are 89.79% for predictions in 2018, 84.73% for predictions for 2019 and 85.52% for 2020. In this case the monte carlo that possible apply to do predictions budget's utilization the following year.
Sistem Pendukung Keputusan terhadap Jenis dan Penerima dalam Penentuan Bantuan Desa Menggunakan Metode Simple Additive Weighting Nandes, Randi Afri
Jurnal Informatika Ekonomi Bisnis Vol. 3, No. 3 (2021)
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v3i3.85

Abstract

Sidoluhur Village is a village located in Padang Jaya District, North Bengkulu which has a large population. The his village has 3 hamlets in one village. The problem in Sidoluhur Village is that it is difficult to determine the recipient of village assistance, because the number of aid proposals that are proposing is more than the number of people who receive assistance. There are so many proposals that have been submitted, this is of course very troublesome for village officials who choose to receive assistance. As problems develop, a decision support system is needed that will provide results on the computer to determine who should get help. A decision support system is a system for finding decision support, decisions are taken using a system designed based on usage needs, in helping to make decisions, decisions are designed based on predetermined criteria and alternatives and have a system that is structured and programmed in the form of weighting that will be accumulated and normalized and produce ranking. This study uses the Simple Additive weighting method, commonly referred to as a method that uses a weighted additive form. The form of the method is to calculate the total weight value of the work steps on the existing alternatives of all attributes. To explain about the completion of the method uses village aid recipient data. A lot of data that will be used as alternatives in this study are 9 candidates for village aid recipients. As a result, the recipients of aid should not be less than 0.5000, with the result that 7 recipients of assistance and 2 people who are not eligible to receive assistance.
Sistem Penunjang Keputusan dalam Optimalisasi Pemberian Insentif terhadap Pemasok Menggunakan Metode TOPSIS Gunawan, Vicky Setia
Jurnal Informatika Ekonomi Bisnis Vol. 3, No. 3 (2021)
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v3i3.86

Abstract

Generally, every company must have an assessment of the supplier of materials in order to maintain the quality of their production. When a supplier gets a good rating, the company usually gives awards such as incentives to the supplier in the hope of increasing motivation, professionalism and good relations with the company. The determination of incentives is currently only based on analysis of existing data records manually, which may lead to errors. From previous observations, a decision support system was created in the optimization of incentives. This study aims to optimize the results of decisions in providing incentives to suppliers. The method used is Technique for Others Preference by Similarity to Ideal Solution (TOPSIS). This method can determine which suppliers are entitled to incentives. The data that is processed in this research comes from PT. Prima Beton Cakrawala. Price, Quality, Delivery, Service and Offer are the assessment criteria for determining incentive recipients. The results of the TOPSIS calculation process can find a more accurate alternative choice decision, because the alternative assessment is in accordance with the specified criteria. Based on the value of the criteria weight for the selection of incentive recipients for each alternative. The results of this study recommend A3 suppliers with a preference value of 0.646 as raw material suppliers who are entitled to receive incentives. Comparisons made between manual calculations and the system built get almost the same results. So that the level of accuracy is 95% accurate enough, so that it can produce factual decision data in order to assist companies in determining incentive recipients so as to increase the motivation of suppliers in providing services. So that it is expected that the leadership can use it as a reference for optimizing decisions on providing incentives.
Klasterisasi Teknik Promosi dalam Meningkatkan Mutu Kampus Menggunakan Algoritma K-Medoids Darma, Surya
Jurnal Informatika Ekonomi Bisnis Vol. 3, No. 3 (2021)
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v3i3.87

Abstract

Promotion technique is one of the methods used by AMIK and STIKOM Tunas Bangsa Pematangiantar in finding new students. By developing promotional techniques that are more effective and efficient, it can produce the information needed to get new student candidates. The data that is processed in this research is the data of new student candidates who come from the AMIK New Student Admissions (PMB) and STIKOM Tunas Bangsa Pematangsiantar. Based on promotional data in 2020, there are several promotions carried out, including through print media, banners, collaboration with SMA / SMK schools in Pematangsiantar city, through alumni, and the web. Furthermore, the data is processed using Rapidminer software. The processing stages are grouped using the K-Medoids algorithm on the data of prospective students, including name, place and date of birth, address, religion, cellphone number, school origin, choice of study program and source of information. Followed by the process of improving the data so that more accurate data is obtained to be processed. The results of the testing of this method are knowing which regions are applying to AMIK and STIKOM Tunas Bangsa Pematngsiantar which are grouped into 2 clusters, namely the highest and the lowest. The K-Medoids algorithm that is used makes a big contribution by providing new information that can be used as a reference for AMIK and STIKOM Tunas Bangsa Pematngsiantar in terms of Promoting New Student Admissions in the coming year.
Evaluasi Penentuan Kelayakan Pemberian Subsidi Listrik dengan Metode MFEP Yanto, Bobi Heri; Yunus, Yuhandri
Jurnal Informatika Ekonomi Bisnis Vol. 3, No. 3 (2021)
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v3i3.91

Abstract

The electricity subsidy program is a poverty control program that provides electricity subsidies to poor and underprivileged households that are paid by the Government of Indonesia to PT. PLN. The purpose of providing subsidies is to achieve a power supply and help poor customers and those who have not been contacted by PT. PLN so that they can enjoy electrical energy. At PT. Haleyora Power to determine the recipients of electricity subsidies there are still many mistakes such as not being on target, these subsidies are even obtained by people who are able to this incident not only in one period but often, because in the Decision Making System determining the eligibility of electricity subsidy recipients still uses a manual process and the database used is still in paper form in the form of files and there are no specific characteristics to be considered. This research aims to produce a system that can be used as a tool and makes it easier to determine the eligibility of electricity subsidy recipients. The method used in this research is the Multifactor Evaluation Process (MFEP) method. With the existence of a decision support system for determining eligibility assistance for electricity subsidies, the eligibility criteria will become clearer. The results of the ranking of 20 potential electricity subsidy recipients whose data are processed and produce a total calculation or accuracy of 100% using the Multifactor Evaluation Process (MFEP) method based on data on electricity subsidy recipients at PT. Haleyora Power. So that this research can be a reference in making the right decisions on providing electricity subsidies at PT. Haleyora Power.
Prediksi Peningkatan Jumlah Pelanggan dengan Simulasi Monte Carlo Anggraini, Siska Dwi; Nurcahyo, Gunadi Widi
Jurnal Informatika Ekonomi Bisnis Vol. 3, No. 3 (2021)
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v3i3.92

Abstract

CV. Tomi Advertising is a business sector that operates in advertising, construction and promotion that has various types of work services such as manufacturing neonboxes, signboards, signboards, banners, mild steel, modif houses, and others. CV. Tomi Advertising was founded in August 1997 with several ups and downs in business so that it can survive until now by establishing cooperation in several areas such as Pekanbaru, Jambi, Riau Islands and Pangkal Pinang. The recording system for the number of customers who came to CV. Tomi Advertising is done manually using a book. So that the recording of the number of subscribers is not well organized. There are some customers who do not fill in the customer arrival book so that the increase in the number of customers from year to year is less effective. The prediction of the number of subscribers is used as a reference to increase the number of subscribers. The prediction of the number of subscribers is a calculation of the level of the number of customers who come at a certain time. The purpose of this study is to predict the increase in the number of customers that occur at CV. Tomi Advertising. Where, data processing carried out by the Monte Carlo method comes from the amount of data from January 2018 to December 2020. Data processing for the number of customers is also applied to the system using the PHP programming language (Hypertext Processor). Based on the simulation, the increase in the number of customers that has been done is getting an average of 72% so that it can make it easier for business managers to make decisions in order to develop a business.
The Panel Data Analysis to Identify the Factors Affecting Turkish Currency Assets of Foreign Deposit Banks Özgür, Ersan
Jurnal Informatika Ekonomi Bisnis Vol. 3, No. 3 (2021)
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v3i3.97

Abstract

With the implementation of free market economy in Turkey starting from 1980, restrictions on foreign capital flows began to be abolished. Within the scope of international expansion in financial aspects, steps for integration with global financial markets were taken, and regulations were made. Accordingly, the number of foreign banks in Turkish banking system have increased since 1980, and reached an important scale in the sector. The share of foreign deposit banks’ total assets in the entire banking sector is at 22,8% level as of 2019. In this study, panel data analysis was performed to identify the factors affecting the Turkish currency assets of foreign deposit banks. The 11-year data for the 2009-2019 period were utilized in the study. Turkish Currency Assets / Total Assets was determined as the dependent variable in the analysis. The factors affecting the Turkish currency assets of foreign deposit banks were identified as Turkish Currency Liability / Total Liability [TPYUK], Turkish Currency Deposits / Total Deposits [TPMEV], and Turkish Currency Loans / Total Loans [TPKREDI]. Based on the study results the model formed was significant, and the ratio of independent variables for explaining the dependent variable in the model was approximately 48%. The independent variables TPYUK and TPKREDI were revealed to have a statistically significant positive effect on the dependent variable at 5% significance level. A 1-unit raise in TPYUK increased the dependent variable by 0,436 unit, and a 1-unit raise in TPKREDI by 0,033 unit. No statistically significant effect of TPMEV as the other independent variable was identified on the dependent variable.

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