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 6 Documents
Search results for , issue "Vol. 3, No. 2 (2021)" : 6 Documents clear
Sistem Pendukung Keputusan dengan Metode Multi Factor Evaluation Process dalam Mengidentifikasi Penerima Bantuan yang Tepat pada Program Keluarga Harapan Sutra, Lidia; Nurcahyo, Gunadi Widi
Jurnal Informatika Ekonomi Bisnis Vol. 3, No. 2 (2021)
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v3i2.65

Abstract

The Family Hope Program (PKH) is a conditional cash transfer program for poor families. PKH is one of the government programs in reducing poverty in Indonesia. The large amount of PKH participant data that will be processed can take a lot of time and can hamper the flow of aid. This study aims to create a system that can assist PKH facilitators in identifying the right beneficiaries for the PKH program quickly and with accurate results. The method used in this research is the Multi Factor Evaluation Process (MFEP) method. The data processed in this study consisted of 25 PKH participant data obtained from PKH Nagari Kunangan Parik Rantang facilitators. The criteria used as an assessment for PKH participants were having early age children, pregnant women, the elderly, with disabilities, high school children, junior high school children, and elementary school children. The stages of the MFEP method are determining the weight of each criterion, filling in the value for each factor, and calculating the evaluation weight then adding up all the evaluation weights to get the total evaluation value which is used as the final value in decision making. From data processing on 25 PKH participants, the results of the eligible decisions consisted of 20 participants and 5 non-eligible participants. The data that has been processed using the MFEP method is compared with data from PKH Facilitators and produces decisions with a 100% similarity level. With this level of accuracy, the MFEP method can be used in identifying the right recipients of assistance in the Family Hope Program.
Klasterisasi Dana Bantuan Pada Program Keluarga Harapan (PKH) Menggunakan Metode K-Means Said, Abdul Azis; Defit, Sarjon; Yunus, Yuhandri
Jurnal Informatika Ekonomi Bisnis Vol. 3, No. 2 (2021)
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v3i2.66

Abstract

The Family of Hope Program (PKH) is a program that aims to reduce poverty and improve the quality of human resources. Optimizing the provision of assistance in accordance with the expectations of those in need. Data on the poor or integrated social welfare data is needed as a reference for grouping. This study aims to make it easier for the selection team to provide assistance in accordance with the predetermined criteria whether or not they deserve to receive the assistance. The data used in the study is data from 2019. The data processing in this study uses the K-Means Clustering method with 3 clusters, namely Cluster 1 (C1) Nearly Poor Households (RTHM), Cluster 2 (C2) Poor Households (RTM), Cluster 3 (C3) Very Poor Households (RTSM). The results of the clustering process with 2 iterations state that for Cluster 1 the amount of data is, for Cluster 2 the amount of data, and for Cluster 3 the amount of data. So this research is very helpful in relocating targeted assistance according to the family hope cluster.
Simulasi Monte Carlo dalam Mengidentifikasi Peningkatan Penjualan Tanaman Mawar Dewi, Dian Cyntia; Sumijan
Jurnal Informatika Ekonomi Bisnis Vol. 3, No. 2 (2021)
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v3i2.67

Abstract

Roses are one of the most popular types of plants in the community. The sale of roses at the flower shop of 5 siblings is increasingly in demand. Identifying the increase in sales is important in analyzing sales progress. At the present time the seller can only see a manual increase in sales that are most in demand. This study aims to determine predictions of the increase in sales of rose flowers with a monte carlo simulation accurately and accurately. The data that will be processed in this study in the last 2 years, namely 2018 and 2019, rose plants obtained at the 5 Brothers Flower Shop in Solok City. There are several types of roses in the predicted sales level. Then the data will be converted into the probability distribution into cumulative frequency and followed by generating random numbers so that they can determine random numbers. Next, we will group the boundary intervals of the random numbers that have been obtained and continue with the simulation process so that the simulation results and percentage accuracy are obtained using the Monte Carlo method. The results of this study on data processing from 2019 to 2020 have an accuracy of 90%. So this research is very appropriate in identifying the increase in sales for the following year. The design of this system determines the amount of increased sales of goods using the monte carlo method in a flower shop of 5 siblings. Monte Carlo simulations can be used to identify specific sales increases. The results obtained are quite accurate using the Monte Carlo method.
Sistem Pakar dengan Metode Backward Chaining untuk Optimalisasi Layanan Helpdesk E-Government Hariona, Popi
Jurnal Informatika Ekonomi Bisnis Vol. 3, No. 2 (2021)
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v3i2.68

Abstract

The e-Government helpdesk service is an assistance service to deal with user needs related to disturbances and problems that occur both infrastructure and networks, applications and information systems as well as information security that occur in the Payakumbuh City Government. At this time most of the complaints that come to the front office helpdesk always need technicians to handle them, despite the limited number of technicians for handling e-Government problems in Payakumbuh City. This study aims to optimize e-Government Helpdesk services so that services can be carried out without direct technician intervention. The data used in this research is the disturbance report data that goes to the e-Government helpdesk service of Payakumbuh City during the last 11 months from 33 Regional Devices in Payakumbuh City and the stages of problem solving by technicians. This study uses the backward chaining method to identify the causes of disruption to e-Government services. The results achieved in this study are as many as 21 rules that can be applied directly to helpdesk services, with an accuracy rate of 92%. The rules generated by the backward chaining method can be used to optimize the resolution of disturbances that enter the helpdesk by the front office without waiting for the technician.
Simulasi Metode Monte Carlo dalam Menjaga Persediaan Alat Tulis Kantor Prawita, Riska
Jurnal Informatika Ekonomi Bisnis Vol. 3, No. 2 (2021)
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v3i2.69

Abstract

The use of office stationery in an educational institution is an absolute necessity. Provision of adequate and well-managed office stationery will achieve good effectiveness and efficiency as well. This study aims to predict the demand for office stationery using a Monte Carlo simulation. Monte Carlo simulation is a probabilistic method that determines odds based on random numbers. The data used in this study was the data on requests for Office Stationery in 2018 to 2019 at IAIN Batusangkar. The data was processed based on the Monte Carlo simulation stage by generating random numbers from the data. The results of the Monte Carlo simulation conducted in this study showed an accuracy rate of 96.92 % and were able to predict the demand for Office Stationery. Based on the level of accuracy generated in this study, the Monte Carlo Simulation can be used to predict the demand for Office Stationery for the following year. So, by knowing the demand for Office Stationery, the supply of Office Stationery at IAIN Batusangkar is maintained and effectiveness and efficiency are also achieved.
Simulasi Monte Carlo dalam Prediksi Jumlah Penumpang Angkutan Massal Bus Rapid Transit Kota Padang Alfikrizal, Khaliq
Jurnal Informatika Ekonomi Bisnis Vol. 3, No. 2 (2021)
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v3i2.72

Abstract

Bus Rapid Transit is a system of bus facilities, services and comfort which is used to increase speed and reliability and is integrated with a strong transit identity through high quality services. Trans Padang is a land transportation based on Bus Rapid Transit in Padang City which is managed by the Transportation Agency which started operating in January 2014 with a total bus fleet of 10 units on the Lubuk Buaya-Pasar Raya Padang route. Currently it has 2 corridors operating out of 6 corridors designed. This study aims to predict the number of Bus Rapid Transit passengers in Padang City and determine the level of accuracy of simulation data with real data using the Monte Carlo method. The data used to predict the number of passengers is data on the number of passengers from January 2017 to December 2019. From the simulations carried out, simulated accuracy is obtained for predicting the number of passengers with an average accuracy of above 80%. Based on a fairly high level of accuracy, the application of the Monte Carlo method to predict the number of Bus Rapid Transit passengers in Padang City is considered to be able to predict the number of passengers in the following year.

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