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Journal : Jurnal Informatika Ekonomi Bisnis

Prediksi Optimal dalam Produksi Bata Merah Menggunakan Metode Monte Carlo Hendro Zalmadani; Julius Santony; Yuhandri Yunus
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.
Optimalisasi Penggunaan Lahan Perkebunan Kelapa Hibrida Menggunakan K-Means Clustering Henky Andema; Sarjon Defit; Yuhandri Yunus
Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 2 (June 2020)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (560.81 KB) | DOI: 10.37034/infeb.v2i2.23

Abstract

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.
Prediksi Tingkat Kedatangan Wisatawan Asing Menggunakan Metode Backpropagation Salman Alfarisi Salimu; Yuhandri Yunus
Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 4 (December 2020)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (537.612 KB) | DOI: 10.37034/infeb.v2i4.50

Abstract

The tourism industry is always growing and plays an important role in the national economy, both as the second largest contributor to foreign exchange and as a large labor absorber. This study aims to optimize production using the Artificial Neural Network (ANN) method. The technique used is Backpropagation. The data processed is data on the number of foreign tourists from 2017 to 2019 in the Mentawai Islands. The results of the momentum obtained are 2-5-1 on the division of data into 2, namely training data for 2017 and 2018 and test data for 2019. The optimal prediction result is 0.99847, so this research is very helpful in predicting the arrival rate of foreign tourists in Mentawai Islands.
Simulasi Monte Carlo dalam Memprediksi Tingkat Pendapatan Penjualan Kuliner Muhammad Ihksan; Yuhandri Yunus
Jurnal Informatika Ekonomi Bisnis Vol. 3, No. 1 (March 2021)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (426.255 KB) | DOI: 10.37034/infeb.v3i1.63

Abstract

Radja Minas is one of the culinary places located in the city of Padang with more than 30 employees. With the development of Radja Minas, of course, a good management strategy is needed. One way to do a revenue simulation, sales revenue simulation is a process of drawing or predicting sales. This study aims to predict the average sales revenue, so that it becomes a recommendation for use in making management strategies. The data processed in this research is sales data from 2017 to 2019 which comes from Radja Minas. This data will be processed using the monte Carlo method. The results of the tests that have been done have an accuracy rate of 92.66%. The high level of accuracy from the results of predictive data processing, this research is very precise and suitable for optimizing sales revenue. So that this research becomes a recommendation to be used in making a management strategy at Radja Minas in the future.
Klasterisasi Dana Bantuan Pada Program Keluarga Harapan (PKH) Menggunakan Metode K-Means Abdul Azis Said; Sarjon Defit; Yuhandri Yunus
Jurnal Informatika Ekonomi Bisnis Vol. 3, No. 2 (June 2021)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (547.893 KB) | 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.
Evaluasi Penentuan Kelayakan Pemberian Subsidi Listrik dengan Metode MFEP Bobi Heri Yanto; Yuhandri Yunus
Jurnal Informatika Ekonomi Bisnis Vol. 3, No. 3 (September 2021)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (236.506 KB) | 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.
Co-Authors - Hendrick AA Sudharmawan, AA Abdul Azis Said Agung Ramadhanu Akbar Iskandar Alifcha Ghazian Alifia Restu Selvanda Allans Prima Aulia Angga Putra Juledi Arika Juwita Z Ayu Prima Siska Bobi Heri Yanto Budi Jaya Budi Permana Putra Chairul Imam Darnis, Rahmi Dendi Ferdinal Deno Yulfa Ardian Desi Laidawati Dodi Andre Putra DWI JULISA UTARI Dwika Assrani Dzaki Al Fikri Eka Naufaldi Novri Eka Sofianti Fahmi Firzada Fajri Ilhami Andrean Fhajri Arye Gemilang Gunadi Widi Nurcahyo Hasanatul Iftitah Hendro Zalmadani Henky Andema Hermanto Heru Rahmat Wibawa Putra Indah Dwi Putri Irvan Okta Mazhona Ismail Virgo Jefdy Kurniawan Johan Danu Wijaya Jufriadif Na`am, Jufriadif Julius Santony Julius Santony K Kadrahman Lc Granadi Suhaidir Lidia K Simanjuntak Lova Endriani Zen Lusi Kestina M Ilham Aldyno M Mutia Malik, Rio Andika Mardison Mesran, Mesran Mohammad Guntur Montesna Muhammad Arif Zikir Risky Muhammad Ihksan Muhammad Ikhlas Musli Yanto Nandra Sunaryo Nasma Yeni Nasution, Annio Indah Lestari Nuning Kurniasih R Rahmiyanti Rafi Septiawan Putra Ragil Ardiansyah Rahmad Dian Riski Randa Hidayatullah Rivo Stephano Roby Nurbahri Romi Hardianto Ronda Deli Sianturi Rovidatul S Salmiati S Sumijan Sahat Sonang Sitanggang Salman Alfarisi Salimu Sarjo Defit Sarjon Defit Sarjon Defit Septiana Vratiwi Setiawan, Adil Silfia Andini Sri Amalia Harahap Sri Dewi Stefani Hardiyanti Putri Subrianto Chandra Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Syahid Hakam Abdul Halim Syaljumairi, Raemon Teddy Winanda Teguh Junaidi Tessa Y M Sihite Wenni Afrodita Willy Eka Septian Yendi Putra Yosua Ade Pohan Yundari, Yundari Yuniko Fauzan Yusma Elda Zupri Henra Hartomi