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Mining Data In Identification Of Consumer Patterns Of Agricultural Machine Sales Using Fp-Growth Algorithm Eka Sofianti; Sarjo Defit; Yuhandri
SYSTEMATICS Vol 2 No 3 (2020): December 2020
Publisher : Universitas Singaperbangsa Karawang

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Abstract

The sales transaction data for agricultural machinery at the Mandiri Jaya Teknik Solok store is a large data set making it difficult to identify consumer purchasing patterns. Large data sets can be processed into useful information. Sales transaction data available at the Mandiri Jaya Teknik Solok store can be processed into useful information to increase sales. This study aims to identify consumer purchasing patterns in order to know which items are often sold and to find out which items need to be stocked more and to increase sales. The data that is processed in this study uses the sales transaction data obtained from the sales invoice of Toko Mandiri Jaya Teknik Solok. Data is in the form of sales data for 13 weeks of 20 items with a minimum support value of 15% and a confidence value of 60%. The method uses one of the data mining techniques associated with the FP-Growth algorithm, where the Fp-Growth algorithm uses the concept of tree development in searching for the types of items that are often purchased (frequency item sets). The tools used are Rapidminer 9.8 so that the purchase patterns of goods are obtained which are used as information to predict the level of frequently sold items. 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 stock of goods 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 stores.
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

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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

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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

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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

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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.
Sistem Pendukung Keputusan Spesifikasi Biji Jagung Berkualitas Terbaik dengan Metode Multi Attribute Utility Theory Chairul Imam; Julius Santony; Yuhandri
Jurnal KomtekInfo Vol. 5 No. 3 (2018): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1366.315 KB) | DOI: 10.35134/komtekinfo.v5i3.27

Abstract

Farmers sell corn kernels in the company of PT Charoen Pokphan Indonesia Tbk Medan, corn kernels are used to mix feed ingredients to meet the protein values and nutrition of these feeds to be of high quality. The company PT Charoen Pokphan Indonesia Tbk Medan buys corn kernels to farmers by specifying the best quality corn kernels, so they know the total price of corn kernels is in accordance with the quality needed. This research determines the criteria of the best quality types of corn kernels and how to apply the Multi Attribute Utility Theory to decision support systems to determine the quality of corn kernels, to be able to help the company PT Charoen Pokphan Indonesia Tbk Medan in determining the quality of corn kernels. Based on the criteria set out in the company PT Charoen Pokphan Indonesia Tbk Medan to obtain the best quality corn kernels using grade 1 to grade 4 and ranking. The results of testing these methods are produced a decision on an alternative with a total value of 86.7%. So this method is needed to evaluate the determination of the best quality corn kernels to produce the best decisions
Penentuan Materi Layanan Bimbingan TIK Menggunakan Algoritma C4.5 Montesna; Yuhandri; Jufriadif Na’am
Jurnal KomtekInfo Vol. 6 No. 1 (2019): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1186.437 KB) | DOI: 10.35134/komtekinfo.v6i1.38

Abstract

Changes in curriculum from KTSP (Education Unit Level Curriculum) to 2013 Curriculum result in changes in Information and Computer Technology (ICT) subjects to ICT Guidance (BTIK). These subjects are not scheduled in general, so students need to be guided by questionnaires. To find out the right guidance needs data mining is needed. So this research is done in determining the accuracy of the guidance needs in accelerating the process of questionnaire data. The method used is C4.5 Algorithm. The results of the study have an accuracy of 90%, so it can be recommended in determining guidance material for students.
Perbandingan Metode Cropping pada Sebuah Citra untuk Pengambilan Motif Tertentu pada Kain Songket Sumatera Barat Yuhandri
Jurnal KomtekInfo Vol. 6 No. 1 (2019): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (934.023 KB) | DOI: 10.35134/komtekinfo.v6i1.45

Abstract

At the time of image processing where we only need a certain part of an image according to the needs called the Region of Interest (ROI), in order to obtain that, the processing is carried out in a cropping process. Cropping is mostly done by researchers, especially those who research in the field of image processing in order to do data processing on an image, the results of cropping process on an image are usually done to make it easier for researchers to focus on something that is needed only. In this study is to compare existing cropping methods to get a motif found in an image of West Sumatra songket fabric. In this study using the method of cropping rectangle, square, circle, ellipse, polygon and tested using the Matlab programming language. The results of comparison of 5 cropping methods for taking certain motifs on the songket image with 5 different songket image samples, shows that the best results are obtained by using the polygon method. Polygon method can reach certain coordinate points in a songket image, so that the results of cropping are better and other motives that are carried along during the cropping process can be reduced.
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