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All Journal Infotech Journal InfoTekJar (Jurnal Nasional Informatika dan Teknologi Jaringan) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Teknik Komputer AMIK BSI Bina Insani ICT Journal Informatics for Educators and Professional : Journal of Informatics IndoMath: Indonesia Mathematics Education KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer JURIKOM (Jurnal Riset Komputer) Jurnal ICT : Information Communication & Technology Building of Informatics, Technology and Science Infotekmesin Respati Journal of Computer System and Informatics (JoSYC) Jurnal Sains Teknologi Transportasi Maritim Jurnal Sistem Komputer dan Informatika (JSON) Madani : Indonesian Journal of Civil Society MEANS (Media Informasi Analisa dan Sistem) Jurnal Teknologi Informasi dan Komunikasi Jurnal Digit : Digital of Information Technology Mosharafa: Jurnal Pendidikan Matematika JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jupiter Journal of Computer & Information Technology Experimental Student Experiences AMMA : Jurnal Pengabdian Masyarakat Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal)
Odi Nurdiawan
STMIK IKMI Cirebon
Arts Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Social Sciences Transportation Other

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Journal : Journal of Computer System and Informatics (JoSYC)

 1 
Penerapan Association Rule Menggunakan Frequent Pattern Growth Untuk Rekomendasi Produk Jersey Sepakbola Anwar Musaddad; Odi Nurdiawan; Gifthera Dwilestari
Journal of Computer System and Informatics (JoSYC) Vol 3 No 3 (2022): May 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i3.1390

Abstract

The phenomenon of the beginning of the year, what some football fans have been waiting for, is the publication of the latest jersey from their favorite team. When the new jersey was launched, football fans flocked to buy the jersey, but there were several shops available for the new jersey. This was experienced by the Eighteen Sport shop, in fulfilling the wishes of fans, there were obstacles to re-stock the jerseys that were most in demand. So many items that have not been sold. The focus of this research lies in managing jersey sales data in June, July and August, as well as high interest in the demand for club jerseys. The high demand for jerseys is influenced by the achievements of the club itself. This study uses the FP Growth algorithm with the aim of getting a recommendation pattern from the wishes of football fans. Based on the results of the support management, it was found that consumers by buying 1 jersey item will buy back 1 different jersey item as many as 15 patterns. Consumers by buying 2 jersey items will repurchase 1 different jersey item as many as 46 patterns. Consumers by buying 3 jersey items will repurchase 1 different jersey item as many as 37 patterns. Consumers by buying 4 jersey items will repurchase 1 different jersey item for 10 patterns. So that the pol data becomes the owner's recommendation to make a repeat purchase.
Klasifikasi Pemberian Bantuan UMKM Cirebon dengan Menggunakan Algoritma K-Nearest Neighbor Hira Wahyuni Azizah; Odi Nurdiawan; Gifthera Dwilestari; Kaslani Kaslani; Edi Tohidi
Journal of Computer System and Informatics (JoSYC) Vol 3 No 3 (2022): May 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i3.1392

Abstract

The Indonesian government in obtaining Real Time data on MSMEs who are entitled to assistance, accuracy in distributing MSME assistance, and accelerating Indonesia's economic growth through MSMEs, especially the Cirebon Regency area. There are several ways so that cash transfer assistance for micro-scale SMEs from the government is right on target, in this study the authors will use data mining techniques with the k-nearest neighbors method in classifying receiving assistance from SMEs. The data used in this study uses secondary data with attributes of Regency, District, Business Name, Product Name, Business License, Assets and Turnover. The application of the KNN algorithm uses the retrieval operator, cross validation, and in developing the model using the KNN algorithm operator, apply model and performance. The results of the accuracy are 98.46 % with details, namely the Prediction Results are Eligible and it turns out to be true as many as 339 Data. The Prediction Result is Eligible and it turns out to be true Not Eligible as much as 2 Data. Prediction results are not eligible and it turns out to be true as much as 4 data. Prediction results are not eligible and it turns out to be true, 42 data are not eligible. Recommendations for the pattern of knowledge obtained using the K-NN algorithm. Researchers provide recommendations that are feasible to be given assistance for MSMEs as many as 339 MSME participant data spread across the Cirebon district and included in the affected category. Then there are several MSME participants who cannot receive MSME assistance according to the application of the KNN algorithm, which is 42 data, and there are 2 data from participants who are proposed to receive MSME assistance. The hope of the research for participants who receive assistance from the government can survive in conditions like this covid 19
Co-Authors Abdul Robi Padri Ade Bani Riyan Ade Irma Purnamasari Ade Irma Purnamasari Ade Irma Purnamasari Ade Irma Purnamasari Ade Rizki Rinaldi Adisty Tri Putra Agis Maulana Robani Agus Surip Ahmad Faqih Ahmad Faqih Ahmad Faqih Ahmad Zam Zami Ananda Rafly Andi Setiawan Anwar Musaddad Aria Pratama Arif Rinaldi Dikananda Bambang Irawan Basysyar, Fadhil Muhammad Cep Lukman Rohmat Cep Lukman Rohmat Dias Bayu Saputra Dikananda, Arif Rinaldi Dilla Eka Lusiana Dita Rizki Amalia Dwi Teguh Afandi Edi Tohidi Edi Wahyudin Eko Wiyandi Fadhil M. Basysyar Fadrin Helmi Febriansyah, Feggy Fidya Arie Pratama Fidya Arie Pratama Gifthera Dwilestari Haidah Putri Haidar Fakhri Hira Wahyuni Azizah Husein Subandi Ibnu Ubaedila Irfan Ali Irfan Ali Irfan Ali, Irfan Irma Purnamasari, Ade Irvandi Jaelani Sidik Julia Eka Yanti Kaslani Khamim Surya Hadi Kusuma Al Atros Kurniawan Fajar Abdulloh Lukmanul Hakim Martanto . Medina Aprilia Putri Melia Melia Melisa Hikari Mia Fijriani Mohammad Rosihin Amar Muchamad Sobri Sungkar, Muchamad Sobri Mulyana Mulyana Mulyawan Mulyawan Nana Suarna Nana Suarna Nana Suarna Nanda Permatasari Nining Rahaningsih Noval Salim Nur Atikah Nurhadiansyah Nurhadiansyah Nurhadiansyah, Nurhadiansyah Pratama, Fidya Arie Pratiwi, Fitriyani Purnamasari, Ade Irma Putriyana Putriyana R, Nining Rifki Nurcholis Rini Astuti Riyan Suryatana Rohmat, Cep Lukman Rudi Hartono Ruli Herdiana Ruli Herdiana Rully Pramudita Saeful Anwar Saeful Anwar Saeful Anwar, Saeful Saepul Hadi Salsa Billa Agistina Siti Aisyah Tio Prasetiya Tio Prasetya TOMAS TOMAS Topan Hadi Tuti Hartati Tuti Hartati Wiyandi, Eko Yudhistira Arie Wijaya