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All Journal EDUNOMIC : JURNAL ILMIAH PENDIDIKAN EKONOMI FAKULTAS KEGURUAN DAN ILMU PENDIDIKAN Jurnal Informatika dan Teknik Elektro Terapan Infotech Journal InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Jurnal Teknik Komputer AMIK BSI Bina Insani ICT Journal Informatics for Educators and Professional : Journal of Informatics IndoMath: Indonesia Mathematics Education JITK (Jurnal Ilmu Pengetahuan dan Komputer) KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer JURNAL TEKNOLOGI DAN OPEN SOURCE JURIKOM (Jurnal Riset Komputer) Jurnal ICT : Information Communication & Technology Building of Informatics, Technology and Science Infotekmesin JATI (Jurnal Mahasiswa Teknik Informatika) Respati Media Informatika 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 Innovation in Research of Informatics (INNOVATICS) Jurnal Teknik Informatika (JUTIF) Jurnal Digit : Digital of Information Technology Mosharafa: Jurnal Pendidikan Matematika JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jupiter Journal of Computer & Information Technology Jurnal Informatika dan Teknologi Informasi BULLET : Jurnal Multidisiplin Ilmu AMMA : Jurnal Pengabdian Masyarakat Jurnal Sistem Informasi dan Manajemen Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal)
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Journal : Journal of Computer System and Informatics (JoSYC)

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 Rauf Chaerudin Abdul Robi Padri abdullah, nur syarief Ade Irma Purnamasari Ade Irma Purnamasari Ade Irma Purnamasari Ade Kurnia, Dian Ade Rizki Rinaldi Adisty Tri Putra Agis Maulana Robani Agung Nugraha Agus Surip Ahmad Faqih Ahmad Faqih Ahmad Faqih Ahmad Faqih Ahmad Zam Zami Ainnur Rahman, Rizal Amar, Mohammad Rosihin Amarda, Juan Amri, Hajijin Ananda Rafly Andi Setiawan Andi Setiawan Anwar Musaddad Aria Pratama Arif Fitriyanto, Goffar Arif Rinaldi Dikananda baihaqqi, Farisky Bambang Irawan Basysyar, Fadhil Muhammad Basysyar, Muhammad Fadhil Cep Lukman Rohmat Cep Lukman Rohmat Cep Lukman Rohmat Dadang Sudrajat Deasiva, Imanda Dewanty Rafu, Maria Dias Bayu Saputra Dikananda, Arif Rinaldi Dilla Eka Lusiana Dita Rizki Amalia Dodi Solihudin Dwi Teguh Afandi Edi Tohidi Edi Wahyudin Eko Wiyandi Fadhil M. Basysyar Fadrin Helmi FANDI ACHMAD Faturrohman, Faturrohman Fauzi Fauzi Febriansyah, Feggy Fidya Arie Pratama Fidya Arie Pratama Firmansyah Firmansyah Fitriyani, Nur Sifa Gifthera Dwilestari Haidar Fakhri Hanafi, Muhammad Salman Hayati, Umi Heliyanti Susana Herdiana, Ruli Herdiana, Rully Heriyawan, Ikhsan Himawan, Irvan Hira Wahyuni Azizah Ibnu Ubaedila Irfan Ali Irfan Ali Irfan Ali, Irfan Irma Purnamasari, Ade Irvandi Irvandi IRVANDI, IRVANDI Jaelani Sidik Jamalul'ain, Abdul Jayawarsa, A.A. Ketut Julia Eka Yanti Juliadi, Diky Karlina, Lita Kaslani Khamim Surya Hadi Kusuma Al Atros Khoirul Insan, Moh Khoirul Kurniawan Fajar Abdulloh Laturrizqi, Washi Lukmanul Hakim M. Basyisyar, Fadhil M. Iqbal Fadhilah, Aji Mamluah, Karimatul Martanto . Mauludin, Muhammad Rifqi Medina Aprilia Putri Melia Melia Melia Melia Melisa Hikari Mia Fijriani Muchamad Sobri Sungkar, Muchamad Sobri Muhalim, Alvy Mulyana Mulyana Mulyawan Mulyawan Musliyadi, Mar'i Nana Suarna Nana Suarna Nana Suarna Nanda Permatasari Nining Rahaningsih Noval Salim Nur Atikah Nurcholis, Rifki Nurhadiansyah Nurhadiansyah Nurhadiansyah, Nurhadiansyah Nurrohmat, Iman Pratama, Fidya Arie Pratama, Irfan Pratiwi, Fitriyani Prihartono, Willy Purnamasari, Ade Irma Putri, Haidah R, Nining Riansah, Adam Rinaldi Dikananda, Arif RinaldiĀ Dikanda, Arif Riyan Suryatana Riyan, Ade Bani Rizki, Dicky Miftakhul Rohmat, Cep Lukman Rokhmatan Khaerullah, Rizal Rudi Hartono Rudi Kurniawan Ruli Herdiana Rully Pramudita Saeful Anwar Saeful Anwar Saeful Anwar, Saeful Saepul Hadi Salsa Billa Agistina Suarna, Nana Subandi, Husein Syafi'i, Syafi'i Taufik Hidayat Tengku Riza Zarzani N Tio Prasetiya Tio Prasetya TOMAS TOMAS Topan Hadi Tuti Hartati Tuti Hartati Wiyandi, Eko Yudhistira Arie Wijaya Yunus, Shofian Zeya Sebastian, Muhammad