Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Martabe : Jurnal Pengabdian Kepada Masyarakat
Mitha Rosadi
Universitas Islam Negeri Sumatera Utara
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
UPAYA PENGAKOMODASIAN TERADAP MASYARAKAT DESA SIDODADI KECAMATAN SIBIRU-BIRU SUMATERA UTARA Bella Ananda; Feby Mayori Rambe; Mitha Rosadi; M.Rafi Aufa; Rizki Ramadhan Nasution; Silva Azura; Efi Brata Madya
Martabe : Jurnal Pengabdian Kepada Masyarakat Vol 5, No 8 (2022): Martabe : Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jpm.v5i8.3066-3076

Abstract

Kuliah kerja nyata (KKN) ialah suatu bentuk kegiatan pengabdian kepada masyarakat yang dilakukan oleh mahasiswa melalui pendakatan lintas keilmuan yang di dapat selama duduk di bangku perkuliahan. Kuliah kerja nyata (KKN) ini dilakukan di desa sidodadi yang terhitung dari tanggal 18 juli 2022 sampai dengan 18 agustus 2022, adapun tujuan dari kelompok KKN-106 ini ialah membentuk masyarakat yang bermartabat serta menjadikan desa sidodadi menjadi lebih religious. Pengabdian ini kami lakukan melalui kegiatan mengajar di SD dan Paud, membuat posko – posko les di desa untuk meningkatkan pendidikan didesa sidodadi, membuat event – event islami, membantu kegiatan UMKM, ikut partisipasi dalam membantu masyarakat di desa sidodadi dalam bergotong royong, serta mengikuti kegiatan perwiridan yang ada di Desa Sidodadi.
Comparison of Apriori and FP-Growth Algorithms in Analyzing Association Rules Mitha Rosadi; Muhammad Siddik Hasibuan
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 2 (2024): September 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i2.9965

Abstract

The problem objectives of this research include the following: To implement Apriori and FP-Growth Algorithms in determining the comparison of association rules and To build a jupyter notebook application model in determining the comparison of association rules of Apriori and FP-Growth Algorithms. This research compares Apriori and FP-Growth algorithms in analyzing association rules, with a focus on implementation and model development in Jupyter Notebook. Through manual calculation using 10 transaction data samples and testing on 38,765 groceries data entries from Kaggle, differences were found in the lift results between itemsets. Apriori algorithm often shows a negative relationship between items, while FP-Growth gives a similar interpretation but with slightly different lift values, showing a different influence in the relationship between items. In addition, FP-Growth proved to be more efficient with a much faster execution time (5.2757 seconds) than Apriori (185.9585 seconds), especially in handling large datasets. The results of this study indicate that the selection of an appropriate algorithm should consider the characteristics of the dataset and the purpose of the analysis.
Co-Authors Bella Ananda Efi Brata Madya Feby Mayori Rambe M.Rafi Aufa Muhammad Siddik Hasibuan Rizki Ramadhan Nasution Silva Azura