Article Per Year (5 Year)
p-Index From 2019 - 2024
0.444
P-Index
This Author published in this journals
All Journal Martabe : Jurnal Pengabdian Kepada Masyarakat Journal of Computer Networks, Architecture and High Performance Computing
Bella Ananda
Universitas Islam Negeri Sumatera Utara
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT 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.
K-Nearest Neighbor Algorithm and Case Base Reasoning on Xenia Car Damage Detection Expert System Bella Ananda; Raissa Amanda Putri
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 2 (2024): Articles Research Volume 6 Issue 2, April 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i2.3700

Abstract

PT Astra Daihatsu Motor or commonly abbreviated as ADM is the Sole Agent Brand Holder (ATPM) of Daihatsu cars in Indonesia. Xenia car is one of the most popular cars in Indonesia. Although there are many Xenia car users, it is not uncommon for Xenia cars to experience damage caused by the ignorance of car users, where the car user only knows how to use it but does not know how to maintain the car properly and correctly. Before damage occurs to the car, the car usually experiences several symptoms of damage that the user does not realize. With that, there are often difficulties experienced by users to find out the type of damage to the car. The purpose of applying and designing applications in this study is to apply the Case Based Reasoning method with the K-Nearest Neighbor Algorithm to detect damage to Xenia cars and to design and build applications with the Case Based Reasoning method with the K-Nearest Neighbor Algorithm to detect damage to web-based Xenia cars. This research uses the Research and Development method. Based on the results of research from previous cases, the new case has similarities with 5 cases and the highest similitude value is with the highest type, namely the type of Injector Malfunction damage with a value of 0.625 or around 62.5%. This expert system application can detect and determine the results of Xenia car engine damage detection by applying a method that looks for the closest similarity value of new cases to old cases, namely the Case Based Reasoning method and the K-Nearest Neighbor Algorithm looking for the closest neighbors of the same weight value. This web-based expert system can be used by users to find the results of Xenia Car engine damage detection experienced by determining the symptoms that are available in web-based applications. This web-based application can also provide solutions from the detection results of the type of Xenia car engine damage.
Co-Authors Efi Brata Madya Feby Mayori Rambe M.Rafi Aufa Mitha Rosadi Raissa Amanda Putri Rizki Ramadhan Nasution Silva Azura