Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal Jurnal Manajemen Informatika dan Sistem Informasi Teknomatika: Jurnal Informatika dan Komputer
Ramadhana Saputra
Unknown Affiliation
Computer Science & IT

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

Found 2 Documents
Search

 1 
IMPLEMENTASI PROTEKSI CLIENT-SIDE PADA PRIVATE CLOUD STORAGE NEXTCLOUD Dedy Hariyadi; Dedy Hariyadi; Imam Puji Santoso; Ramadhana Saputra
Jurnal Manajemen Informatika dan Sistem Informasi Vol. 2 No. 1 (2018): MISI Januari 2019
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/misi.v2i1.65

Abstract

Saat ini hampir setiap perangkat terhubung dengan teknologi komputasi awan. Teknologi komputasi awan yang menawarkan layanan menarik adalah Cloud Storage seperti Google Drive, Dropbox, One Drive, Mega, dan lain-lain. Teknologi Cloud Storage semacam itu dapat diterapkan di lingkungan private atau on-premise. Peranti lunak Cloud Storage yang dapat diinstall di lingkungan private diantaranya, OwnCloud, Nextcloud, SeaFile, dan lain-lain. Implementasi Cloud Storage perlu diwaspadai karena memiliki celah keamanan saat transmisi data dari client ke server atau sebaliknya dan tidak terproteksinya berkas yang tersimpan pada Cloud Storage server. Pada penelitian ini menunjukkan hasil pengujian kerentanan menyimpan berkas dan direktori di penyedia Cloud Storage berserta memberikan solusi mengatasi keamanan tersebut.
Penerapan Metode Rabin-Karp untuk Mengukur Kemiripan Kata Dua Dokumen Berbasis Web Ramadhana Saputra; Ari Cahyono; M. Abu Amar Al Badawi
Jurnal Teknomatika Vol 14 No 1 (2021): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v14i1.1128

Abstract

Scientific literature plays a significant role in the academic requirements of colleges, encompassing various types such as papers, reports, journals, and scripts. However, the issue of plagiarism, including the copying and plagiarizing of others' work, remains prevalent in the creation of scientific papers. In particular, digital content plagiarism often involves copy-pasting and quoting from original documents. To address this, measuring the similarity of words between documents becomes essential. In Dhamayanti's research, the recommendation is to enhance the Rabin-Karp algorithm by utilizing a distinct method [1]. This study builds upon previous research employing a string-matching method. Instead of the conventional cosine method, the substitution method employed string-Karp techniques within the Rabin-Karp algorithm, resulting in improved similarity percentages. The manufacturing of the application adopts the string-matching method using the Rabin-Karp algorithm. The algorithm matches 5-gram word sequences converted into hash values, and the similarity percentage is determined based on matching hash values. The presence of identical words indicates similarity. The application is tested using six scientific writing documents from diverse sources with related titles. Through 15 test runs, the accuracy level reached 90%.
Co-Authors Ari Cahyono Dedy Hariyadi Imam Puji Santoso M. Abu Amar Al Badawi