p-Index From 2020 - 2025
5.445
P-Index
This Author published in this journals
All Journal Jurnal Kependidikan: Penelitian Inovasi Pembelajaran DIKSI Jurnal Hidrolitan Teknotan: Jurnal Industri Teknologi Pertanian SOROT: Jurnal Ilmu-ilmu Sosial LiNGUA: Jurnal Ilmu Bahasa dan Sastra Jurnal Harpodon Borneo JURNAL ANALISIS KEBIJAKAN KEHUTANAN Lexicon Jurnal Arbitrer IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature Journal of Language and Literature Naturalistic : Jurnal Kajian dan Penelitian Pendidikan dan Pembelajaran RETORIKA: Jurnal Bahasa, Sastra, dan Pengajarannya LLT Journal: A Journal on Language and Language Teaching JURNAL PENGABDI Journal of Socioeconomics and Development Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Martabe : Jurnal Pengabdian Kepada Masyarakat English Language and Literature International Conference (ELLiC) Proceedings Adabiyyat: Jurnal Bahasa dan Sastra Linguistik Indonesia JCRS (Journal of Community Research and Service) Dinamika: Jurnal Bahasa, Sastra, dan Pembelajarannya Ilomata International Journal of Social Science Bakti Budaya: Jurnal Pengabdian kepada Masyarakat Sehat Rakyat: Jurnal Kesehatan Masyarakat Deskripsi Bahasa SASDAYA: Gadjah Mada Journal of Humanities Leksema: Jurnal Bahasa dan Sastra BAHASTRA Jurnal Jalan Jembatan Indonesia Bergerak: Jurnal Hasil Kegiatan Pengabdian Masyarakat MEMACE Jurnal Ilmiah Kajian Ilmu Humaniora Al-Bahtsu: Jurnal Penelitian dan Pendidikan Islam Gayatri : Jurnal Pengabdian Seni dan Budaya
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Linguistik Indonesia

AUTHORSHIP ANALYSIS IN ELECTRONIC TEXTS USING SIMILARITY COMPARISON METHOD Puspitasari, Devi Ambarwati; Fakhrurroja, Hanif; Sutrisno, Adi
Linguistik Indonesia Vol. 42 No. 1 (2024): Linguistik Indonesia
Publisher : Masyarakat Linguistik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26499/li.v42i1.544

Abstract

The most recent changes to the criteria in legal process for scientific evidence have emphasized scientific methods of authorship analysis. This study examined the authorship of electronic texts using a quantitative method based on forensic stylistics and computer technologies. This study uses 300 digital texts produced by 100 authors, including 100 questioned texts (Q-text) and 200 known texts (K-text). Personal texts of WhatsApp messages are used in this study as electronic texts. Authorship analysis was conducted by tracing the n-gram and testing all the text sets using the Similarity Comparison Method (SCM). Based on the results of the word 1-gram test, the SCM accuracy was found to be quite high, ranging from 85% to 96%. The findings of employing the tiny set are promising, with the various stylistic traits offering dependable accuracy ranging from 92% to 98.5%. The character-level n-gram tracing indicates a key feature of authorship attribution.