Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Data : Journal of Information Systems and Management Jurnal Ilmu Komputer
Wiharjo, Sudarno
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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

Found 2 Documents
Search

 1 
Phishing Email Classification Approach Using Machine Learning Algorithms - A Literature Review Firman; Tukiyat; Wiharjo, Sudarno
Data : Journal of Information Systems and Management Vol. 3 No. 3 (2025): July 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/data.v3i3.692

Abstract

Email phishing is one of the cybersecurity threats that continues to grow, utilizing social engineering to obtain sensitive data. Various machine learning-based approaches have been researched to detect and classify phishing emails. This article presents a literature review of phishing email classification methods, including the K-Nearest Neighbor (KNN) algorithm, Naïve Bayes, Support Vector Machine (SVM), Random Forest, and deep learning-based approaches. The discussion included feature extraction techniques (TF-IDF, Word2Vec, BERT), handling data imbalances, and model performance evaluation. This review identifies current research trends, challenges, and gaps for further research.
Analisis Sentimen Pelayanan Pelanggan Mini Market Alfamart Pada Media Sosial Twitter Dengan Naïve Bayes Classifier Aziz, Awaludin; Susanto, Agung Budi; Wiharjo, Sudarno
Jurnal Ilmu Komputer Vol 1 No 2 (2023): Jurnal Ilmu Komputer (Edisi Desember 2023)
Publisher : Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Twitter is one of the social media that is currently popular, here the public is free to have opinions, write, and comment on anything. PT Sumber Alfaria Trijaya with its trademark Alfamart is a company engaged in the retail sector. Not infrequently consumers submit complaints, criticisms, and suggestions through this social media. Community opinion can be used as evaluation material in improving services. In this study, sentiment analysis for Alfamart minimarket customer service was carried out based on data obtained from Twitter. This sentiment analysis aims to classify Alfamart's customer service tweets into positive, negative, and neutral sentiments using the naive Bayes classifier algorithm. The data used is 2000 tweet data and then preprocessing is carried out so that 1691 tweets are clean data. Of the 1691 data analyzed, 1017 positive tweets, 297 negative tweets, and 377 neutral tweets were obtained. Then the data will be divided into 80% training data and 20% test data. The results of the accuracy value are 70% with a Precision value of 70%, a Recall value of 70%, and an F1-Score value of 66%.
Co-Authors Agung Budi Susanto Aziz, Awaludin Firman Tukiyat