Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Intizar Jurnal Teknologi Informasi dan Multimedia
Akbar, Syafaat
Unknown Affiliation
Religion Arts Humanities Computer Science & IT

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

Found 2 Documents
Search

 1 
Eksistensi Mahar dalam Perkawinan: antara Simbol Status Sosial dan Kewajiban Agama Akbar, Syafaat; Sainun
Intizar Vol 30 No 1 (2024): Intizar
Publisher : Pusat Penelitian dan Penerbitan Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Islam Negeri Raden Fatah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19109/intizar.v30i1.22709

Abstract

Penelitian ini bertujuan untuk mengeksplorasi peran mahar sebagai simbol status sosial dalam budaya Sasak di Lombok dan kewajiban agama dalam konteks perkawinan. Metode yang digunakan adalah pendekatan deskriptif kualitatif dengan pengumpulan data melalui wawancara dan studi literatur. Teknik triangulasi digunakan untuk validitas data, sedangkan analisis data menggunakan model interaktif untuk mendalami konteks secara mendalam. Hasil penelitian menunjukkan bahwa mahar tidak hanya sebagai kewajiban agama, tetapi juga sebagai indikator status sosial yang dipengaruhi oleh pendidikan dan status sosial calon mempelai wanita. Tradisi mahar yang tinggi terkadang menjadi beban bagi calon suami dari latar belakang ekonomi rendah, bertentangan dengan prinsip syariat Islam yang menekankan kemudahan dalam pernikahan. Pemahaman yang mendalam terhadap nilai-nilai agama dapat mengurangi tekanan sosial dan mendorong praktik pernikahan yang lebih adil sesuai dengan ajaran Islam.
Pengembangan Deteksi Pesan Spam pada Website Inti Everspring Indonesia Menggunakan Algoritma Support Vector Machine Akbar, Syafaat; Hani'ah, Mamluatul; Rozi, Imam Fahrur
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 2 (2026): May
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i2.872

Abstract

The development of information technology has driven the growth of email-based communica-tion in business environments, including at Inti Everspring Indonesia. However, the high volume of incoming emails increases the potential for spam messages that may disrupt work effectiveness and data security. This study develops a spam detection system on the company’s website by ap-plying the Support Vector Machine (SVM) algorithm. SVM was selected because of its ability to perform text classification efficiently. The dataset used in this research comes from the company’s internal emails, consisting of labeled spam and non-spam messages. Since the dataset is imbal-anced, an oversampling process was applied, followed by text preprocessing steps including case folding, tokenization, removal of stop words, symbols, numbers, and stemming. The model was then trained using the SVM algorithm, and its performance was evaluated using several metrics: accuracy, recall, precision, and F1-score. Based on the experiments, the SVM-based spam detec-tion model achieved 100% precision, 100% recall, and a 100% F1-score. To validate the reliabil-ity of the algorithm, SVM performance was compared with BERT and Naïve Bayes. BERT achieved 96% accuracy, and Naïve Bayes achieved 97% accuracy. These results indicate that SVM is capable of classifying messages accurately, and SVM outperforms both algorithms.
Co-Authors Imam Fahrur Rozi Mamluatul Hani’ah Sainun