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All Journal Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Journal of Economic, Business and Engineering (JEBE) Revenue : Jurnal Ekonomi Pembangunan dan Ekonomi Islam Psycho Aksara Jurnal Penelitian Psikologi
Sibyan, Hidayatus
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Aerospace Engineering Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Mechanical Engineering Social Sciences

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KONSEP EKONOMI BEROKAH DALAM TRADISI PENGAJIAN KOLOMAN MADURA DI DESA LARANGAN BADUNG KECAMATAN PALENGAAN PAMEKASAN Sibyan, Hidayatus; Fawaid, Akh.; Zaini, Moh.
Revenue : Jurnal Ekonomi Pembangunan dan Ekonomi Islam Vol 6 No 02 (2023): Revenue : Jurnal Ekonomi Pembangunan dan Ekonomi Islam
Publisher : Sekolah Tinggi Ilmu Ekonomi Bakti Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56998/jr.v6i02.121

Abstract

This study aims to investigate the concept of Berokah Economics in the tradition of recitation in Madura. The focus of this research is to understand how the concept is applied in the economic practices of the people involved in recitation activities in Madura. The research method used is qualitative research with a descriptive approach. Data was collected through participatory observation, in-depth interviews, and analysis of documents related to recitation traditions and related economic practices. The research participants consisted of members of the Madurese community involved in recitation activities and economic practices. The results of the study show that the concept of Berokah Economics in the tradition of recitation in Madura has significant implications for empowering the community's economy. Study participants integrate the teachings of the Islamic religion in their daily economic practices. They apply principles such as sincerity, piety to Allah, and gratitude in doing business. This concept influences the way they conduct transactions, interact with consumers, and manage their economic resources. also serves as a forum for friendship and exchange of information between members of the study.
Eksplorasi Gaya Hidup Terhadap Kesuksesan pada Lansia di Panti Werda Omega Semarang Khabibah, Ummy; Fatin, Salsabilla; Zakia, Nadhifa Rif'aldina; Rahmawati, Putri; Wibisono, Muhammad Athar; Bahrudin, Maulana Azis; Amalia, Annida; Sibyan, Hidayatus; Septiani, Dian Nabila; Hikmah, Siti
Psycho Aksara : Jurnal Psikologi Vol 3 No 2 (2025): Volume 3, Nomor 2, Juli 2025
Publisher : LEMBAGA PENELITIAN DAN PENGABDIAN MASYARAKAT UNIVERSITAS NAHDLATUL ULAMA BLITAR

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/pyschoaksara.v3i2.1868

Abstract

Jumlah lansia yang semakin meningkat menuntut perhatian terhadap kualitas hidup mereka. Penelitian ini bertujuan mengekspslorasi gaya hidup dan makna kesuksesan hidup lansia di panti werda omega semarang. Pendekatan yang digunakan menggunakan studi fenomenologis, data dikumpulkan melalui wawancara yang mendalam dengan empat lansia yang dipilih secara purposive. Analisis dilakukan dengan coding tematik. Lansia memiliki refleksi diri, pengendalian emosi, semangat hidup yang tinggi, dan hubungan sosial harmonis. Bagi lansia kesuksesan berisi ketenangan batin, kesehatan, hubungan baik, dan kebahagiaan sederhana.
IMPLEMENTASI YOLOv11 UNTUK DETEKSI KATA BAHASA ISYARAT BISINDO DAN SIBI Syaefudin, Ahmad; Sibyan, Hidayatus; Mahmudati, Rina; Asnawi, M. Fuat; Hasanah, Nur
Journal of Economic, Business and Engineering (JEBE) Vol. 7 No. 2 (2026): April
Publisher : Universitas Sains Al Qur'an

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32500/jebe.v7i2.11208

Abstract

Komunikasi merupakan hak dasar manusia, namun penyandang disabilitas rungu sering menghadapi hambatan dalam berinteraksi dengan masyarakat umum yang minim pemahaman bahasa isyarat. Penelitian ini bertujuan untuk mengimplementasikan dan mengevaluasi kinerja algoritma YOLOv11 dalam mendeteksi kata pada Bahasa Isyarat Indonesia (BISINDO) dan Sistem Isyarat Bahasa Indonesia (SIBI) secara real-time. Metode yang digunakan meliputi pengumpulan dataset sebanyak 1.745 citra yang mencakup 12 kelas kata, preprocessing menggunakan Roboflow untuk anotasi dan augmentasi, serta pelatihan model menggunakan Google Colab. Hasil penelitian menunjukkan bahwa model YOLOv11 mampu mendeteksi bahasa isyarat dengan sangat baik, mencapai nilai mean Average Precision (mAP@50) sebesar 98%, Precision 96.8%, dan Recall 96.4% pada tahap validasi. Implementasi sistem dilakukan berbasis web menggunakan framework Flask, memungkinkan deteksi interaktif melalui kamera. Secara keseluruhan, penelitian ini menunjukkan bahwa penerapan model YOLOv11 efektif dalam mendukung penerjemahan bahasa isyarat secara real-time. Implikasi dari penelitian ini adalah meningkatnya aksesibilitas komunikasi bagi penyandang disabilitas rungu, khususnya dalam interaksi sehari-hari dengan masyarakat umum, serta membuka peluang pengembangan sistem penerjemah bahasa isyarat yang lebih luas, adaptif, dan terintegrasi pada berbagai platform digital.
LSTM-Based Causal Attribution Modeling of the 2025 Sumatra Flash Flood Discourse on YouTube Jalia, Kunti Najma; Suwondo, Adi; Sibyan, Hidayatus
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 10 No. 1 (2026)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v10i1.2132

Abstract

Existing disaster sentiment analysis mainly focuses on emotional polarity classification, while often over-looking the causal reasoning that shapes public discourse on responsibility for disaster outcomes. This study proposes and assesses a Long Short-Term Memory (LSTM)-based causal attribution classification framework to examine YouTube comments related to the 2025 Sumatra flash flood. It compares LSTM performance with Sup-port Vector Machine (SVM) and Naïve Bayes baselines. A total of 17,503 publicly available comments were collected through the YouTube Data API v3 and processed into a final dataset of 12,299 comments. The com-ments were classified into two causal categories, human factor and nature/prayer factor, using lexicon-based scoring validated by three independent annotators (Cohen's κ = 0.81). The experimental results show that LSTM achieves 98.17% accuracy with strong stability (±0.25% standard deviation) under stratified five-fold cross-validation, substantially outperforming SVM (82.83%) and Naïve Bayes (75.04%). These findings indi-cate that sequence-based architectures can capture the contextual dependencies in causal attribution dis-course, offering a replicable framework for disaster risk communication monitoring systems.
Co-Authors Akh. Fawaid Amalia, Annida Asnawi, M. Fuat Bahrudin, Maulana Azis Fatin, Salsabilla Jalia, Kunti Najma Khabibah, Ummy Mahmudati, Rina Moh. Zaini Nur Hasanah Putri Rahmawati Said, Muhammad Arju Septiani, Dian Nabila Siti Hikmah, Siti Suwondo, Adi Syaefudin, Ahmad Wibisono, Muhammad Athar Zakia, Nadhifa Rif'aldina