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All Journal Jurnal Ilmiah Pengabdian dan Inovasi JUSTIFY : Jurnal Sistem Informasi Ibrahimy COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi JAR'S (Journal of Advanced Research in Informatics) Proceeding Of International Conference On Education, Society And Humanity Khatulistiwa : Journal of Artificial Intelligence
Beny Yusman
Universitas Hafshawaty Zainul Hasan
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Social Sciences Transportation

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Deteksi Objek untuk Menghitung Perkiraan Kalori Makanan Menggunakan Metode R-CNN Mask Berbasis Web Nadiyah, Nadiyah; Putri, Merlina Eka; Khairi, Matlubul; Furqan, Moh.; Yusman, Beny
COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi Vol 5, No 1 (2024): Transformasi Digital: Tren dan Tantangan dalam Era Revolusi Industri 4.0
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/coreai.v5i1.8982

Abstract

Diet sebagai pengaturan pola makan seimbang yang sengaja dilakukan untuk mencapai tujuan tertentu. Pelaku diet defisit kalori harus selalu menghitung jumlah kalori dari makanan yang dikonsumsi, salah satu caranya adalah dengan menimbang setiap jenis makanan. Jika membawa timbangan kemana pun kita pergi kurang fleksibel. Dengan memanfaatkan tren foto makanan saat ini, estimasi jumlah kalori makanan dapat dihitung dengan mudah. tujuan dari penelitian ini adalah menghasilkan sebuah aplikasi untuk mendeteksi jumlah kalori pada makanan dengan menggunakan metode Mask Region Convulutional Neural Network (Mask R-CNN) berbasis web. Manfaat dari penelitian ini adalah untuk memudahkan para pelaku diet dalam menghitung estimasi jumlah kalori melalui foto makanan. Pada penelitian ini diusulkan untuk menggunakan metode Mask RCNN untuk mendeteksi kalori pada makanan berbasis web dari citra digital. Dataset yang digunakan pada penelitian ini menggunakan 5 jenis makanan yaitu ayam geprek, baso aci, hamburger, seblak dan bakwan dengan jumlah data 220 citra dan masing-masing kategori 50 citra dan untuk data testing menggunakan 22 citra setiap kelas makanan. Model pada penelitian ini dilatih dengan menggunakan metode Mask RCNN, yaitu data training menggunakan epoch 20 dengan nilai loss 0.2759, nilai loss val 0.8429 dan waktu 5226s. Hasil dari implementasi model berbasis web menggunakan framework flask  pada data uji coba citra sebanyak 22 gambar makanan dengan memperoleh nilai akurasi ayam geprek 60% dengan total kalori sebanyak 246,0 disetiap kelas, baso aci 60% dengan total kalori sebanyak 218,0 disetiap kelas, hamburger 60% dengan total kalori sebanyak 369,0 disetiap kelas, seblak 80% dengan total kalori sebanyak 269,0 disetiap kelas dan bakwan 40% dengan total kalori sebnayak 137,0 di setiap kelas.
Spam SMS Classification Analysis Using Naive Bayes with Python Language Beny Yusman
Khatulistiwa SMART: Science, Methodology, Artificial intelligence, Research, and Technology Vol 1 No 2 (2025): Juni 2025
Publisher : Khatulistiwa : Journal of Artificial Intelligence

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Abstract

Short Message Service (SMS) continues to be widely used in Indonesia, both by official institutions and private entities, despite the growing prevalence of internet-based communication technologies. This study aims to classify SMS messages into three categories—normal SMS, promotional SMS, and fraudulent (spam) SMS—using the Naïve Bayes algorithm. The dataset used in this study comprises 1,143 records, obtained from an open-source platform on GitHub. The research stages include dataset collection, text preprocessing (consisting of case folding, tokenization, filtering, normalization, and stemming), term weighting using two text representation techniques: Count Vectorizer and TF-IDF, and classification using the Multinomial Naïve Bayes algorithm. Classification performance was evaluated using a confusion matrix, along with accuracy, precision, recall, and F1-score metrics. The results show that both combinations—Multinomial Naïve Bayes with Count Vectorizer and with TF-IDF—performed well in classifying SMS messages. The Count Vectorizer model achieved an accuracy of 93%, while the TF-IDF model demonstrated competitive precision and recall values. These findings confirm that the Naïve Bayes algorithm, when paired with appropriate text representation techniques, can serve as an effective solution for automatic SMS classification systems, particularly for short messages in the Indonesian language. This research also opens opportunities for exploring more advanced classification algorithms in future studies.
Pendampingan Literasi Digital untuk Mengurangi Risiko Kejahatan Siber Membentuk Masyarakat yang Lebih Aman M. Syafiih; Nadiyah; Khairi, Matlubul; Moh. Furqan; Beny Yusman
Jurnal Ilmiah Pengabdian dan Inovasi Vol. 2 No. 4 (2024): Jurnal Ilmiah Pengabdian dan Inovasi (Juni)
Publisher : Insan Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57248/jilpi.v2i4.456

Abstract

This community service activity aims to improve digital literacy and cybersecurity awareness in Paiton Sub-district as a response to the increasing risk of cybercrime in the community. The approach used involves the Participatory Action Research (PAR) method by involving various stakeholders, including the sub-district government, education office, and caregivers of Islamic boarding schools. The mentoring process includes a series of activities such as intensive training, interactive workshops, awareness campaigns through various media, as well as individual and group mentoring. These activities are designed to provide the Paiton community with a deep understanding of cyber threats, personal data protection techniques, and digital ethics. The results of these activities show significant improvements in digital literacy and changes in community behavior in using technology more safely. The formation of new institutions in the form of community groups and local cybersecurity teams is also evidence of the effectiveness of this collaborative approach. In conclusion, this service activity succeeded in creating social transformation by raising collective awareness of the dangers of cybercrime and producing a community that is more skilled in facing modern digital challenges. This program is expected to serve as a model for similar efforts in other regions to improve digital security and broader community welfare.
Sistem Analisis Kepadatan Lalu Lintas Menggunakan Teknologi YOLOv8 Nadiyah, Nadiyah; Yusman, Beny; Furqan, Moh.; Arifin, Zainal
COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi Vol 6, No 1 (2025): Kecerdasan Buatan dalam Meningkatkan Efisiensi Bisnis
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/coreai.v6i1.12217

Abstract

Kemacetan lalu lintas menjadi salah satu tantangan utama di perkotaan yang memengaruhi efisiensi transportasi dan produktivitas masyarakat. Penelitian ini mengembangkan sistem analisis kepadatan lalu lintas berbasis YOLOv8, teknologi terbaru dalam deteksi objek. Dataset yang digunakan mencakup gambar kendaraan beranotasi dari berbagai kondisi. Model YOLOv8 dilatih untuk mendeteksi dan menghitung kendaraan secara real-time pada video. Evaluasi dilakukan berdasarkan akurasi dan kecepatan pemrosesan dalam berbagai kondisi pencahayaan dan cuaca. Hasil menunjukkan YOLOv8 mencapai akurasi deteksi 88%, membuktikan kemampuannya untuk menganalisis kepadatan lalu lintas secara efisien. Sistem ini berpotensi diimplementasikan dalam manajemen lalu lintas cerdas untuk mengoptimalkan waktu sinyal dan mengurangi kemacetan. Penelitian selanjutnya dapat mengintegrasikan sistem ini dengan perangkat IoT untuk aplikasi transportasi cerdas yang lebih luas.
EFFECTIVENESS OF LOCAL-R LEARNING MODEL ON STUDENTS' LEARNING MOTIVATION IN SCHOOLS Handayani, Fatimah Citra; Bambang, Bambang; Yusman, Beny
PROCEEDING OF INTERNATIONAL CONFERENCE ON EDUCATION, SOCIETY AND HUMANITY Vol 2, No 2 (2024): Third International Conference on Education, Society and Humanity
Publisher : PROCEEDING OF INTERNATIONAL CONFERENCE ON EDUCATION, SOCIETY AND HUMANITY

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Abstract

Study This aims To ensure the effectiveness of learning models based on Literacy – Orientation – Collaboration – Reflection (LOK-R)towards motivation Study students at school. Research conducted with Library Research methods or Literature reveals the connection between learning models and motivation Study students. This is done because of learning models and motivation. The study has two keys. The main one correlates with the learning process in class. In addition, that study also discusses the implementation of the LOK-R learning model. From the results, the study concluded that the LOK-R learning model has proven very effective because it can increase the motivation of the Study as well as the enthusiasm of participants in the learning process. 
Pengembangan Sistem Informasi Keuangan Perumahan Berbasis Django dengan Pendekatan Extreme Programming dan Integrasi WhatsApp API Yusman, Beny
COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi Vol 5, No 2 (2024): Internet of Things (IoT): Aplikasi dan Potensinya di Masa Depan
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/coreai.v5i2.12550

Abstract

Penelitian ini mengkaji pengembangan sistem informasi keuangan warga perumahan berbasis web dengan metode Extreme Programming (XP) menggunakan framework Django serta integrasi notifikasi real-time melalui WhatsApp API menggunakan Fonnte. Permasalahan utama yang dihadapi dalam pengelolaan manual adalah rawan kesalahan pencatatan, keterlambatan pelaporan, dan rendahnya partisipasi warga. Hasil penelitian menunjukkan bahwa sistem yang dikembangkan mampu melakukan pencatatan transaksi secara akurat, menyajikan laporan keuangan otomatis, serta mengirimkan notifikasi tagihan secara cepat kepada warga. Pengujian Black Box membuktikan seluruh fungsi berjalan sesuai spesifikasi, sementara evaluasi pengguna dengan kuesioner skala Likert menunjukkan tingkat kepuasan yang tinggi terhadap kemudahan verifikasi pembayaran, peningkatan transparansi, dan efektivitas komunikasi keuangan. Dengan demikian, penerapan XP terbukti mempercepat siklus pengembangan serta menghasilkan sistem yang sesuai dengan kebutuhan pengguna. Rekomendasi penelitian selanjutnya adalah pengembangan fitur komunikasi dua arah dan integrasi dengan layanan pembayaran digital.
Pengembangan Sistem Informasi Kredit Poin Mahasiswa Di Fakultas Teknik Universitas Nurul Jadid Syafiih, M .; Yusman, Beny; Nadiyah, Nadiyah
Journal of Advanced Research in Informatics Vol 4 No 1 (2025): Journal of Advanced Research in Informatics
Publisher : Fakultas Teknik, Universitas Wiraraja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24929/jars.v4i1.4891

Abstract

The management of student credit points at the Faculty of Engineering, Nurul Jadid University (UNUJA) previously used a Laravel 5-based information system that had various limitations. Several important features could not function optimally due to outdated technology, and had not been integrated with the Nurul Jadid University Single Sign-On (SSO) system, thus complicating the centralized authentication process. This study aims to develop a modern, responsive, and integrated student credit point information system with Nurul Jadid University SSO using the Laravel 11 framework. The development method applied is Rapid Application Development (RAD), which focuses on accelerating the development process through prototyping, rapid iteration, and continuous receipt of user feedback. The results showed that the new system was able to fix all previously non-functional features and provide optimal authentication integration with SSO. Testing using the black-box method on all test scenarios resulted in a 100% feasibility rate, proving that the system has functioned according to specifications and met user needs. In addition, external testing showed the highest percentage of 98% (Strongly Agree) and the lowest percentage of 86% (Strongly Agree). These findings are significant because they demonstrate that utilizing the Laravel 11 framework with SSO integration can improve efficiency, accuracy, and transparency in student credit point management, while simultaneously supporting a more structured academic process.
Perancangan Sistem Pendukung Keputusan Penentuan Prioritas Proyek Pengembangan Aplikasi pada CV BOSpintar Jaya Yusman, Beny; Fadel, Moh.; M. Syafiih; Muafi; Bambang
JUSTIFY : Jurnal Sistem Informasi Ibrahimy Vol. 4 No. 2 (2026): JUSTIFY : Jurnal Sistem Informasi Ibrahimy
Publisher : Fakultas Sains dan Teknologi, Universitas Ibrahimy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/justify.v4i2.9079

Abstract

CV BOSpintar Jaya, a company engaged in application development services, faces challenges in determining project priorities when multiple development requests are received within a limited timeframe. Priority determination that relies on subjective judgment may lead to project delays, inefficient resource allocation, and decreased client satisfaction. This study aims to design a Decision Support System (DSS) to assist management in objectively and systematically determining the priority of application development projects. The research methodology includes requirements analysis, identification of project alternatives and decision criteria, criteria weighting, decision model design, as well as system interface and database design. The criteria used include project value, urgency level, development complexity, estimated duration, risk of requirement changes, and availability of developer resources. The calculation process produces preference values and project rankings as recommendations for project prioritization. The results show that the designed DSS is able to provide consistent, transparent, and traceable priority recommendations, thereby supporting faster and more accurate decision-making while reducing dependence on subjective assessments. The proposed DSS is expected to improve project planning efficiency, optimize resource allocation, and enhance the quality of application development services at CV BOSpintar Jaya.
Co-Authors Bambang Bambang Bambang Fadel, Moh. Furqan, Moh. Handayani, Fatimah Citra Khairi, Matlubul M. Syafiih Moh. Furqan Muafi Nadiyah Nadiyah Nadiyah Putri, Merlina Eka Syafiih, M . Zainal Arifin