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IMPLEMENTASI METODE RAPID APPLICATION DEVELOPMENT (RAD) DALAM PENGEMBANGAN SISTEM ENTERPRISE INDUSTRI TEKSTIL BERBASIS WEBSITE Ramadhan, Dimas Dharu; Mumpuni, Retno; Sihananto, Andreas Nugroho
Jurnal Informatika dan Teknik Elektro Terapan Vol. 12 No. 3S1 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3S1.5222

Abstract

Penelitian ini berfokus pada perancangan dan pengembangan aplikasi enterprise berbasis web yang khusus untuk industri konveksi tekstil di Bojonegoro, yang masih banyak menggunakan pencatatan manual atau aplikasi terpisah sehingga kurang efisien. Aplikasi ini dirancang untuk mengintegrasikan berbagai aspek operasional perusahaan, mulai dari manajemen, transaksi, hingga pengambilan keputusan, dengan tujuan meningkatkan efisiensi, produktivitas, dan koordinasi antar role dalam perusahaan. Pengembangan menggunakan metode Rapid Application Development (RAD), yang memungkinkan siklus pengembangan cepat dengan melibatkan klien secara intensif. Melalui prototyping yang berulang, klien dapat memberikan masukan langsung sehingga perangkat lunak dapat disesuaikan dengan kebutuhan hingga tercapai hasil yang optimal sesuai standar klien.
PERANCANGAN SISTEM KLINIK KESEHATAN DAN INVENTORI OBAT DI KLINIK KESEHATAN GRATIS AL-MUHAJIRIN Winata, Chycik Ayu; Mumpuni, Retno; Aditiawan, Firza Prima
Jurnal Informatika dan Teknik Elektro Terapan Vol. 12 No. 3S1 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3S1.5242

Abstract

Penelitian ini bertujuan untuk merancang dan mengembangkan sistem klinik kesehatan dan inventori obat di Klinik Kesehatan Gratis Al-Muhajirin. Sistem ini dirancang untuk meningkatkan efisiensi operasional klinik dengan memudahkan pengelolaan data pasien, kunjungan, dan stok obat. Menggunakan pendekatan Model-View-Controller (MVC), sistem ini diimplementasikan dengan fitur utama yang meliputi manajemen data pasien, pencatatan kunjungan, dan pengelolaan inventori obat. Uji coba sistem menunjukkan bahwa penerapan sistem ini dapat mengurangi kesalahan pengelolaan data dan meningkatkan efisiensi klinik secara keseluruhan. Hasil penelitian ini penting karena memberikan solusi praktis bagi klinik yang memiliki keterbatasan sumber daya dalam pengelolaan operasional harian.
IMPLEMENTASI FUZZY MAMDANI DALAM SISTEM PENILAIAN PERKEMBANGAN ANAK USIA DINI Arfiqi, Fawwaz; Mumpuni, Retno; Nurlaili, Afina Lina
JUTIM (Jurnal Teknik Informatika Musirawas) Vol 9 No 1 (2024): JUTIM (Jurnal Teknik Informatika Musirawas) JUNI
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jutim.v9i1.2299

Abstract

Pendidikan Anak Usia Dini (PAUD) adalah fase krusial sebelum anak-anak memasuki jenjang pendidikan formal. Untuk memperoleh pemahaman yang lebih mendalam mengenai pertumbuhan dan perkembangan anak usia dini, diperlukan suatu proses penilaian yang sistematis dan terstruktur. Penelitian ini bertujuan untuk mengembangkan dan mengimplementasikan algoritma Fuzzy Mamdani dalam sistem penilaian perkembangan anak yang terstruktur. Hasil dari penelitian ini menunjukkan algoritma Fuzzy Mamdani dapat mengolah data penilaian dari observasi periodik, menghasilkan tingkatan tentang perkembangan anak, serta sistem penilaian berjalan baik yang diverifikasi melalui pengujian Blackbox. Sehingga sistem ini diharapkan dapat meningkatkan efektivitas dan efisiensi dalam proses penilaian serta memungkinkan pemantauan yang lebih teratur dan menyeluruh terhadap tingkatan perkembangan anak yang dihasilkan oleh sistem.
Studi Performa TF-IDF dan Word2Vec Pada Analisis Sentimen Cyberbullying Ahmad Hilman Dani; Eva Yulia Puspaningrum; Retno Mumpuni
Router : Jurnal Teknik Informatika dan Terapan Vol. 2 No. 2 (2024): Juni : Router: Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Profesi Telekomunikasi dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v2i2.76

Abstract

On August 14, 2023, Indonesia had approximately 228 million social media users, a number that is expected to continue growing to reach 267 million by 2028. Social media can be used to spread both positive and negative information, and one of the various negative effects is cyberbullying. Consequently, much research is conducted in the field of machine learning to develop sentiment analysis. One crucial step in sentiment analysis is word weighting. The two most common word weighting methods are TF-IDF and Word2Vec. These methods can be compared to determine which one produces better classification results, allowing cyberbullying sentiments on social media to be detected more accurately. Based on nine test scenarios, the final results showed that TF-IDF performed better than Word2Vec in this study, with an accuracy of 84%.
Stres adalah masalah psikologis umum di kalangan Generasi Z, didorong oleh tekanan akademik, perbandingan sosial, dan paparan digital. Deteksi dini sangat penting untuk mencegah masalah kesehatan mental yang lebih parah seperti gangguan kecemasan, burnout Ananda Asa Firstha Affandi; Basuki Rahmat; Retno Mumpuni
bit-Tech Vol. 8 No. 3 (2026): bit-Tech - IN PROGRESS
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3375

Abstract

Stress is a common psychological issue among Generation Z, driven by academic pressure, social comparison, and digital exposure. Early detection is essential to prevent more severe mental health problems such as anxiety disorders, burnout, or depression. This study aims to optimize a web-based stress detection system using the Recursive Feature Elimination (RFE) method combined with the Random Forest algorithm. A dataset consisting of 500 psychological assessment records and 12 symptom features (G01 to G12) from A3M Consultant Surabaya was used as the basis for analysis. RFE successfully reduced the number of features to six key indicators, such as G01 (anxiety), G02 (emotional instability), G04 (restlessness), G08 (withdrawal), G09 (confusion), and G12 (suicidal thoughts) while maintaining high model accuracy. The baseline Random Forest using 12 features achieved 0.91 accuracy, while the RFE-optimized model with 6 selected features maintained a comparable accuracy of 0.90. The resulting model achieved an accuracy of approximately 0.90 based on Stratified K-Fold Cross Validation, showing consistent performance across folds. The optimized model was then integrated into a web application called “The Z Space,” which combines data driven predictions from Random Forest with rule- based reasoning using Forward Chaining. This hybrid approach ensures both interpretability and accuracy in determining stress levels. The findings highlight that RFE effectively reduces computational complexity without decreasing model performance, making it suitable for real time web implementation in stress detection systems for Generation Z.
Sistem Absensi Desktop Menggunakan Face Recognition dan Pendekatan Adaptive Attendance Monitoring Imam Afandy; Fawwaz Ali Akbar; Retno Mumpuni
bit-Tech Vol. 8 No. 3 (2026): bit-Tech - IN PROGRESS
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3487

Abstract

Manual attendance processes in higher education often face severe constraints regarding time inefficiency and vulnerability to data manipulation, specifically the prevalent issue of proxy attendance. Although Face Recognition technology has been widely adopted, most existing systems utilize a "once recognition" method, which fails to validate the student's presence throughout the entire lecture duration. This study aims to bridge this gap by developing an automatic desktop-based attendance system that integrates Face Recognition with a novel Adaptive Attendance Monitoring (AAM) approach. The proposed system utilizes a robust deep learning pipeline employing the Multi-Task Cascaded Convolutional Neural Network (MTCNN) for face detection and alignment, followed by FaceNet for generating 128-dimensional feature embeddings. To ensure real-time performance, the processing is accelerated by CUDA GPU technology on an NVIDIA RTX 4060 Ti. The system architecture follows a decoupled Client-Server model based on REST API, ensuring scalability and low-latency data transmission. The primary novelty of this research is the AAM algorithm, which continuously calculates the cumulative duration of a student's presence. A student is validated as "Present" only if they maintain visibility for at least 80% of the total session duration, effectively eliminating the "check-in and leave" loophole. Experimental results demonstrate that the system achieves a 100% recognition accuracy at an optimal distance of 1.0 meter under normal lighting conditions, with a processing latency consistently maintained under 100ms. These findings confirm that the proposed desktop-edge architecture significantly outperforms traditional mobile-based solutions in terms of stability, security, and continuous monitoring capabilities.
Web-Based Woven Fabric Recommendation System Integrated Fuzzy AHP and MOORA Based on User Preferences Mulyani Satya Bhakti; Retno Mumpuni; Afina Lina Nurlaili
bit-Tech Vol. 8 No. 3 (2026): bit-Tech - IN PROGRESS
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3768

Abstract

This study proposes a web-based decision support system for woven fabric selection by integrating the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA). The system addresses limitations in conventional selection processes that rely on subjective judgment and lack structured multicriteria evaluation. The proposed approach combines uncertainty-based weighting using Fuzzy AHP with objective ranking using MOORA, enabling a transparent and systematic decision-making process. Unlike previous hybrid MCDM-based recommender systems, this study integrates user preference modeling within a web-based framework and incorporates consistency validation and sensitivity analysis to ensure reliable results. The experimental results show that fabric type is the most influential criterion, with a weight of 0.33, and that alternative A4 consistently ranks as the best option, with an optimization value of 0.392. Sensitivity analysis shows that the ranking results remain stable across a 20% weight variation, and comparison with the SAW method confirms consistent rankings. In addition, User Acceptance Testing (UAT) involving 20 respondents achieves a score of 86.4%, indicating high usability and user satisfaction. However, the system is evaluated within a limited dataset and does not incorporate adaptive learning mechanisms. Therefore, future work is directed toward expanding the dataset and integrating machine learning-based approaches to enhance adaptability and scalability. Overall, the proposed system provides a structured, transparent, and empirically validated solution for multicriteria decision-making.
Design of Web-Based Decision Support System Using AHP and bcrypt Security Moh. Mario Subagio; Retno Mumpuni; Afina Lina Nurlaili
bit-Tech Vol. 8 No. 3 (2026): bit-Tech - IN PROGRESS
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3769

Abstract

This study presents the development of a web-based decision-support system to prioritize village administrative services using a structured, data-driven approach. This research addresses a gap in existing systems, which generally lack integration of systematic decision-making methods and robust security mechanisms, leading to inefficiency, low transparency, and subjective decision-making in village administrative processes. To overcome these limitations, the system integrates the Analytical Hierarchy Process (AHP) to evaluate multiple criteria, including submission time, document completeness, urgency level, service type, and request frequency, thereby enabling qualitative assessments to be transformed into measurable, comparable priority values. In addition, the bcrypt algorithm enhances system security by protecting user authentication data through password hashing, thereby mitigating risks such as unauthorized access, brute-force attacks, and rainbow-table attacks. The system is developed as a web-based application to ensure accessibility, scalability, and centralized data management. Evaluation results indicate that the system produces consistent and reliable priority rankings, as evidenced by a Consistency Ratio (CR) within the acceptable threshold, and demonstrates improved decision accuracy and operational efficiency compared to conventional manual approaches. Document completeness is identified as the most influential criterion in determining service priority. Furthermore, the proposed system offers broader applicability beyond village administration, particularly in other public service domains requiring transparent, efficient, and secure decision-making processes. Overall, this study contributes by integrating AHP and bcrypt within a unified system to enhance both decision quality and data security in digital administrative services.