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All Journal JURIKOM (Jurnal Riset Komputer) TIN: TERAPAN INFORMATIKA NUSANTARA Prosiding Seminar Nasional Rekayasa Teknologi Industri dan Informasi ReTII Jurnal Media Teknik Elektro dan Komputer
Rahmadani, Noni Fauzia
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Sistem Informasi Daftar Kunjungan Berbasis Web di Kementerian Agama Kabupaten Deli Serdang Nugroho, Agung; Rahmadani, Noni Fauzia
Jurnal Media Teknik Elektro dan Komputer Vol 1 No 2 (2024): Jurnal Media Teknik Elektro dan Komputer
Publisher : Yayasan Pendidikan Al-Yasiriyah Bersaudara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65371/metrokom.v1i2.79

Abstract

Manual recording of visit lists at the Ministry of Religious Affairs of Deli Serdang Regency faces challenges such as the risk of damage to guest books, archive accumulation, and difficulties in periodic recapitulation, which hinder effective data management and decision-making. To address these issues and support the implementation of the smart government concept, this research aims to develop a modern and efficient web-based visit list information system. Using the Research and Development (R&D) method and the waterfall software development model, the system was built through stages of requirements analysis, design, implementation, testing, and maintenance. The system includes two main interfaces: an admin section for visitor data management, recapitulation creation, Excel data export, and statistical visualization; and a user section for visit form submission and proof of registration. Built with PHP, Bootstrap, and MySQL, the system ensures a user-friendly interface and structured database. The application was tested using black-box testing to evaluate functionality and usability. Visitors successfully registered, with accurate proof of registration generated. Admin features, such as data management, recapitulation, and Excel export, operated effectively, while statistical visualizations provided actionable insights. The system demonstrated high performance, with fast response times and secure data management without loss or corruption. Usability testing revealed positive feedback, with users highlighting the intuitive interface and responsive design across devices. These results confirm the system’s ability to improve administrative efficiency, replace manual processes, and enhance transparency and accountability in public service delivery.
Design, Development, and Implementation of a Desktop-Based Laundry Management Application for Optimizing Operational Efficiency Rahmadani, Noni Fauzia; Syahputri, Rifdah; Nugroho, Agung; Nasution, Luftia Rahma; Siregar, Dzilhulaifa; Dewi, Aulia Kartika
TIN: Terapan Informatika Nusantara Vol 5 No 9 (2025): February 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i9.7045

Abstract

Manual management of laundry operations often faces various challenges, such as recording errors, limited monitoring of employee activities, and lack of transparency in financial reporting. To address these issues, this research aims to design and develop a desktop-based laundry management application that integrates order management, problem reporting, and financial management efficiently. The application is designed for three main user roles: staff, shop heads, and owners. Staff are responsible for inputting customer orders and reporting operational issues, shop heads monitor staff activities and handle problems, while owners can access financial reports and order activity recaps to support strategic decision-making. This research employs the Research and Development (R&D) method with the Waterfall software development model, encompassing requirements analysis, system design, implementation, and testing. Data collection was conducted through literature studies and direct observation of operational processes in multiple laundry businesses. The application was developed using the Java programming language and MySQL database and operates locally without requiring an internet connection. Testing results indicate that the system improves order processing efficiency by reducing recording time by approximately X% compared to manual methods, accelerates financial transaction recording, and enhances transparency in operational reporting. With this system, laundry management is expected to become more effective, accurate, and easily accessible to all users.
Deteksi Sentimen Publik terhadap Isu Lingkungan di Platform X (Twitter) Menggunakan Naïve Bayes dan Support Vector Machine untuk Mendukung SDGs 13: Climate Action Rahmadani, Noni Fauzia; Nasution, Luftia Rahma; Syahputri, Rifdah; Dewi, Aulia Kartika
Retii 2025: Prosiding Seminar Nasional ReTII ke-20 (Edisi Penelitian)
Publisher : Institut Teknologi Nasional Yogyakarta

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

Abstract

Isu lingkungan merupakan salah satu topik yang paling banyak dibahas di media sosial dan menjadi perhatian global seiring meningkatnya kesadaran terhadap perubahan iklim. Twitter sebagai salah satu platform dengan jumlah pengguna besar menjadi sumber data yang potensial untuk memahami persepsi publik terhadap isu lingkungan. Penelitian ini bertujuan untuk mendeteksi sentimen publik terhadap isu lingkungan di Twitter menggunakan algoritma Naïve Bayes dan Support Vector Machine (SVM). Data yang digunakan merupakan Climate Change Twitter Sentiment Dataset dari Kaggle, yang berisi ribuan cuitan tentang isu perubahan iklim dengan label sentimen positif, negatif, dan netral. Tahapan penelitian meliputi text preprocessing (pembersihan teks, tokenizing, dan stopword removal), ekstraksi fitur menggunakan Term Frequency–Inverse Document Frequency (TF-IDF), pelatihan model, serta evaluasi kinerja algoritma. Hasil pengujian menunjukkan bahwa SVM memiliki akurasi yang lebih tinggi dibandingkan Naïve Bayes, masing-masing sebesar 89,4% dan 84,7%. Temuan ini menunjukkan bahwa SVM lebih efektif dalam mendeteksi pola sentimen publik. Penelitian ini diharapkan dapat mendukung pencapaian Sustainable Development Goal (SDG) ke-13, yaitu Climate Action, melalui pemanfaatan teknologi kecerdasan buatan untuk memahami opini masyarakat terhadap isu lingkungan.
Prediction of Burnout Syndrome Risk in University Students Using the C5.0 Algorithm Rahmadani, Noni Fauzia; Sriani
JURNAL RISET KOMPUTER (JURIKOM) Vol. 13 No. 2 (2026): April 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v13i2.9550

Abstract

Burnout among university students is a serious issue that can reduce learning motivation, academic performance, and mental health. Approximately 25–30% of students experience burnout symptoms, which negatively affect concentration and academic productivity. Early detection is still limited due to the lack of accurate data analysis. This study aims to predict the risk level of student burnout using the C5.0 algorithm as a classification method capable of handling both categorical and numerical data. The research data were obtained from 306 students at Universitas Islam Negeri Sumatera Utara through an online questionnaire based on the Maslach Burnout Inventory–Student Survey (MBI-SS). The data were processed through cleaning, encoding, and splitting into training and testing sets using Python. The results show that the model achieves excellent classification performance, with an accuracy of 99.25% on the training set (precision 99.72%, recall 99.45%) and 97% on the testing set (precision 100%, recall 96%). The model also identifies the most influential attributes contributing to burnout, such as stress level and emotional exhaustion. The main contribution of this study is the development of an accurate and interpretable machine learning-based model for predicting student burnout risk. These findings provide practical implications for educational institutions in supporting early detection and designing data-driven preventive interventions, such as counseling services and stress management programs.
Co-Authors Dewi, Aulia Kartika Nasution, Luftia Rahma Nugroho, Agung Siregar, Dzilhulaifa Sriani Syahputri, Rifdah