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All Journal Proceeding SENDI_U Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi Jurnal Biologi Tropis JSiI (Jurnal Sistem Informasi) Jurnal Penelitian dan Pengabdian Kepada Masyarakat UNSIQ Menara Ilmu bit-Tech Jurnal Abdi Insani Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat Infotech: Journal of Technology Information IJECS: Indonesian Journal of Empowerment and Community Services Journal Computer Science and Informatic Systems : J-Cosys Journal of Economic, Business and Engineering (JEBE) Jurnal Ilmiah IT CIDA : Diseminasi Teknologi Informasi Jurnal Teknik Informatika Jurnal Bisnis Manajemen dan Akuntansi Duta Abdimas: Jurnal Pengabdian Masyarakat Biner : Jurnal Ilmiah Informatika dan Komputer Proceeding of International Conference Health, Science And Technology (ICOHETECH) Adopsi Teknologi dan Sistem Informasi eProceedings of Management Innovative: Journal Of Social Science Research Bengawan :Jurnal Pengabdian Masyarakat International Journal of Trends in Accounting Research Journal Of Artificial Intelligence And Software Engineering Persona: Kajian Bahasa dan Sastra Jurnal Informatika Polinema (JIP)
Oktaviani, Intan
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Other

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Journal : bit-Tech

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Website-Based Sales Transaction Data Monitoring Information System Risandi, Arfika Putri; Hasanah, Herliyani; Oktaviani, Intan
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2679

Abstract

Micro, Small, and Medium Enterprises (MSMEs) contribute significantly to the Indonesian economy, yet many still rely on manual transaction recording using Excel, which often results in errors, delays in reporting, and difficulties in accessing historical sales data. These limitations hinder effective decision-making and reduce operational efficiency. In response to these challenges, this study aims to develop a website-based sales transaction data monitoring information system that enables real-time monitoring and structured data management for various user roles: admin, reseller, and leader. The system was developed using the Rapid Application Development (RAD) method, which emphasizes fast prototyping and user feedback to ensure functionality meets actual needs. Features include automated Excel data uploads, interactive dashboards, and reseller performance visualizations tailored to user roles. Testing was conducted using Black Box Testing and User Acceptance Testing (UAT). The results indicate that all system functions operated according to design specifications and received positive feedback from users regarding usability and effectiveness. The implementation of this system successfully addresses the common problems faced by MSMEs in transaction management by improving accuracy, speeding up reporting, and enhancing monitoring transparency. In conclusion, this system offers a practical solution that is ready to be adopted by MSMEs with similar transaction recording issues, supporting digital transformation and operational efficiency in the MSME sector.
Predicting Social Media Addiction Using Machine Learning and Interactive Visualization with Streamlit Tegar, Alfiyan Tegar Budi Satria; Hasanah, Herliyani; Oktaviani, Intan
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2715

Abstract

The increasing use of social media among students has raised concerns regarding its impact on mental health, academic performance, and interpersonal relationships. This study introduces a Streamlit-based web application that predicts social media addiction levels using the Random Forest algorithm. The model incorporates variables such as daily usage hours, mental health scores, and conflicts caused by social media. The innovation of this approach lies in combining machine learning with interactive visualizations for real-time addiction prediction, providing a user-friendly, data-driven tool for early screening. Unlike traditional models that primarily rely on self-reported data or simple metrics, this method integrates multiple behavioral and psychological indicators to improve prediction accuracy. The model outperforms linear regression in all key metrics, achieving an R² value of 0.9903, which explains 99.03% of the variation in addiction scores. It also reports a low Mean Absolute Error (MAE) of 0.0370, Mean Squared Error (MSE) of 0.0244, and Root Mean Squared Error (RMSE) of 0.1561, highlighting its accuracy. Black-box testing showed an average error of just 0.354% in predictions and confirmed that the app’s features function effectively across devices. These findings emphasize the potential of this application as an effective tool for identifying students at risk of social media addiction, enabling timely interventions, and offering a foundation for future improvements through real-time data integration and advanced machine learning models.
Co-Authors Adrianto, Fajri Agus Riyanto Agustina Agustina, Melinda Ajeng Ayu Arumsari Al Ayyubi, Raihan Abdurrahim Alamsyah, Bintang Ashari, Arya Atina, Vihi Bramantyo, Rakesh Budi Suryono, Arif Desriani, Rahmi Dewanti, Cahyaning Dwi Hartanti Eko Purwanto Ely Nastiti, Faulinda Ety Meikhati Faulinda Ely Nastiti Febrianisa, Amanda Eka Hafiz, Abdullah Ahmad Hasanah, Herliyani Heppy Millanyani Husin, Husna Sarirah Ilyas, Daffa Isnanto, Erliana Putri Joko Sutarto Jowanka, Axzara Wirid Isra Mahbub, Hanif Marginingsih, Marginingsih Marta, Fadhillah Moh Muhtarom Nofikasari, Indah Novianto, Ricky Eko Nurchim Nurchim Nurohman, Nurohman Pipin Widyaningsih Pradana, Rico Yoga Prasetia, Esa Galang Prasetyo, Adi Tri Prasetyo, Eri Angga Purawanto, Eko Putri, Khalisah Nabila Ratna Dewi Risandi, Arfika Putri Santosa, Tri Djoko Saraswati, Ririn Uke Sigit Purnomo Sumarlinda, Sri Sundari Sundari Sundari Sundari, Muncar Susanti, Hemalia Susanty, Meredita Tegar, Alfiyan Tegar Budi Satria Tri . Wiharti Tri Joko Raharjo Triana Triana, Triana Wijiyanto Wijiyanto, Wijiyanto Zulkifli, Suripto Moh.