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All Journal TEKNIK INFORMATIKA Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Sistemasi: Jurnal Sistem Informasi Seminar Nasional Teknologi Informasi Komunikasi dan Industri Krea-TIF: Jurnal Teknik Informatika Building of Informatics, Technology and Science Journal of Computer System and Informatics (JoSYC) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Computer Science and Information Technology (CoSciTech) Bulletin of Computer Science Research JUTECH : Journal Education and Technology Journal of Comprehensive Science Knowbase : International Journal of Knowledge in Database Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Teknik Indonesia Indonesian Journal of Multidisciplinary on Social and Technology INOVTEK Polbeng - Seri Informatika Jurnal Komtika (Komputasi dan Informatika)
Elin Haerani
UIN Suska Riau
Aerospace Engineering Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Transportation Veterinary Other

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Journal : jurnal computer science and information technology coscitech

 1 
Pengembangan Sistem Informasi Cerdas Career Guidance Berbasis Minat Di Perguruan Tinggi Haerani, Elin; Syafria, Fadhilah; Muhammad Yusuf Fadhillah
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

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

Abstract

The development of an intelligent information system career guidance based on interests is designed to address the difficulties faced by high school graduates in determining their major in higher education. Difficulties often arise due to confusion caused by a lack of guidance and information. To help address this issue, an intelligent interest- based major recommendation information system was developed using the breadth-first search (BFS) method, which consists of 8 interest categories based on the Rothwell-Miller Interest Blank theory (RMIB). This intelligent information system can provide direction and guidance (career guidance) to students in determining the right major according to their interests. Career guidance application services are highly needed by students who are currently in their unstable teenage years, struggling to determine their paths. This system generates output in the form of major recommendations along with related information. The system is built with PHP and MySQL and tested using the user acceptance test (UAT).
Implementasi Algoritma Random Forest pada Web-App Sebagai Instrumen Deteksi Dini Penyakit Diabetes Fauzan, Habibul; Haerani, Elin; Kurnia, Fitra; Yanti, Novi
Computer Science and Information Technology Vol 7 No 1 (2026): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v7i1.11261

Abstract

Diabetes is a chronic metabolic disease and one of the leading causes of death worldwide, with the number of sufferers projected to reach 1.3 billion by 2050. Delayed diagnosis remains a primary challenge, as nearly half of those affected are unaware of their condition in the early stages, thereby increasing the risk of fatal complications. Data mining approaches using classification algorithms have been widely utilized for early screening. However, the development of medical record models is often hindered by imbalanced data, which causes models to be biased toward the majority class and reduces detection sensitivity for the minority class (patients with diabetes). Furthermore, there is a lack of research integrating these predictive models into responsive application interfaces for end-users. Consequently, this study implements Random Forest optimized with the SMOTE (Synthetic Minority Over-sampling Technique) into a web-based application to serve as a practical early detection tool. Random Forest was selected for its ability to handle complex data and reduce the risk of overfitting. The research stages include data preprocessing, balancing training data using SMOTE, model parameter adjustment through hyperparameter tuning with Grid Search, and the development of a client-server architecture using AstroJS and Flask. The evaluation results demonstrate that the use of SMOTE significantly improves the model's ability to identify the minority class. The model achieved a Recall of 75.0% and an overall accuracy of 95.8%, effectively minimizing False Negative errors. The developed application was verified through Black Box Testing and was declared successful as a responsive and accessible early detection tool for both healthcare professionals and the general public.
Co-Authors -, Jasril Abdul Haris Kurnia Sandi Harahap Akbar, Lionita Asa Alfaridzy, M. Audi Amelia, Felina Ananda, Rahmadan Alam Ardan Anugrah, Wendy Baehaqi Cahyadi, Wahyu Dede Fadillah Elsilaturrahmi, Elsilaturrahmi Elvia Budianita Fadhilah Syafria Fahmi Rizal Fauzan, Habibul Febi Yanto Fitri Insani Fitri Wulandari Fitria Novitasari Gusti, Gogor Putra Hafi Puja Gusti, Siska Kurnia Habibi, M. Ilham hariansyah, Aldi Ikhsan, Tomi Indrizal, Habibi Putra Israldi, Tino Iwan Iskandar Jasril Jasril Kasman Rukun kurnia, fitra Mai Candra , Reski Maulani, Tedi Muhammad Affandes Muhammad fauzan Muhammad Fikry Muhammad Taufiq Muhammad Yusuf Fadhillah Muhammad, Raja Allifin Nazir, Alwis Novi Yanti Novriyanto Novriyanto Okfalisa Okfalisa Okfalisa Oktavia, Lola Oktavia, Lola Oktavia Prananda, Alga Pranata, Joni Rahman, Muhammad Taufikur Ramadhani, Siti Simatupang, Muhammad Farid Audi Rahman Surya Agustian Suwanto Sanjaya Syafria, Fadhillah Syah Utama, Isruel Vitriani, Yelvi Yusra, Yusra zikrillah aulia, said rizki