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All Journal Bulletin of Electrical Engineering and Informatics JOIN (Jurnal Online Informatika) JMM (Jurnal Masyarakat Mandiri) Infoman's: Jurnal Ilmu-Ilmu Manajeman dan Informatika JOINT (Journal of Information Technology Jurnal Teknik Informatika (JUTIF) Data Sciences Indonesia (DSI) Journal of Islamic Economics and Business Scientica: Jurnal Ilmiah Sains dan Teknologi Infomans: Jurnal Ilmu-ilmu Informatika dan Manajemen Journal of Visionary Sharia Economy (JOVISHE) JIMT: Jurnal Informatika, Multimedia dan Teknik Jurnal Teknologi Riset Terapan
Firmansyah, Esa
STMIK Sumedang
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering Physics Social Sciences Other

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Journal : Jurnal Teknik Informatika (JUTIF)

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Performance Optimization of Support Vector Machine with SMOTE for Multiclass Stunting Prediction in Sumedang District, Indonesia Fadil, Irfan; Surya Manggala, Ramdani; Firmansyah, Esa; Helmiawan, Muhammad Agreindra
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4843

Abstract

The percentage of stunting toddlers in Sumedang Regency is the highest compared to other nutritional problems. Stunting imposes a significant risk to the future quality of human resources. This study explores the performance of the Support Vector Machine (SVM) algorithm in predicting the stunting status of toddlers in Tanjungmedar Subdistrict, the region with the highest incidence of stunting cases in Sumedang Regency in 2020. The testing uses RapidMiner software and applies the Synthetic Minority Oversampling Technique (SMOTE) to overcome the imbalanced dataset so that the resulting performance can be optimized. Accuracy, precision, recall, and F1-score are measured in performance evaluation using a confusion matrix. The findings demonstrate that SMOTE might adjust the distribution of target classes in the dataset to maximize the SVM algorithm's performance. At the start of the test, the SVM model produced an accuracy of 85.10%. After applying SMOTE, the accuracy of the SVM model increased to 89.08%. The F1-score also increased for each class, except for the Normal class, which decreased slightly. These results demonstrate the suitability of SVM combined with SMOTE for health-related multiclass classification tasks, especially in imbalanced public health datasets, contributing to the advancement of applied machine learning in healthcare informatics.
Quantitative Analysis of the Key Factors Driving Cybersecurity Awareness Among Information Systems Users Helmiawan, Muhammad Agreindra; Firmansyah, Esa; Herdiana, Dody; Akbar, Yopi Hidayatul; Subiyakto, A’ang; Rahman, Titik Khawa Abdul
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4861

Abstract

Cybersecurity threats are increasingly complex and widespread, posing significant risks to individuals and organizations. However, many studies tend to address the technological or behavioral aspects separately. The study uses a survey-based quantitative approach using PLS-SEM to analyze key factors that influence cybersecurity awareness, including demographics, training, psychological bias, and organizational culture. The findings suggest that several constructs-such as threat awareness, perceived risk, and education-significantly predict cybersecurity awareness and behaviour. Notably, the model yields an R² value of up to 0.703 with a strong path significance (p < 0.05), which underscores the robustness of the relationship. This study offers an integrated perspective on cybersecurity by bridging the psychological, educational, and organizational dimensions. It highlights cybersecurity awareness as a mediating construct that links upstream factors to secure user behavior-a relational structure that has not been explored in previous research.
Co-Authors Al Ghifari*, muhammadMuhammad Alvin Al-Fajr, Fikry Haikal Ali Rahman Andres Nodas Ansyari, Atikah Rifdah Anugrah, Robi Asri, Yessy Bayu Rizki Beben Sutara, Beben Binti Abd. Rahman, Aedah Darmawan, Sofyan Dody Herdiana Dwi Yuniarto Dwina Kuswardani, Dwina Ely, M. Jafar Emilia Emilia Fhatturohmah, Siska Helmiawan, Muhammad Agre Husnulmar’ati, Ghina Irfan Fadil Jumadi Jumadi Maulana , Moch Agus Tono Mohamad Irfan Muh Akbar Tamrin Muhammad Agreindra Helmiawan Muhammad Fajri Muhammad Firmansyah, Muhammad Muhammad Ghufron Nurfalah, Kamal Pramudya, Pranata Pramudya, Widi Rahman, Titik Khawa Abdul Ramadhan, Naufal Dzaky Ramadhani, Sonia Rospita, Sonia Setiawan, Hilal Naufal Sidiq, Adityansyach Umar Silviani, Listia Sofian, Yanyan Subiyakto, A'ang Subiyakto, A’ang Suliyanti, Widya Nita Surya Manggala, Ramdani Ulil Hikmah, Hilda Wildan Budiawan Zulfikar Yopi Hidayatul Akbar Yulia Sariwaty S, Yulia