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All Journal Jurnal Ilmiah Informatika Komputer Techno.Com: Jurnal Teknologi Informasi Jurnal Penelitian Pendidikan Jurnal Sistem dan Informatika Scientific Journal of Informatics CESS (Journal of Computer Engineering, System and Science) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI ILKOM Jurnal Ilmiah Data Science: Journal of Computing and Applied Informatics Jurnal Informatika Global Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika JTIK (Jurnal Teknik Informatika Kaputama) SKANIKA: Sistem Komputer dan Teknik Informatika Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Computer Science and Information Technology (CoSciTech) Jurnal Senopati : Sustainability, Ergonomics, Optimization, and Application of Industrial Engineering Jurnal Pengabdian Kepada Masyarakat Simpatik: Jurnal sistem Informasi dan Informatika JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Unnes Journal of Mathematics Konstelasi: Konvergensi Teknologi dan Sistem Informasi Jurnal Informatika Teknologi dan Sains (Jinteks) Malcom: Indonesian Journal of Machine Learning and Computer Science JUSIFOR : Jurnal Sistem Informasi dan Informatika Jurnal ilmiah teknologi informasi Asia Indonesian Journal of Mathematics and Natural Sciences
Florentina Yuni Arini
Universitas Negeri Semarang
Arts Humanities Automotive Engineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Nursing Public Health Social Sciences Veterinary Other

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ANT NESTING OPTIMIZATION UNTUK PENINGKATAN AKURASI CNN DALAM DIAGNOSTIK BRAIN TUMOR Arini, Florentina Yuni; Oktavian, Aloysius; Hidayaturrohmah, Nia Nur; Aryaputra, Daffa Pramata; Syanjalih, Alul Hidja; Aldevis, Mohammad Farrel; Aisar, Muhammad Zidan
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 9 No 1 (2026): Jurnal SKANIKA Januari 2026
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v9i1.3669

Abstract

This study discusses the application of a new optimization algorithm, namely Ant Nesting Optimization (ANO), to improve the performance of Convolutional Neural Networks (CNN) in brain tumor classification based on MRI images. ANO is inspired by the behavior of Leptothorax ants in selecting optimal nest locations, which is applied in the model's exploration and exploitation processes. The optimized CNN model shows an increase in classification accuracy of up to 97%, with superior performance in detecting various types of brain tumors. The evaluation results show that the proposed model has faster and more stable loss convergence compared to the standard model. This optimization method not only improves classification precision but also accelerates model stabilization during the training process. With these results, the research proves the effectiveness of ANO as an optimization method in deep learning networks and opens up wider application opportunities in the field of artificial intelligence-based diagnostics.
Optimizing K-Nearest Neighbor Using Ant Colony Optimization for Heart Disease Classification Arini, Florentina Yuni; Pongthanoo, Patcharanikarn; Salsabila, Kansa Maulina; Raihan, Muhammad; Muzakki, Naufal Habib
Data Science: Journal of Computing and Applied Informatics Vol. 10 No. 1 (2026): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v10.i1-23647

Abstract

Heart disease is one of leading causes of death globally, making early detection essential for improving clinical outcomes. This study presents a heart disease prediction approach using the K-Nearest Neighbor (KNN) algorithm, addressing class imbalance with Synthetic Minority Over-sampling Technique (SMOTE) and enhancing feature selection through Ant Colony Optimization (ACO). Exploratory data analysis identified age, gender, cholesterol, blood pressure, e xercise-Induced Angina (EIA), ST-segment depression, number of affected vessels, and thalassemia status as key indicators of disease severity. KNN model achieved 0.90 accuracy with balanced precision and recall. The employment of SMOTE improved sensitivity for the minority class, slightly reducing overall accuracy to 0.88. However, ACO as hyperparameter tuning KNN able to produce promising accuracy 0.91. This result indicate that combining KNN with metaheuristic optimization provides a reliable, interpretable method for heart disease prediction, offering valuable support for clinical decision-making and risk assessment.
Analisis Aksesibilitas Tokopedia Berbasis Mobile Menggunakan User Experience Questionnaire Arini, Florentina Yuni; Habibi, Mahdi; Kaltsum, Zahra Zakiyah; Rahman, Muhammad Rifqi; Putra, Pramudya Kirana Mandala; Pradana, Samudra Azriel
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 6 No 4 (2025)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.6.4.519

Abstract

This study aims to comprehensively examine the accessibility level and user experience of Tokopedia on mobile based on the Human-Computer Interaction (HCI) approach by employing the User Experience Questionnaire (UEQ) as the primary instrument. Data collection involved 50 active Tokopedia users, with the UEQ instrument comprising 26 statements and a 7-point response scale. Six core scales—attractiveness, perspicuity, efficiency, dependability, stimulation, and novelty—were evaluated and analyzed by calculating the average score for each aspect and comparing it to the standard UEQ benchmark. The results demonstrate that Tokopedia excels in attractiveness, perspicuity, and efficiency, while innovation in the novelty and stimulation scales remains a challenge that requires further optimization. This study underlines the importance of UX evaluation based on HCI as a foundation for developing inclusive features to support an optimal and sustainable user experience
Peningkatan Prediksi Kelainan Tekanan Darah dengan Logistic Regression dan Random Forest: Pendekatan Sequence Machine Learning Florentina Yuni Arini; Rahmat Hidayat; Putra, Arzaki Zunior; Furqon, Muhammad Nur; Hilmi, Muhammad Zuniar
PaKMas: Jurnal Pengabdian Kepada Masyarakat Vol 6 No 1 (2026): Mei 2026
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/pakmas.v6i1.4497

Abstract

Early detection of blood pressure abnormalities plays a critical role in preventing and managing cardiovascular diseases, which remain the leading cause of death globally. This study proposes a sequence machine learning approach that combines Random Forest (RF) and Logistic Regression (LR) to enhance the accuracy of abnormal blood pressure prediction. The dataset, obtained from Kaggle, includes various clinical and lifestyle-related features. Data preprocessing involved handling missing values, label encoding, and normalization of numerical features. Evaluation of individual models showed that Random Forest achieved an accuracy of 0.83, while Logistic Regression reached 0.75. The sequence model, which incorporates Random Forest-generated prediction probabilities as an additional feature in Logistic Regression, improved the prediction performance with an accuracy of 0.84. Feature importance analysis identified hemoglobin level, chronic kidney disease, and genetic pedigree coefficient as the most influential predictors in classifying abnormal blood pressure. These findings highlight the effectiveness of the sequence approach in addressing the complexity of medical data and improving the precision of clinical decision support systems for hypertension diagnosis and management. Recommendations include developing advanced ensemble models, collecting longitudinal data, and conducting external validation to enhance model generalizability across diverse clinical populations.
KLASIFIKASI ANEMIA MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR DAN KANGAROO OPTIMIZATION ALGORITHM Hexa Sakti Tunjung Hidayat; Florentina Yuni Arini
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 8 No 2 (2026): EDISI 28
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v8i2.7373

Abstract

Anemia merupakan masalah kesehatan global yang ditandai dengan penurunan kadar hemoglobin, yang jika tidak dideteksi secara dini dapat menyebabkan komplikasi serius seperti gangguan psikomotorik dan peningkatan risiko maternal. Penelitian ini bertujuan untuk mengoptimalkan sistem klasifikasi anemia dengan mengintegrasikan algoritma K-Nearest Neighbor (kNN) dan Kangaroo Optimization Algorithm (KOA) guna meningkatkan akurasi diagnosis melalui seleksi fitur dan optimasi parameter. Metode penelitian ini mencakup prapemrosesan data Complete Blood Count (CBC) dari dataset klinis, yang kemudian diproses menggunakan KOA untuk mengidentifikasi subset fitur paling relevan dan menentukan nilai k optimal pada kNN berdasarkan mekanisme regulasi energi dan perilaku melompat kangguru. Hasil analisis menunjukkan bahwa integrasi KOA secara signifikan mengatasi kelemahan kNN standar terhadap dimensi data tinggi, meningkatkan akurasi klasifikasi hingga mencapai level kompetitif di atas 94% dibandingkan metode tanpa optimasi yang hanya mencapai kisaran 71%. Simpulan dari penelitian ini menegaskan bahwa pendekatan metaheuristik berbasis kangguru sangat efektif dalam meminimalkan kesalahan diagnosis medis, memberikan kontribusi penting bagi pengembangan sistem pendukung keputusan klinis yang cepat dan reliabel untuk tenaga medis dalam menangani kasus anemia secara global.
Co-Authors Abas Setiawan Abdurrafi, Muhammad Agus Setyawan Ahmad Mustofa Hadi Ahmad Mustofa Hadi Ahmad Rozaq Heryansyah Ahmad Zidhan Ilmana Aisar, Muhammad Zidan Aisyah Nathania Araminta Aji, Yusuf Pandu Satrio Alaida, Salma Keysha Alamsyah - Aldevis, Mohammad Farrel Amin Suyitno Amrullah, Reza Zaidan Ananda Hisma Putra Kristianto Anggraeni, Dinda Ayu Anwar, Alfani Salsabilla Ardiansyah, Ikhsan Aryaputra, Daffa Pramata Asfino, Fadli Nugraha Astagina, Paramesti Athaya, Ikhsan Rakha Aufa Putra Wicaksono Awan Saputra Romadhoni Bagaskara, Josephin Nova Bhimawan, Farrel Fatih Brata, Prayoga Adi Dewanti, Rahima Ratna Duankhan, Poomin Endang Sugiharti, Endang Fadhlullah, Muhammad Azzam Fajariansyah, Ridwan Faqih, Muhammad Najmuddin Farrel Athaillah Putra Fatih Akbar Alim Putra Fatiha Misbah, Mutia Zahra Firdaus Zahid, Ahmad Galvin Fittra Marga Ardana Furqon, Muhammad Nur Gerard Sean Dwayne Habibi, Mahdi Haryolukito Pambudi, Fawwaz Hernawan, Yoga Heryansyah, Ahmad Rozaq Hexa Sakti Tunjung Hidayat Hidayaturrohmah, Nia Nur Hilmi, Muhammad Zuniar Inoru Nian Alfita Intan Permata Sari Fauziah Irfan, Mohammad Syarif Isa Akhlis Isnaeni, Siti Itsna Sabila Hidayati Januar Pancaran Nur Fajri Julianto, Richy Kaltsum, Zahra Zakiyah khairunnisa, Nadhia Adzqiya Lyon Ambrosio Djuanda Maloringan, Ariel James Mardlootillah, Hanif Ilmi Milannisya, Anya Kawakibi Much Aziz Muslim Muhammad Alvin Adinata Muhammad Lutfi Wibowo Muhammad Sulthonul Izza Mukti, Asteen Retno Muthia Nis Tiadah Muzakki, Naufal Habib Nafi', Raihan Muhammad Naryapramono, Afrilza Daffa Nathania Adristina Niratha, I Gede Ardhy Oktavian, Aloysius Pambudi, Fawwaz Haryolukito Pastika, Puan Bening Pongthanoo, Patcharanikarn Pradana, Samudra Azriel Prameswari, Della Egyta Pratama, Eric Vibriano Julia Putra, Arzaki Zunior Putra, Pramudya Kirana Mandala Putri, Farah Wahida Rizkia Putriaji Hendikawati Radhiti, Brigita Winona Elvaretta Rafi, Dhifansa Pradibtya Raharjo, Bagus Purbo Rahima Ratna Dewanti Rahman, Muhammad Rifqi Rahmat Hidayat Raihan, Muhammad Ramadhan, Farhan Husyen Ramadhan, Taufiqur Ramdhani, Khusnun Najwa Rifan, Slamet Rinandi, Tyto Riza Arifudin Rizky Aulia Adi Saputro Romadhoni, Awan Saputra Ryo Pambudi Said, Danish Adli El Salsabila, Kansa Maulina Santoso, Tony Budi Saputra, Gagah Suryanatha Athallah Saputro, Rizky Aulia Adi Sari, Yuliana Mustika Satria, Diva Sekar Tri Handayani Septiana, Dina Wachidah Sihombing, Nico Anselmus Supriyono Supriyono Syanjalih, Alul Hidja Toharo, Munajid Varindya Ditta Iswari Wahyudiantoro, Rizky Tri Warianta, Dwi Tatang Whisnu Ulinnuha Setiabudi, Whisnu Ulinnuha Wibowo, Muhammad Lutfi Wicaksana, Rangga Winata, Ardin Zaenal Abidin