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All Journal JURNAL SISTEM INFORMASI BISNIS IT JOURNAL RESEARCH AND DEVELOPMENT TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Teknik Informatika (JUTIF) Journal of Law, Poliitic and Humanities Malcom: Indonesian Journal of Machine Learning and Computer Science Science, Technology, and Communication Journal Scientific Journal of Informatics INOVTEK Polbeng - Seri Informatika
Okfalisa Okfalisa
Department of Information Technique, FST, UIN SUSKA
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Application of ADASYN Technique in Classification of Stroke Disease using Backpropagation Neural Network zikrillah aulia, said rizki; okfalisa, okfalisa; haerani, elin; oktavia, lola
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/jdhv9s39

Abstract

The high prevalence of stroke in Indonesia and the challenge of imbalanced medical record data are major obstacles to the development of an accurate early detection system. This research aims to build a reliable stroke classification model by applying the ADASYN (Adaptive Synthetic Sampling) oversampling technique to address class imbalance before the data is processed using the Backpropagation Neural Network (BPNN) algorithm. The ADASYN technique is applied with the goal of reducing the bias that arises from the imbalanced data distribution between the majority and minority classes. Testing was conducted through various data splitting scenarios (70:30, 80:20, 90:10) and hyperparameter variations to find the optimal configuration. The best results were obtained with the 90:10 data split scheme, using an architecture of 29 neurons and a learning rate of 0.01, which successfully achieved peak performance with an accuracy of 90.46% and an F1-score of 91.03%. This study demonstrates that the combination of ADASYN and BPNN is a highly effective approach for producing a stroke prediction model that is not only accurate but also sensitive to the minority class, thus having great potential as an early detection support tool in the healthcare sector.
Klasifikasi Sentimen Masyarakat Terhadap Kaesang Pangarep pada Media Sosial Twitter/X Menggunakan MLP Classifier dengan Fitur FastText Tarmizi, Veci Cahyono; Agustian, Surya; Okfalisa, Okfalisa; Pizaini, Pizaini
TIN: Terapan Informatika Nusantara Vol 6 No 7 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i7.8815

Abstract

Social media has become a primary channel for the public to express their opinions and reactions toward various political developments in Indonesia. One of the prominent discussions revolves around Kaesang Pangarep’s appointment as the Chairman of the Indonesian Solidarity Party (PSI). This study aims to analyze and classify public sentiment regarding this issue by employing the Multi-Layer Perceptron (MLP) algorithm integrated with FastText-based text representation. The dataset was collected from Twitter using keywords such as “Kaesang PSI”, and was further expanded with additional data from general topics including Covid-19 and Open Topic, ensuring a balanced distribution across positive, neutral, and negative sentiment categories for a more comprehensive representation of public opinion. The model’s performance was evaluated through four metrics: accuracy, precision, recall, and F1 Score. The experimental results demonstrate that the MLP–FastText model achieved consecutive scores of 0. 5129 for F1 Score, 0. 6035 for accuracy, 0. 5319 for precision, and 0. 5996 for recall. These findings indicate that the combination of MLP and FastText effectively captures sentiment patterns within textual data, particularly in the context of unstructured and dynamic social media content, and performs well when enhanced with relevant external data augmentation strategies.
Co-Authors Ahmad, Sayyidina Anshari Al-Sa’ban, M Dafa Alfitri, Rahmat Aslati Aslati Azhar Azhar Belantara, M Abyan Che Hussin, Ab Razak Delifah, Nur Elin Haerani Erlina, Marni Fachry Abda El Rahman Fadhilah Syafria Fahruddin Fahruddin Finaldhi, Harry Fitri Insani Haerani, Elin Haerani Iswavigra, Dwi Utari kurnia, fitra Luh Kesuma Wardhani Maulana, Muhammad Rizky Muslimin, Al’hadiid Najwa, Nina Fadilah Nazruddin Safaat H Ningrum, Melia Vivi Oktavia, Lola Pizaini Pizaini Pranggono, B. Pratama, M Farhan Aulia Rahmad Abdillah Robert Libra Ruri Hartika Zain Rusnedy, Hidayati Saktioto Saktioto Santana, Qistan Alif Setiaji, Haris Setiawan, Adil Simaremare, Harris Simaremare Siti Ummi Masruroh Surya Agustian Tarmizi, Veci Cahyono Vernando, Julio Yusra, Yusra zikrillah aulia, said rizki