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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) JST ( Jurnal Sains Terapan ) INOVTEK Polbeng - Seri Informatika ILKOM Jurnal Ilmiah JURNAL TEKNOLOGI DAN OPEN SOURCE Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Jurnal Riset Informatika Jurnal Informatika dan Rekayasa Elektronik Jurnal Sistem informasi dan informatika (SIMIKA) Zonasi: Jurnal Sistem Informasi Jurnal Tekinkom (Teknik Informasi dan Komputer) JISA (Jurnal Informatika dan Sains) Jurnal Computer Science and Information Technology (CoSciTech) Mitra Mahajana: Jurnal Pengabdian Masyarakat Jurnal J-PEMAS Jurnal Algoritma JAIA - Journal of Artificial Intelligence and Applications SATIN - Sains dan Teknologi Informasi The Indonesian Journal of Computer Science
Triyani Arita Fitri
STMIK Amik Riau
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Public Health Social Sciences Other

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Optimasi Algoritma Knn Menggunakan Smote Untuk Prediksi Stroke Khairi, Zuriatul; Yanti, Rini; Fitri, Triyani Arita; Fatdha, Eiva
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2474

Abstract

Stroke is a disease with a high mortality and disability rate, especially in Indonesia. Early detection of stroke risk is important to prevent serious consequences. This study examines the distribution of stroke cases based on age groups and evaluates the performance of the K-Nearest Neighbors (KNN) algorithm on imbalanced data and after applying the Synthetic Minority Oversampling Technique (SMOTE). The analysis uses two data division scenarios: 80:20 and 70:30 between training and test data. The results show that the risk of stroke increases with age. No cases were found in the 20–30 age group, cases began to appear in the 30–40 age group, and increased sharply above the age of 50. KNN without SMOTE had an accuracy of 95% (80:20) and 94% (70:30), but low recall, 0.04 and f1-score 0.07 (80:20), and recall 0.03 and f1-score 0.05 (70:30). After SMOTE, recall increased to 0.36 and f1-score 0.21 (80:20), and recall 0.28 and f1-score 0.17 (70:30). Accuracy decreased to 86% in both ratios, but recall and f1-score increased, indicating that the model was more sensitive to stroke cases. Overall, SMOTE effectively reduces majority class bias and helps the model recognize overlooked stroke patterns. However, sensitivity still needs to be improved through parameter tuning, selection of relevant features, or alternative algorithms to enhance prediction reliability.
Recommendations For Repairing Uninhabitable Homes Using the Multi-Attribute Utility Theory (MAUT) Method Cesmawati, Cesmawati; Rahmiati, Rahmiati; Fitri, Triyani Arita
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 5 No. 1 (2022): Jurnal Teknologi dan Open Source, June 2022
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v5i1.2224

Abstract

Rumah yang layak huni, bersih dan memiliki infrastruktur yang bagus merupakan harapan setiap manusia. Sebaliknya, rumah yang tidak layak huni bisa menyebabkan ketidaknyamanan bagi penghuni rumah, dan juga dapat menjadi sumber penyakit yang sebaiknya dihindari oleh penghuni rumah. Permasalahan yang dihadapi oleh pihak Dinas PUPR Provinsi Riau masih menggunakan cara manual terutama dalam menentukan rekomendasi calon penerima rumah tidak layak huni. Metode MAUT diselesaikan dengan prinsip memberikan nilai utilitas untuk setiap kriteria dengan rentang nilai 0 hingga 1 yang menunjukkan pilihan terburuk untuk nilai 0 (nol) dan pilihan terbaik untuk nilai 1 (satu), dengan perbandingan bobot nilai masingmasing kriteria menghasilkan perbandingan yang relevan antar kriteria. Hasil perangkingan berdasarkan data yang diproses dengan lima alternatif maka memperoleh hasil 18,0 atas nama kepala keluarga Siswanto dengan status layak mendapatkan bantuan perbaikan rumah dari Pemerintah Provinsi Riau.
Co-Authors Agus Tri Nurhuda Agustin Agustin Agustin Agustin Agusviyanda Agusviyanda Ahmad Zamsuri, Ahmad Aldi Saputra Anam, M Khairul Boby Hasbul Fikri Bunga Nanti Pikir Cesmawati Cesmawati Cesmawati, Cesmawati Edwar Ali Efrizoni, Lusiana Ega Ranaldi Pebriansyah Erleni - Erleni -, Erleni Erlin Erlin - Erlin -, Erlin Fatdha, Eiva Fika Felanda Ardelia Firdaus, Muhammad Bambang Fransiskus Zoromi Fransiskus Zoromi, Fransiskus Hadi Asnal, Hadi Hamdani Hamdani - Hamdani Hamdani Hanafiah, Anggi Hanafiah, Anggi Handoko Hazira, Nadila Herwin Herwin, Herwin Ismanizan, Ryan Johan Junadhi Junadhi Karpen Kharisma Rahayu Koko Harianto Koko Harianto Kudadiri, Parlindungan Lusiana Lusiana Efrizoni M Naofal Arsyad M. Mashudi Muhammad Bambang Firdaus Nu'man Nu'man Nurhadi Nurjayadi Nurjayadi Perty Putriani Saragih Praba Isna Tasya Rahmaddeni Rahmaddeni Rahmawati Rahmiati Rahmiati Rahmiati Rahmiati Rinaldi Yuslami Rini Yanti Rini Yanti, Rini Rio Ferdiansyah Rita Novita Safitri, Dea Susandri, Susandri SUSANTI Susanti Susanti Susanti, Susanti SUSI ERLINDA Syam, Salmaini Safitri Teguh Sujana Torkis Nasution Widi Paramita Wirta Agustin Yuslami, Rinaldi Yusuf Nuron Zuriatul Khairi