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All Journal Jurnal Simetris Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) Jurnal Sains dan Informatika JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI ILKOM Jurnal Ilmiah JATI (Jurnal Mahasiswa Teknik Informatika) JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) JAMI: Jurnal Ahli Muda Indonesia JTECS : Jurnal Sistem Telekomunikasi Elektronika Sistem Kontrol Power Sistem dan Komputer Kontribusi: Jurnal Penelitian dan Pengabdian Kepada Masyarakat Nusantara of Engineering (NOE) Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Insand Comtech : Information Science and Computer Technology Journal JSITIK: Jurnal Sistem Informasi dan Teknologi Informasi Komputer Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Jurnal Informatika: Jurnal Pengembangan IT Jurnal Pengabdian Masyarakat Nusantara
Aidina Ristyawan, Aidina
STMIK AMIKOM Yogyakarta
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Social Sciences Transportation

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Penerapan Algoritma Apriori untuk Mengidentifikasi Pola Peminjaman Buku Pada Perpustakaan Mas Trip Kabupaten Kediri Galuh, Asye Candra Andy; Firliana, Rina; Ristyawan, Aidina
JSITIK: Jurnal Sistem Informasi dan Teknologi Informasi Komputer Vol. 4 No. 1 (2025): Desember 2025
Publisher : Cipta Media Harmoni

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53624/jsitik.v4i1.723

Abstract

Latar Belakang: Perpustakaan berfungsi penting dalam meningkatkan kualitas intelektual masyarakat, namun banyak yang menghadapi tantangan dalam pengelolaan data, mengurangi kepuasan pengguna. Tujuan: Tujuan penelitian ini untuk mengidentifikasi pola peminjaman buku di Perpustakaan Mas Trip Kabupaten Kediri menggunakan algoritma Apriori. Metode: Metode penelitian menggunakan metode kuantitatif, data yang digunakan berasal dari gabungan tiga dataset publik (Books, Ratings, dan Users), yang kemudian diproses melalui teknik preprocessing dan dianalisis dengan algoritma association rule mining. Hasil: Hasil analisis menunjukkan bahwa kombinasi kedua algoritma ini dapat memberikan rekomendasi buku yang lebih personal dan akurat. Model yang dibangun kemudian diekspor ke dalam file untuk digunakan dalam aplikasi web berbasis Streamlit. Aplikasi tersebut memungkinkan pengguna mendapatkan rekomendasi buku berdasarkan histori peminjaman dan rating. Kesimpulan: Penelitian ini membuktikan bahwa integrasi algoritma data mining dapat meningkatkan efisiensi pengelolaan koleksi dan kualitas layanan perpustakaan.
Analysis of Preprocessing Technique Combinations and Hyperparameter Tuning for Building a Reliable Random Forest–Based Stroke Prediction Model Ristyawan, Aidina; Nugroho, Arie
International Journal of Engineering and Computer Science Applications (IJECSA) Vol. 5 No. 1 (2026): March 2026
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v5i1.6080

Abstract

Stroke is a major health threat that can result in permanent disability or death, yet its risks can be mitigated through accurate early detection. Although the Random Forest algorithm is frequently utilized for stroke prediction, prior studies have often neglected model reliability, specifically the stability of performance between training and testing phases. This research aims to develop a dependable stroke prediction model by implementing the CRISP-DM methodology on a public dataset comprising 5,110 data points. The proposed methodology involves a comprehensive evaluation of 48 preprocessing technique combinations—addressing missing values in the BMI attribute, categorical transformation, feature scaling, and class balancing—followed by a two-stage hyperparameter optimization strategy: Randomized Search for broad exploration and Grid Search Refine for local refinement to ensure optimal stability. Model performance was evaluated using accuracy, precision, recall, and F1-score metrics. The results demonstrate that hyperparameter tuning successfully enhanced model performance by up to 38.80%. Additionally, it was found that the hybrid balancing technique (SMOTETomek) did not consistently yield the most stable models in this specific case. The optimal model (Model No. 8) achieved a training accuracy of 0.925 and a testing accuracy of 0.877. With a minimal performance gap of 0.047 (below the 0.05 threshold), this model is classified as "good fitting," signifying superior generalization capabilities. Consequently, this model is highly recommended for implementation as a robust and trustworthy early warning decision support system for medical professionals.
Classification of Dog and Cat Images using the CNN Method Adriyanto, Teguh; ramadhani, risky aswi; Helilintar, Risa; Ristyawan, Aidina
ILKOM Jurnal Ilmiah Vol 14, No 3 (2022)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v14i3.1116.203-208

Abstract

Blind people can be defined as those people who are unable to see objects or pictures around them with their eyes. This inability becomes an issue for them when dealing with objects or images in front of them. These problems lead to the novelty of this study that is to recognize objects or images around blind people with the CNN algorithm. Dogs and cats were used as objects in this study. These object recognitions used Deep Learning, a relatively new science in the field of machine learning. Deep learning works like the human brain's ability to recognize an object. In this study, the objects that were used were pictures of a dog and a cat. This study used 3 types of data, namely training, validation, and testing data. The data training consisted of dog data with a total of 1000 images and cat data with a total of 1000 images. Data validation consisted of 500 dog data  and 500 cat data. The CCN architecture employed 3 convolution layers. The layer was convolution 1 using 16 filters of kernel size 3x3, the second convolution using 32 filters of  kernel size 3x3 and the third using 64 filters of kernel size 3x3. While the data testing consisted of 51dog data and 27 cat data. The method used to analyze the image was CNN. The input was an image with a size of 150x150 pixels with 3 channels, namely R, G, and B. This classification went through a performance test with the Confusion Matrix and it obtained 45% precision, 45% recall and 45% f1-score. From these results it can be concluded that the accuracy values should be improved.
Co-Authors Abadi, Ahmad Fajar Achmad, Ridho Adriyanto, Teguh Afdholul Faathin, Achmad Afrizal Ahmad Bayu P Aini, Ersa Dwi Nur Alamsyah, M Alfianto Alja, Farhan Maulana Amarya, Theo Krisna Andi Sunyoto Andy G, Asye Candra Ardyansyah, Fikri Arfiansyah, Zen Arie Nugroho, Arie Arighy, Erza Farrel Aulia, Ewanda Herdika Septa Azzahra, Salsabila Dini Azzahro, Zia Ulhaq Bahtiyar, Arul Damayanti, Sofiana Yuli Diniati, Erna Dwi Harini Dzatama, Krisna Fahrizal Eka Fauziah Erna Daniati Ervin Kusuma Dewi, Ervin Kusuma Fadhila, Amelia Nur Farhan Gagat Retnanto Faruq, Umar Al Faruqziddan, Muhammad Fatayasya, Ikhfal Fauzi, Mohammad Ainun Naja Felmidi, Ferdian Ahmat Firmansyah, Achmad Ali Fitriono, Deri Galuh, Asye Candra Andy Hariyanto, Feri Tri Ilahi, Ferlita Putri Anugerah Indrawan, Dea Rizky Irawati, Elsa Irfa’udin, Muhammad Islami, Bifadhlillah Marsheila Jatmiko Jatmiko Jauhar, Moh. Iqbal Iqza Kamilatutsaniya, Nila Khasanah, Reka Ainul Krisnaryoko, Ersa Kurniawan, Mohammad Nova Kusrini Muhammad Najibulloh Muzaki Mustofa, Mohammad Annan Makruf Muzaki, M. Majibulloh Muzaki, Muhammad Reza Nalsa Cintya Resti Nanda, Thoyib Fernanda Ningrum, Dea Yuliana Ayu Nur Alamsyah, Nur Nurfajriana, Intan Melinda Pradhana, Akmal Hisyam Pradikdo, Angga Cahyo Prayogi, Anindita Puspa Ayu Priyanto, Evania Putra, Regi Candra Purnama Putri, Fitria Dessela Putri, Ravega Widyawati Putriani, Dewi Rina Firliana Rini Indriati Risa Helilintar Risky Aswi R, Risky Sahira, Maha Shelin Santoso, Heru Teguh Sari, Vivi Anggun Permata Sawabudin, Bahrul Shofyana, Altha Inas Sucipto Sucipto Syafa’at, Achmadhin Tristan Teguh Andriyanto, Teguh Tri Febriyanto, Moch Tri Puji Saputra, Alfian Utomo, Aris Danang Tri Varuq, M Nizar Bahri Al Wahiid, Hermawan Nur Wardani , Anita Sari Wardani, Saylendra Arga Wardhani, Aurel Fransisca Kusuma Wibisono, Ryan Marcell Widodo Widodo Wulandari, Putri Widya Ayu Septi Wulandari, Rindi Febri