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All Journal Infotech Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jiko (Jurnal Informatika dan komputer) Jurnal Teknologi Progresif: Jurnal Ilmiah Komputer International Journal of Economics, Business and Accounting Research (IJEBAR) bit-Tech JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) JUKI : Jurnal Komputer dan Informatika Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat Infotek : Jurnal Informatika dan Teknologi Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Jurnal Teknik Informatika Duta.com : Jurnal Ilmiah Teknologi Informasi dan Komunikasi Prosiding Seminar Nasional Hasil-hasil Penelitian dan Pengabdian Pada Masyarakat Proceeding of International Conference Health, Science And Technology (ICOHETECH) Politeknosain Adopsi Teknologi dan Sistem Informasi Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Innovative: Journal Of Social Science Research Equivalent : Journal of Economic, Accounting and Management
Afu Ichsan Pradana
Universitas Duta Bangsa Surakarta
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Other

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Sistem Rekomendasi Kuliner Karanganyar Menggunakan Metode Hybrid Recommendation Radya Prameswari Putri; Joni Maulindar; Afu Ichsan Pradana
Progresif: Jurnal Ilmiah Komputer Vol 21, No 2 (2025): Agustus
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v21i2.3105

Abstract

Karanganyar has many culinary tourist destinations, but the number of diverse choices often makes it difficult for users to choose where to eat according to their preferences. Therefore, this research aims to help users find culinary places based on special menus. The recommendation system will be developed using a hybrid approach by combining content-based filtering and collaborative filtering. The content-based method matches the special menu with user input using cosine similarity, while collaborative filtering calculates the score from the normalized rating and the number of reviews using the weighted sum. A weight of 0.6 is given for content-based and 0.4 for collaborative because direct preference for menus is considered more dominant. The test was carried out using 5 different menus using precision and recall, with the test results for 100% recall, and the precision got a score of 75.42% because there are still recommendations displayed in the system that only have similar characteristics but are not really relevant to the user's preferencesKeywords: Collaborative filtering; Content-based filtering; Hybrid recommendation; Culinary recommendation; Recommendation system. AbstrakKaranganyar memiliki banyak destinasi wisata kuliner, namun jumlah pilihan yang beragam sering menyulitkan pengguna dalam menentukan tempat makan sesuai preferensi. Oleh karena itu, penelitian ini bertujuan untuk membantu pengguna menemukan tempat kuliner berdasarkan menu spesial. Sistem rekomendasi yang akan dikembangkan menggunakan pendekatan hybrid dengan menggabungkan content-based filtering dan collaborative filtering. Metode content-based mencocokkan menu spesial dengan input pengguna menggunakan cosine similarity, sedangkan collaborative filtering menghitung skor dari rating yang dinormalisasi dan jumlah ulasan dengan menggunakan weighted sum. Bobot 0,6 diberikan untuk content-based dan 0,4 untuk collaborative karena preferensi langsung terhadap menu dinilai lebih dominan. Pengujian dilakukan dengan menggunakan 5 menu yang berbeda menggunakan precision dan recall, dengan mendapatkan hasil pengujian untuk recall 100%, dan precision mendapatkan nilai 75,42% karena masih ada rekomendasi yang ditampilkan disistem yang hanya mirip karakteristiknya tetapi tidak benar-benar relevan dengan preferensi penggunaKata Kunci: Collaborative filtering; Content-based filtering; Hybrid recommendation; Rekomendasi kuliner; Sistem rekomendasi 
Implementation of Web-Based Room Management System for Boarding House Operations Renata Gilang Saputra; Rudi Susanto; Afu Ichsan Pradana
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2738

Abstract

The rapid advancement of digital technologies has significantly impacted various sectors, including property management. However, boarding house management still relies heavily on manual processes, resulting in inefficiencies such as inaccurate tenant data, delayed payments, and difficulties in monitoring room occupancy. This study aims to design and develop a web-based room management information system for Pak Yadi Boarding House, aimed at automating and streamlining key administrative tasks. Using the Waterfall development model, the study follows five phases: requirements analysis, system design, implementation, testing, and maintenance. Data collection was performed through literature review, observation, and interviews with the boarding house owner. The system was implemented using the Laravel framework and MySQL, with system architecture designed using UML diagrams. Testing was conducted using the Black Box method, with user acceptance testing involving one administrator and ten tenants. Key features tested include room data entry, tenant registration, payment invoicing, and complaint management. Results showed that all features performed as intended, and 90% of users expressed satisfaction with the system’s functionality and interface. The system successfully reduced administrative workload, minimized data entry errors, and enhanced operational efficiency. This research demonstrates that web-based systems can improve boarding house management and offers a scalable model for similar small-scale accommodations. Future research could explore integrating mobile access and cloud storage to enhance flexibility and remote management capabilities.
SEGMENTATION OF SUBARACHNOID HEMORRHAGE ON BRAIN CT IMAGES USING U-NET AND ATTENTION U-NET: A COMPARATIVE ANALYSIS Ilham Tristadika Saputra; Afu Ichsan Pradana; Dwi Hartanti
JIKO (Jurnal Informatika dan Komputer) Vol 8 No 2 (2025)
Publisher : Program Studi Teknik Informatika Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v8i2.9958

Abstract

Subarachnoid Hemorrhage (SAH) represents a critical medical condition resulting from bleeding in the subarachnoid space, typically due to the rupture of an aneurysm or trauma. Timely identification is vital to avoid long-term neurological impairment. This research assesses the efficacy of U-Net compared to Attention U-Net for the segmentation of SAH in brain CT images, aiming to determine if attention mechanisms enhance segmentation precision. The motivation for this comparison stems from the clinical difficulty in identifying subtle or low-contrast hemorrhagic areas that traditional architectures like U-Net might miss; in contrast, attention-based models are constructed to capture spatial details more proficiently. Both architectures were evaluated using a publicly available SAH CT dataset and assessed on metrics including Dice Score, Intersection over Union (IoU), Precision, Recall, and F1 Score. Attention U-Net outperformed U-Net with higher scores of Dice (0.896) and IoU (0.877), whereas U-Net excelled in precision. Visual assessments also indicated that Attention U-Net was superior in delineating diffuse hemorrhagic regions. These findings advocate for the incorporation of attention mechanisms to enhance segmentation accuracy and clinical relevance in neuroimaging
Penerapan Algoritma Decision Tree Untuk Prediksi Tingkat Risiko Jentik Nyamuk Berdasarkan Data Pemeriksaan Posyandu Aines Nafis Husna; Nurmalitasari Nurmalitasari; Afu Ichsan Pradana
JUKI : Jurnal Komputer dan Informatika Vol. 8 No. 1 (2026): JUKI : Jurnal Komputer dan Informatika, Edisi Mei 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53842/juki.v8i1.2449

Abstract

Pemantauan jentik nyamuk merupakan kegiatan yang dilakukan untuk mengetahui kondisi lingkungan dan mencegah peningkatan populasi nyamuk yang berpotensi menimbulkan penyakit. Penentuan tingkat risiko wilayah berdasarkan hasil pemeriksaan jentik masih dilakukan secara manual sehingga berpotensi menimbulkan perbedaan penilaian. Penelitian ini bertujuan untuk membangun model klasifikasi tingkat risiko jentik nyamuk menggunakan algoritma Decision Tree berdasarkan data historis pemeriksaan jentik nyamuk. Data yang digunakan merupakan hasil rekapitulasi pemeriksaan jentik nyamuk di Desa Langenharjo, Kecamatan Grogol, periode 2023-2025 sebanyak 65 data. Variabel yang digunakan meliputi jumlah rumah diperiksa, jumlah rumah terdapat jentik, jumlah kontainer diperiksa, dan jumlah kontainer terdapat jentik. Tahapan penelitian meliputi pengumpulan data, preprocessing, pelabelan tingkat risiko, pembentukan model Decision Tree, serta pengujian menggunakan pembagian data sebesar 80% sebagai data latih dan 20% sebagai data uji. Hasil penelitian menunjukkan bahwa model mampu mengklasifikasikan tingkat risiko jentik nyamuk ke dalam kategori rendah, sedang, dan tinggi dengan tingkat akurasi sebesar 92%. Hasil klasifikasi tersebut kemudian diimplementasikan pada aplikasi berbasis web untuk membantu proses input data dan penyajian informasi. Berdasarkan hasil tersebut, algoritma Decision Tree dapat digunakan sebagai alat bantu dalam menentukan tingkat risiko jentik nyamuk secara lebih objektif serta mendukung pengambilan keputusan dalam kegiatan pemantauan lingkungan.
Co-Authors Aines Nafis Husna Andriani Kusumaningrum Areta Reza Pradana Arif Eko Fitrianto Arif Wicaksono Septyanto Bachtiar Estu Saputro Bambang Soedijono WA Dessy Ambarsari Divangga Revansa Arya Pradhana Dwi Hartanti Eko Pranoto Saputro Ema Utami Farrois Qithfirul Aziz Frisca Tri Arumsari Hafid Affan Wahid Harsanto Harsanto harsanto harsanto Hartanti, Dwi Hasanah, Herliyani Ilham Tristadika Saputra Indah Nofikasari Joko Endriyanto Kumaratih Sandradewi Lestari, Retna Dewi M. Syafri Lamato Malika Harsanto Maulindar, Joni Moh Muhtarom Muhamad Alwi Kurniawan Muhammad Ridho Assyifa Muhammad Yasir Bintang Nugraha Nanang Setiawan Nurchim Nurchim Nurmalitasari Nurmalitasari Pahlevi, Khumaira Anin Aliya Permatasari, Hanifah Purwanto, Eko Raditya Koesyan Dipo Pramukti Radya Prameswari Putri Renata Gilang Saputra Reza Mar Hendra Putra Rifqi Mizan Aulawi Rina Arum Prastyanti Rudi Susanto Saputra, Abetranda Saputra Defa Sigit Prabawa Sri Lestari Sri Sumarlinda Subastian Wibowo Sudarmawan Sudarmawan Supardi Toto Indriyatmoko Wiji Lestari Wijiyanto