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All Journal Infotek : Jurnal Informatika dan Teknologi Journal of Computers and Digital Business
Muhammad Fahad
Universitas Esa Unggul
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering

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Rancangan Sistem Prediksi Penyakit Jantung Berbasis Framingham Risk Score: Konsistensi Teoritis dan Implementasi Web Hania Ayu Karin; Timothy Christian; Gabriel Putra; Muhammad Fahad; Muhammad Dhaffa Nugroho; Ilham Yusuf Maulana; Bambang Irawan
Journal of Computers and Digital Business Vol. 4 No. 3 (2025)
Publisher : PT. Delitekno Media Madiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56427/jcbd.v4i3.775

Abstract

Penyakit jantung merupakan penyebab kematian tertinggi di dunia. Deteksi dini risiko penyakit jantung dapat dilakukan menggunakan algoritma Framingham Risk Score (FRS). Penelitian ini merancang sistem prediksi risiko penyakit jantung berbasis web dengan mengadaptasi algortima Framingham Risk Score (FRS) yang dimodifikasi untuk lingkungan digital. Sistem dirancang menggunakan HTML, CSS, dan JavaScript sengan antarmuka form input gejala subjektif (nyeri dada, sesak napas, diabetes, dll) dan faktor demografis (usia, gender, riwayat keluarga). Parameter skoring dimodifikasi dari pedoman American Heart Association dan European Society of Cardiology dengan penyesuaian bobot gejala klinis seperti nyeri dada “berat” (+4 poin) dan diabetes (+3 poin). Hasil simulasi teoritis terhadap 5 skenario kasus menunjukkan konsistensi 95-97% dengan perhitungan manual FRS menggunakan kalkulator standar MDCalc. Sistem mengklasifikasikan output menjadi tiga kategori risiko: rendah(<10%), sedang(10-20%), dan tinggi(>20%), disertai rekomendasi tindak lanjut. Keunggulan rancangan ini terletak pada kemudahan akses sebagai alat skrining mandiri, namun memiliki keterbatasan utama yakni tidak mencakup parameter laboratorium (kolesterol, LDL) dan belum diuji dengan data pasien nyata. Simpulan Studi menekankan bahwa sistem ini bersifat prepanduan (pre-screening) dan setiap hasil prediksi harus dikonfirmasi melalui pemeriksaan media lengkap.
Sistem Rekomendasi Beasiswa Prestasi Akademik Berdasarkan Nilai Rata-Rata Dan Indeks Prestasi Kumulatif Menggunakan Logika Fuzz Yoana Nabilah Putri; Adelia Rafa Farzana; Muhammad Fahad; Hania Ayu Karin; Vitri Tundjungsari
Infotek: Jurnal Informatika dan Teknologi Vol. 9 No. 1 (2026): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v9i1.33733

Abstract

Scholarships play a crucial role in enhancing student motivation and academic achievement. However, the selection process often faces challenges in objectively determining eligibility. This study aims to develop an Artificial Intelligence-based scholarship recommendation system using a fuzzy logic approach to address uncertainty and variation in academic grades. The main contribution of this research is improving the objectivity and adaptability of the scholarship selection system through a fuzzy logic approach capable of assessing eligibility in a gradual and proportional manner. Data were collected from various publicly published scholarship agencies, including GPA, grade point average, and other academic requirements. The method used involves fuzzification to convert numerical data into fuzzy sets, applying fuzzy rules in the inference process, and defuzzification to generate consistently interpretable recommendation scores. The system was built using Python on the Google Colab platform and evaluated through white-box testing to ensure all internal logic flows work as designed. The results show that the fuzzy approach can provide more adaptive and objective recommendations compared to fixed threshold-based selection methods. The practical benefit of this system is to provide scholarship institutions with a transparent, efficient decision support tool that reduces subjectivity in the selection process.
Co-Authors Adelia Rafa Farzana Gabriel Putra Hania Ayu Karin Ilham Yusuf Maulana Irawan, Bambang Muhammad Dhaffa Nugroho Timothy Christian Vitri Tundjungsari Yoana Nabilah Putri