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Suwaryo, Niko
Universitas Medika Suherman
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Apriori Algorithm Analysis of Mattress Material Usage Data for Enhanced Production Optimization Niko Suwaryo; Santoso Santoso; Masgo Masgo; Tugiman Tugiman; Sandy Gunarso Wijoyo; Nugraha Nugraha
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4362

Abstract

Production is a value-adding process that transforms raw materials into finished products to meet manufacturing requirements. Association rule analysis serves as a methodological approach to identify relationships between items, particularly in transactional datasets. This analytical method has proven effective in processing exchange data patterns. Analysis of production material usage patterns revealed that when items A and B are utilized, there exists a 50% probability of concurrent item C usage - a significant pattern emerging from transactional data analysis. The study generated association rules for each operational process. Empirical testing through RapidMiner Studio yielded consistent results, demonstrating linear relationships proportional to the modeled scenarios, thereby validating the model's applicability as a decision-making reference. The evaluation of generated association rules through RapidMiner Studio revealed a Lift Ratio value of 1. These results indicate that combinations meeting or exceeding a Lift Ratio threshold of 1 demonstrate statistical validity and practical utility.
Implementasi Sistem Pakar untuk Diagnosis Penyakit Lambung Menggunakan Pendekatan Fuzzy Mamdani Berbasis Website Ilham Roni Yansyah; Dewi Marini Umi Atmaja; Arif Rahman Hakim; Niko Suwaryo
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 2 (2025): APRIL-JUNE 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i2.3534

Abstract

This study aims to develop a more specific diagnostic approach for various gastric diseases in humans, such as gastritis, peptic ulcers, gastric cancer, gastric tumors or polyps, dyspepsia, gastroesophageal reflux disease (GERD), gastroparesis, and gastroenteritis. This approach seeks to enhance the accuracy of disease identification based on more detailed symptoms. An expert system utilizing the Fuzzy Mamdani method is designed to reduce reliance on internal medicine specialists, enabling patients to gain preliminary insights into the type of gastric disease they may have. This expert system is implemented on a web-based platform, leveraging information technology to integrate large-scale databases, supporting efficiency, accuracy, and relevance to the latest developments in medical science. By analyzing digestive disorder symptoms, the system can provide detailed diagnoses, offer insights into identified symptoms, and recommend appropriate treatment solutions.
Penerapan Contrast Limited Adaptive Histogram Equalization untuk Meningkatkan Kontras Citra Lidah pada Identifikasi Dianogsa Penyakit Jantung Menggunakan Convolutional Neural Network suwaryo, Niko; Muslihatin Khuril Rosyida; Sandi Salvan Nuraliyudin
Jurnal Perspektif Vol 10 No 1 (2026): Jurnal Perspektif
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/jp.v10i1.413

Abstract

Penyakit jantung dapat memengaruhi fungsi jantung dan pembuluh darah. Pencegahan melalui gaya hidup sehat dan deteksi dini merupakan kunci utama untuk menjaga kesehatan. Identifikasi diagnosis penyakit jantung juga diperlukan untuk mencegah terjadinya kematian. Informasi dan pengetahuan tentang identifikasi  awal suatu penyakit jantung, dan kesadaran publik tentang kesehatan, masih rendah. Tidak dapat memberikan informasi melalui media tentang penyakit jantung, dan kurangnya edukasi tentang masalah penyakit jantung dalam kasus ini, sehingga  media didukung dalam bentuk sistem yang mudah untuk memberikan solusi yang sesuai untuk mengelola masalah ini. Metode Contrast Limited Adaptive Histogram Equalization (CLAHE)  dan algoritma Convolutional Neural Network (CNN) dapat digunakan untuk meningkatkan kontras pada gambar lidah, klasifikasi gambar, atau mendeteksi objek gambar lidah yang diambil dari foto pasien penyakit jantung dan foto lidah normal tidak terkena penyakit jantung. Penggunaan CLAHE dalam preprocessing citra lidah terbukti berhasil dalam meningkatkan kualitas kontras. CNN dalam mengidentifikasi pola yang berkaitan dengan tanda penyakit jantung. Performa model dan algoritma diuji untuk mengetahui hasil akurasi yang dianalisis serta mengukur metode CLAHE, di mana algoritma CNN dapat digunakan untuk meningkatkan kontras pada gambar lidah dan berfungsi dengan baik, dan dapat menghasilkan tingkat akurasi 100.00%.
Co-Authors Amat Basri Amat Basri Arif Rahman Arif Rahman Hakim Arif Rahman Hakim Arif Rahman Hakim Atmaja, Dewi Marini Umi Dewi Marini Umi Atmaja Dewi Marini Umi Atmaja Dewi Marini Umi Atmaja Ilham Roni Yansyah Ilham Roni Yansyah Koniasari Kurniawan, Avip Masgo Masgo Muslihatin Khuril Rosyida Nawangsih, Ismasari Nugraha Nugraha Sandi Salvan Nuraliyudin Sandy Gunarso Wijoyo Santoso Santoso Sri Rejeki Tugiman Tugiman Tugiman Tugiman