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All Journal JFA (Jurnal Fisika dan Aplikasinya) Gravity : Jurnal Ilmiah Penelitian dan Pembelajaran Fisika Jurnal Fisika : Fisika Sains dan Aplikasinya Tsaqofah: Jurnal Penelitian Guru Indonesia YASIN: Jurnal Pendidikan dan Sosial Budaya MASALIQ: Jurnal Pendidikan dan Sains Al-DYAS : Jurnal Inovasi dan Pengabdian kepada Masyarakat Jurnal Informatika Medis (J-INFORMED) BULETIN FISIKA
Muktamar Cholifah Aisiyah
Universitas Mhammadiyah Lamongan
Religion Astronomy Computer Science & IT Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Health Professions Library & Information Science Materials Science & Nanotechnology Medicine & Pharmacology Nursing Physics Public Health Social Sciences Veterinary Other

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Optimizing the ROI (Region of Interest) Quality of Breast Cancer Skin Contour Images Using a Combination of Contrast Enhancement Methods Based on LiDAR Data Vanis Aisyah Ayu Sugiarti; Muktamar Cholifah Aisiyah; Aris Widodo; Asmaul Lutfi Marufah
BULETIN FISIKA Vol. 26 No. 2 (2025): BULETIN FISIKA
Publisher : Departement of Physics Faculty of Mathematics and Natural Sciences, and Institute of Research and Community Services Udayana University, Kampus Bukit Jimbaran Badung Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/BF.2025.v26.i02.p05

Abstract

Breast cancer has the highest prevalence and mortality rates among cancers in Indonesia, largely due to delayed diagnosis. One of the major challenges is the poor quality of medical images used for early detection. This study aims to improve the quality of images in the important area of the skin around breast cancer patients using Light Detection and Ranging (LiDAR) data by combining methods to enhance contrast and reduce noise. A total of 80 image data (40 cancer anomalies and 40 normal without cancer) and utilized MATLAB software version 24.1.0.2537033 (R2024a) for image processing, starting from increasing CNR and increasing SNR to semi-automatic ROI masking. The results showed that there was a significant increase in CNR values (an average of 38%) and SNR (an average of 42%). These results are supported by a paired T-test, which shows a significant difference between pre- and post-processed images, both in CNR α < 0.0001 and SNR α < 0.0001 parameters. These findings support the claim that image quality improvement is not only visually evident but also statistically evident. This study proves that the method used is effective in improving image quality and shows that LiDAR data has great potential in medical imaging systems.
Rancang Bangun Sistem Deteksi Dini Kanker Payudara Berdasarkan Indikator Warna Pada Kulit Berbasis ESP32-Cam Terintegrasi Edge Impulse Hana Dwi Cahyani; Muhamad Azwar Annas; Uswatun Chasanah; Muktamar Cholifah Aisiyah
BULETIN FISIKA Vol. 26 No. 2 (2025): BULETIN FISIKA
Publisher : Departement of Physics Faculty of Mathematics and Natural Sciences, and Institute of Research and Community Services Udayana University, Kampus Bukit Jimbaran Badung Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/BF.2025.v26.i02.p10

Abstract

Deteksi dini kanker payudara merupakan langkah penting untuk meningkatkan peluang kesembuhan dan menekan angka kematian. Penelitian ini merancang sistem deteksi dini berbasis citra digital dengan memanfaatkan indikator visual berupa warna kemerahan pada kulit. Sistem dikembangkan menggunakan ESP32-Cam yang terintegrasi dengan Edge Impulse untuk pelatihan dan inferensi model klasifikasi berbasis Artificial Intelligence (AI). Deteksi dilakukan melalui pengolahan citra warna dan metode machine learning (ML) yang bekerja berdasarkan prinsip fisika optik dan sensorika, khususnya interaksi cahaya dengan permukaan kulit, serta merupakan bentuk penerapan prinsip-prinsip fisika dalam pengembangan teknologi deteksi visual modern. Dataset dikumpulkan dari phantom payudara dengan variasi tingkat kemerahan, dua jenis warna kulit (kuning langsat dan sawo matang), serta pencahayaan berbeda (600 lux, 800 lux, dan 1000 lux). Gambar diambil dari jarak 20 cm dengan sudut 90° dan 45° menggunakan kamera handphone. Model dilatih menggunakan metode CNN dan diintegrasikan ke ESP32-Cam, namun proses inferensi masih memerlukan koneksi internet untuk dapat dijalankan. Hasil menunjukkan bahwa pencahayaan 800 lux memberikan visual optimal, dan berhasil menjalankan klasifikasi dengan akurasi rata-rata sebesar 90,9%. Evaluasi menggunakan confusion matrix menunjukkan bahwa sistem ini baik dan akurat. Kata kunci: Deteksi dini; edge impulse; ESP32-cam; fisika optik; kanker payudara.
Co-Authors Aris Widodo Aris Widodo Asmaul Lutfi Marufah AZWAR ANNAS, MUHAMAD Bait, Jennifer Farihatul Cahyani, Hana Dwi Hana Dwi Cahyani Heri Rismawan Makrufah, Dini Musfiana, Masria Ningrum, Izza Eka Uswatun Chasanah Uswatun Chasanah Vanis Aisyah Ayu Sugiarti