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Integration of Knowledge-Based CNN Model for Breast Cancer Histopathology Image Classification Badri, Fawaidul; Patmanthara, Syaad; Zaeni, Ilham Ari Elbaith
ILKOMNIKA Vol 7 No 3 (2025): Volume 7, Number 3, December 2025
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/ilkomnika.v7i3.801

Abstract

This study examines the integration of a knowledge-based Convolutional Neural Network (CNN) model for breast cancer histopathology image classification through ontological and epistemological perspectives. Ontologically, the research focuses on the digital representation of histopathological breast tissue images as entities representing benign and malignant conditions, establishing a stable and comprehensive mapping of tissue morphological characteristics. Epistemologically, the study employs a deep learning approach using a CNN model to acquire and validate knowledge about cancer cell morphology patterns from image data, constructing robust epistemic claims regarding tissue differentiation. The BreakHis dataset comprises 7,909 images resized to 224×224 pixels that underwent preprocessing normalization and image augmentation to enhance data quality. The CNN model was designed with Adam and SAM optimizers, learning rates of 0.0001 and 0.003, and a three-epoch warm-up phase to maintain training stability. Experimental results achieved training accuracy of 0.8432, testing accuracy of 0.8481, AUC of 0.8318, precision of 0.8124, and recall of 0.8966, demonstrating excellent model performance in recognizing cancer tissue patterns without overfitting. The integration of this knowledge-based CNN model contributes theoretically to the advancement of artificial intelligence and biomedical science, while demonstrating practical relevance as a reliable decision-support system for breast cancer diagnosis.
Optimalisasi Energi Pada Lift Berdasarkan Gerak Vertikal pada Lift Menggunakan Hybrid Naive Bayes Prana Ihsanuddin, Adika; Sendari, Siti; Ari Elbaith Zaeni, Ilham; Afnan Habibi, M.; Arengga Wibowo, Danang
Jurnal JEETech Vol. 6 No. 2 (2025): Nomor 2 November
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32492/jeetech.v6i2.6203

Abstract

Penelitian ini bertujuan untuk mengoptimalkan penggunaan energi pada sistem lift berdasarkan gerak vertikal menggunakan algoritma Hybrid Naive Bayes. Proses optimalisasi didasarkan pada pengumpulan data dilakukan di Gedung B11 Fakultas Teknik Universitas Negeri Malang selama periode waktu tertentu, dalam upaya mengurangi konsumsi energi pada gedung bertingkat, efisiensi energi lift menjadi salah satu fokus utama. Dengan memanfaatkan data penggunaan lift yang meliputi pola pergerakan vertikal, waktu operasional, serta beban muatan, penelitian ini melakukan klasifikasi dan prediksi efisiensi energi. Algoritma Hybrid Naive Bayes dipilih karena kemampuannya dalam menangani ketidakpastian data serta keandalannya dalam klasifikasi, terutama saat dikombinasikan dengan metode optimisasi lainnya. Hasil prediksi efisiensi energi yang akurat juga memungkinkan manajemen gedung untuk menerapkan strategi operasional yang lebih hemat energi dan ramah lingkungan. Dengan demikian, penelitian ini diharapkan memberikan kontribusi signifikan dalam pengelolaan energi yang lebih efisien pada sistem lift di gedunggedung tinggi.
Co-Authors A.N. Afandi Adam Rachmawan Adib Nur Sasongko Aditama Yudha Atmanegara Adjie Rosyidin Afifah Salim Afnan Habibi, M. Afrian, Ronny Agung Bella Putra Utama Aji Prasetya Wibawa Aji Wibawa Akhmad Afrizal Rizqi Amalia Sufa Andrew Nafalski Andy Hermawan Anggraeni Budiarti Anik N. Handayani Anik Nur Handayani Arengga Wibowo, Danang Arifin, Samsul Aripriharta - Arya Kusuma Wardhana Arya Tandy Hermawan Atmaja, Nimas Hadi Dessy Rif’a Anzani Dian Candra Lestari Dony Setiawan Dwiyanto, Felix Andika Dyah Lestari Eko Pambagyo Setyobudi Elmusyah, Hakkun Erinda, Hayyu Fahreza Al Rafi, Muhammad Alif Fanani, Erianto Faozan Fauzi, Rochmad Fawaidul Badri Febi Elvara Aprilia Felix Andika Dwiyanto Felix Andika Dwiyanto Ferdiansyah, Dodik Septian Ferdinand, Miftakhul Anggita Bima Fitriana Kurniawati Gunawan Gunawan Gunawan Gwinny Tirza Rarastri Hakkun Elmunsyah Hanny Prasetya Hariyadi Hari Putranto Harits Ar Rosyid Hartono, Nickolas Hendrawan, William Hartanto Hidayah Kariima Fithri Hsien-I Lin I Made Wirawan Irvan, Mhd Ismail, Amelia Ritahani Ivatus Sunaifah Kartika Kirana Kevin Raihan Khafit Zaman Kotaro Hirasawa Liliek Rahayu M. Adib Nursasongko Maftuh Ahnan Mahisha Laila Moh. Iqbal Ardiansyah Mohamad Iqbal Mokh Sholihul Hadi Muhammad Arrazy Muhammad Firmansyah muhammad hafiizh, muhammad Muhammad Iqbal Akbar Muhammad Khusairi Osman Muhammad Rifai Muhammad Syauqi Muhammad Usman Mursyit, Mohammad Nafalski, Andrew Ningtyas, Yana Nurfadila, Piska Dwi Nusantar, Alrizal Akbar Nusantar Akbar Prana Ihsanuddin, Adika Puji Santoso Pundhi Yuliawati Rasidy, Ahmad Himawari Retno Indah Rokhmawati Ridwan Shalahuddin Rina Dewi Indahsari Riris Andriani Rizal Kholif Nurrohman Ronny Afrian Samsul Arifin Setumin, Samsul Setyorini Setyorini Shandy Darmawan Simbolon, Triyanti Siti Sendari Sugiono, Bhima Satria Rizki Sujito Sujito Suyono Suyono Syaad Patmanthara Syafaat, Mokhammad Tri Atmadji Sutikno Utama, Agung Bella Putra Wibisono, M. Nurwiseso Yandhika Surya Akbar Gumilang Yogi Dwi Mahandi Yosi Kristian Zafifatuz Zuhriyah