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All Journal e-Dinamis ELT Worldwide: Journal of English Language Teaching Jurnal Adabiyah KAREBA : Jurnal Ilmu Komunikasi International Journal of Artificial Intelligence Research Jurnal Penelitian Sains Knowledge Engineering and Data Science JURNAL MEDIA INFORMATIKA BUDIDARMA BERDIKARI : Jurnal Inovasi dan Penerapan Ipteks UICELL Conference Proceeding Jurnal Pemberdayaan: Publikasi Hasil Pengabdian Kepada Masyarakat IJISH (International Journal of Islamic Studies and Humanities) LISANAN ARABIYA: Jurnal Pendidikan Bahasa Arab Mobile and Forensics Signal and Image Processing Letters Jurnal Ilmiah Permas: Jurnal Ilmiah STIKES Kendal English Teaching and Linguistics Journal (ETLiJ) Al-Fathin: Jurnal Bahasa dan Sastra Arab Letters in Information Technology Education (LITE) Jurnal Kesehatan Tambusai Jurnal Jarlit JTechLP JoEELE El 'Aailah Journal Medical Informatics Technology Bulletin of Social Informatics Theory and Application International Journal of Business English and Communication (IJoBEC) Jurnal Literasi dan Pembelajaran Indonesia Celebes Journal of Language Studies QOSIM: Jurnal Pendidikan, Sosial & Humaniora Journal of Sustainable Community Development GEMBIRA (Pengabdian Kepada Masyarakat) Jurnal Pengabdian Masyarakat Mentari Multidisciplinary Indonesian Center Journal Journal on Mathematics Education Signal and Image Processing Letters Axiology
Ahmad Azhari
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Religion Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Journal : knowledge engineering and data science

 1 
Human Intestinal Condition Identification Based-on Blended Spatial and Morphological Feature using Artificial Neural Network Classifier Athiyah, Ummi; Muhammad, Arif Wirawan; Azhari, Ahmad
Knowledge Engineering and Data Science
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Abstract

Colon cancer is a type of disease that attacks the intestinal walls cell of humans. Colorectal endoscopic screening technique is a common step carried out by the health expert/gynecologist to determine the condition of the human intestine. Manual interpretation requires quite a long time to reach a result. Along with the development of increasingly advanced digital computing techniques, then some of the weaknesses of the manually endoscopic image interpretation analysis model can be corrected by automating the detection process of the presence or absence of cancerous cells in the gut. Identification of human intestinal conditions using an artificial neural network method with the blended input feature produces a higher accuracy value compared to the artificial neural network with the non-blended input feature. The difference in classifier performance produced between the two is quite significant, that is equal to 0.065 (6.5%) for accuracy; 0.074 (7.4%) for recall; 0.05 (5.0%) for precision; and 0.063 (6.3%) for f-measure.
Neural Network Classification of Brainwave Alpha Signalsin Cognitive Activities Azhari, Ahmad; Susanto, Adhi; Pranolo, Andri; Mao, Yingchi
Knowledge Engineering and Data Science
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The signal produced by human brain waves is one unique feature. Signals carry information and are represented in electrical signals generated from the brain in a typical waveform. Human brain wave activity will always be active even when sleeping. Brain waves will produce different characteristics in different individuals. Physical and behavioral characteristics can be identified from patterns of brain wave activity. This study aims to distinguish signals from each individual based on the characteristics of alpha signals from brain waves produced. Brain wave signals are generated by giving several mental perception tasks measured using an Electroencephalogram (EEG). To get different features, EEG signals are extracted using first-order extraction and are classified using the Neural Network method. The results of this study are typical of the five first-order features used, namely average, standard deviation, skewness, kurtosis, and entropy. The results of pattern recognition training show that 171 successful iterations are carried out with a period of execution of 6 seconds. Performance tests are performed using the Mean Squared Error (MSE) function. The results of the performance tests that were successfully obtained in the pattern test are in the number 0.000994.
Parallelization of Partitioning Around Medoids (PAM) in K-Medoids Clustering on GPU Prahara, Adhi; Ismi, Dewi Pramudi; Azhari, Ahmad
Knowledge Engineering and Data Science
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Abstract

K-medoids clustering is categorized as partitional clustering. K-medoids offers better result when dealing with outliers and arbitrary distance metric also in the situation when the mean or median does not exist within data. However, k-medoids suffers a high computational complexity. Partitioning Around Medoids (PAM) has been developed to improve k-medoids clustering, consists of build and swap steps and uses the entire dataset to find the best potential medoids. Thus, PAM produces better medoids than other algorithms. This research proposes the parallelization of PAM in k-medoids clustering on GPU to reduce computational time at the swap step of PAM. The parallelization scheme utilizes shared memory, reduction algorithm, and optimization of the thread block configuration to maximize the occupancy. Based on the experiment result, the proposed parallelized PAM k-medoids is faster than CPU and Matlab implementation and efficient for large dataset.
Convolutional Neural Network on Tanned and Synthetic Leather Textures Faiz, Faadihilah Ahnaf; Azhari, Ahmad
Knowledge Engineering and Data Science
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Abstract

Tanned leather is an output from complex processes called tanning. Leather tanning is an important step that used to protect the fiber or protein structure of animal’s skin. Another reason of tanning process is to prevent the animal’s skin from any defect or rot. After the tanning is complete, the leather can be applied to produce a wide variety of leather products. Thus, the leather prices usually more expensive because it takes longer time in process. Another way to get cheaper price is make non-animal leather that usually known as synthetic or imitation leather. The purpose of this paper is to classify the tanned leather and synthetic leather by using Convolutional Neural Network (CNN). The tanned leather consist of cow, goat and sheep leathers. The proposed method will classify into four class, they are cow, goat, sheep and synthetic leathers. This research consist of 1280 training data with 448×448 pixels size as the input. With CNN method, this research shows a good result for the accuracy about 92.1%.
Cognitive EEG Differentiation with Hypnosis-Based Noise Reduction and K-Harmonic Means for Personalized Brainwave Modeling Azhari, Ahmad; Saputra, Dimas Chaerul Ekty
Knowledge Engineering and Data Science
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Abstract

This study investigates the integration of hypnosis-based noise reduction and K-Harmonic Means (KHM) clustering for personalized brainwave modeling using Electroencephalography (EEG) data. EEG signals were collected from 100 participants using a Neurosky Mindset sensor at the FP1 (prefrontal) location, with each subject performing nine standardized cognitive tasks such as breathing, memory recall, and mathematical problem-solving. Hypnosis was applied not as a filtering method but as a behavioral protocol to standardize subject conditions and minimize physiological and environmental noise. The EEG signals were sampled at 128 Hz and analyzed using KHM clustering with K=4K = 4K=4, resulting in a Silhouette Score of 0.9515, which demonstrates strong cluster separation and robustness against noise. Compared with baseline approaches such as K-Means and Fuzzy C-Means, KHM achieved higher stability and consistency in differentiating cognitive tasks. This performance highlights the advantage of harmonic averaging in mitigating the influence of outliers during clustering. The findings suggest that hypnosis can meaningfully enhance EEG signal quality, thereby improving downstream cognitive state differentiation. Overall, this research contributes to advancing EEG-based cognitive analysis and personalized brainwave modeling, with potential applications in brain–computer interfaces, cognitive diagnostics, and neurofeedback systems. The integration of behavioral noise control (hypnosis) with advanced clustering methods presents a novel hybrid framework for improving the reliability of EEG-based cognitive state identification.
Co-Authors Abbas, Moch Anwar Adhi Prahara, Adhi Adhi Susanto Adys, Himala Praptami Affan, Dhava Chairul Agus Aktawan, Agus Ahmad Barizi Ali, Raden Muhammad Ammattulloh, Fathia Irbati Ammatulloh, Fathia Irbati Ammatulloh, Fathia Irbati Andi Kamariah Andri Pranolo Arief, Husniah Arif Wirawan Muhammad Arwinsyah Arwinsyah, Arwinsyah Asfah, Indrawaty Ashabul Kahfi Susanto Asriati Ayu .H, Sendi Sandra Azhari, Cindy Azwar Abbas Bakri Muhammad Bakhiet Budiarti, Gita Indah Citra Prasiska Puspita Tohamba, Citra Prasiska Puspita Danial Hilmi Darmawansyah Alnur, Rony Darmiany Destiyanti, Intan Dewi Pramudi Ismi, Dewi Pramudi Dharma Ariawan, Ade Dimas Chaerul Ekty Saputra Djumhur, Adang Dwi Hastuti Dwi Normawati, Dwi Dwiza Riana Dzaki , Arif Rahman Edy Setyawan Eirene, Jessica Endo, Hiroyuki Endri Junaidi, Endri Enok Sureskiarti Fadlansyah, Holy Faiz, Faadihilah Ahnaf Faizah Faizah Fariza, Riska Fika Novatiana Furizal, Furizal Gesbi Rizqan Rahman Arief Hadi Saputra Hadi, Muhammad Saepul Hafizh, Muhammad Naufal Hajar, Andi Hardianti Hardianti, Hardianti Hewiz, Alya Shafira Himala Praptami Adys Husniati Husniati, Husniati Imam Riadi Insan Kamil Sinaga Ismail Ismail Jamilah Jamilah Jaya, Erlangga Jefree Fahana Kamal, Mustapa Kamal, Sofia Kamariah, Andi Kartoirono, Suprihatin Khosyi'ah, Siah Kusaka, Satoshi Kyswantoro, Yunita Firdha Lubis, Dhian Wahyudi Mahmuddin Adriansyah Mao, Yingchi Milkhatun, Milkhatun Muhammad Fahri Jaya Sudding Muhammad Kunta Biddinika Murein Miksa Mardhia Musdalifah Musdalifah Musdalifah Nabila, Ai Negara, Candra Putra nisa, Anisa Shahratul Jannah Nugroho, Prasetiyanto Nur Fatimah Nur Robiah Nofikusumawati Peni Nurfitrah Nuril Anwar, Nuril Octaviantara, Adi Pangistu, Lalu Arfi Maulana Purnaramadhan, Riza Putri, Zelza Alifvia Samudera RAMADAN, RIZKY Robin, Qori Aulia Rosyid A.A, Achmad Rully Charitas Indra Prahmana Safitri, Bunga Safitri, Citra Dwi Sahadi, Syah Reza Pahlevi Seny Luhriyani Sunusi Seny Luhriyani Sunusi Setiawan, Dimas Aji Son Ali Akbar Soviyah Sudding, Muhammad Fahri Jaya Sugianto Sugianto Suhail, Faiq Surya Anantatama Sembiring Suryanto, Imam Suryanto, Indra Swara, Ajie Kurnia Saputra Syaefullah, Syaefullah Syafatullah, Muhammad Rafli Syafrina Lamin, Syafrina Syahriyah, Shilfia Fadhilatul Syuhadak Syuhadak Tanikawa, Kanako Topani, Muhammad Alfikri Maida Tuti Purwaningsih, Tuti Ummi Athiyah Wardoyo, Girindra Sulistiyo Zaman, Azmi Badhi'uz Zaman, Azmi Badhi’uz