Perbandingan Aplikasi Algoritma Kernel K-Means pada Graf Bipartit dan K-Means pada Matriks Dokumen- Istilah dalam Dataset Penelitian Covid-19 RISTEKBRIN by Budi Nugroho

“…As comparison, we applied original k-means algorithm on the document-term matrix of the dataset. …”
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Remove Unimportant Features from True Colored Images Using the Segmentation Technique by Shahad Hasso

“…In this work a new approach was built to apply k-means algorithm on true colored images (24bit images) which are usually treated by researchers as three image (RGB) that are classified to 15 class maximum only. …”
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Improvement of Differential Privacy K-means Clustering Algorithm by GUO Rumin, CHEN Xuebin, SHAN Liyang

“…By calculating the minimum privacy budget required for each iteration based on the mean square error between centroids in the original K-means algorithm and the ones in the differential privacy K-means algorithm, a new privacy budget allocation scheme is established in combination with binary search. …”
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Analysis of Customer Power Consumption Behavior Based on DPSO-Kmeans under the Ubiquitous Power Internet of Things by WANG Ying, XIANG Wen, ZHANG Qun, GAO Xiuyun

“…The results prove that DPSO-Kmeans has a better clustering effect than the traditional K-means algorithm, and can extract more typical customers′ electrical behavior pattern.…”
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PREDICTION OF THE POOR RATE K-MEANS AND GENERALIZED REGRESSION NEURAL NETWORK ALGORITHMS (CASE STUDY: NORTH SUMATRA PROVINCE) by Nita Suryani, Arnita Arnita, Rinjani Cyra Nabila, Amanda Fitria

“…In this study, poverty levels were mapped using the K-Means algorithm, and GRNN was then utilized for modeling and prediction. …”
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Detect anomalous quartic gauge couplings at muon colliders with quantum kernel k-means by Shuai Zhang, Ke-Xin Chen, Ji-Chong Yang

“…It is well known that the kernel k-means algorithm can be carried out with the help of quantum computing, which suggests that quantum kernel k-means (QKKM) is also a potential tool for NP phenomenological studies in the future. …”
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CLUSTER AND CONJOINT ANALYSIS FOR DETERMINING ONLINE SHOP SHOPEE CUSTOMERS PREFERENCE BASED ON E-SERVICE QUALITY by Dimas Nurwinata Rinaldi, Fahriza Nurul Azizah, Candra Galang Gemilang Putra

“…This research discusses the use of cluster analysis to segment Shopee's e-commerce customers based on sociodemographic characteristics with k-means algorithm and conjoint analysis to determine which e-service quality attributes are most important to each cluster. …”
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The Comparison Combination of Naïve Bayes Classification Algorithm with Fuzzy C-Means and K-Means for Determining Beef Cattle Quality in Semarang Regency by Feroza Rosalina Devi, Endang Sugiharti, Riza Arifudin

“…In this research, used the combination of Naïve Bayes Classification and Fuzzy C-Means algorithm also Naïve Bayes Classification and K-Means. …”
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Inferring Agronomical Insights for Wheat Canopy Using Image-Based Curve Fit K-Means Segmentation Algorithm and Statistical Analysis by Ankita Gupta, Lakhwinder Kaur, Gurmeet Kaur

“…The proposed algorithm presented here has three stages: (i) first, derivation of dynamic threshold value by curve fitting of data to eliminate the pixels of low-intensity value, (ii) second, extraction and segmentation of thresholded region by application of histogram-based K-means algorithm iteratively (this scheme of the algorithm is referred to as the curve fit K-means (CfitK-means) algorithm); and (iii) third, computation of 23 grey level cooccurrence matrix (GLCM) texture features (traits) from the wheat images has been done. …”
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Segmentasi Pelanggan E-Commerce Menggunakan Fitur Recency, Frequency, Monetary (RFM) dan Algoritma Klasterisasi K-Means by Reyhan Muhammad Fauzan, Ganjar Alfian

“…The study proposes the K-Means algorithm and compares it with K-Medoids and Fuzzy C Means using publicly available e-commerce datasets. …”
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Benchmarking validity indices for evolutionary K-means clustering performance by Abiodun M. Ikotun, Faustin Habyarimana, Absalom E. Ezugwu

“…These findings provide practical guidance for selecting appropriate fitness functions in Evolutionary K-Means algorithms for automatic clustering tasks.…”
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Clustering OKU Timur Script Images using VGG Feature extraction and K-Means by Liu Toriko, Susan Dian Purnamasari, Yesi Novaria Kunang, Ilman Zuhri Yadi, Andri Andri

“…Features are extracted using the VGG16 model, which are then clustered with the K-Means algorithm. Clustering performance is evaluated based on the percentage of correctly grouped characters. …”
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A Multi-Objective Particle Swarm Optimization Approach for Optimizing K-Means Clustering Centroids by Aina Latifa Riyana Putri, Joko Riyono, Christina Eni Pujiastuti, Supriyadi

“…The K-Means algorithm is a popular unsupervised learning method used for data clustering. …”
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Subjective Air Traffic Complexity Analysis Based on Weak Supervised Learning by Weining ZHANG, Weijun PAN, Changqi YANG, Xinping ZHU, Jianan YIN, Jinghan DU

“…Compared with the K-means algorithm based on Euclidean distance, metric learning improves the optimal silhouette coefficient and Davidson-Boldin index by 31.80% and 12.97%, respectively. …”
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Research on action matching of skeletal point coordinates and sports teaching application based on Open-pose by Shunmin Su

“…The k-means algorithm is used to quantize the features of the skeletal point coordinates and the residual operations are concatenated to obtain the skeletal point feature vectors, which are probabilistically weighted to improve the accuracy of matching the skeletal point coordinates with the postural movements. …”
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Low-dose computed tomography image denoising using pixel level non-local self-similarity prior with non-local means for healthcare informatics by Dawa Chyophel Lepcha, Bhawna Goyal, Ayush Dogra, Krunal Vaghela, Ashish Singh, K. S. Ravi Kumar, Durga Prasad Bavirisetti

“…Furthermore, the study incorporates an enhanced version of a recently proposed nonlocal means algorithm. This revised approach uses discrete neighbourhood filtering properties to enable efficient, vectorized, and parallel computation on modern shared-memory platforms thereby reducing computational complexity. …”
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The analysis of sculpture image classification in utilization of 3D reconstruction under K-means++ by Xuhui Wang

“…This study employs a combined image classification method using the ResNet50 and K-means + + algorithm, optimizing the accuracy issues of traditional classification methods and achieving promising classification results.…”
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Fuzzy clustering method based on genetic algorithm in intrusion detection study by HUANG Min-ming LIN Bo-gang

“…Regarding the problem that fuzzy c-means algorithm（FCM） was sensitive to the initial value and converging to the local infinitesimal point easily, applies genetic algorithm to optimization of the FCM algorithm.Firstly, the results of FCM will be sent to the genetic algorithm for optimization, then the new results again used in FCM to obtain the most advantage of the overall situation.The experimental result shows that the algorithm can effectively detect anomaly intrusions behavior of special target and be better than FCM algorithm, and have a strong global optimization and faster convergence speed.…”
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Pulse wave time series unsupervised clustering with importance ratios for heart failure subgroups detection by Dandan WU, Ryohei ONO, Sirui WANG, Yoshio KOBAYASHI, Hao LIU

“…We collected and normalized pulse wave time series and clinical characteristics from 380 HF patients, which were clustered by introducing the K-means++ algorithm and the clustering performance was assessed along with the clinical characteristic differences between clusters. …”
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Approach for distributed BPEL engine placement using K-means by Rong-heng LIN, Bu-dan WU, Yao ZHAO, Fang-chun YANG

“…The algorithm transforms the BPEL engine placing model into some optimization model in mathematics, and the optimization problem is solved by K-means algorithm. How to apply the algorithm in dif-ferent network topologies was also discussed, such as random graph and tree network. …”
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