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Prediction of payment method in convenience stores using machine learning by Pratondo, Agus, Novianty, Astri, Pudjoatmodjo, Bambang

“…This study explores the application of machine learning techniques, specifically the Random Forest algorithm, to predict payment modes in the context of the Indonesian community. …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud by Shariff, S. Sarifah Radiah, Hud, Hady

“…Secondly, in solving every Machine Learning problem, there is no one algorithm superior to other algorithms. …”
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Optimization of hybrid flow shop scheduling in a machine shop: Achieving energy efficiency and minimizing machine idleness with multi-objective Tiki Taka optimization by Siti Nurhazwani Husna, Mohd Hata, Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

“…The optimization result was compared to established algorithms, such as the Non-dominated Sorting Genetic Algorithm-II, the Multi Objectives Evolutionary Algorithm Based on Decomposition, the Multi Objectives Particle Swarm Optimization, and the recent algorithm Multi Objectives Grey Wolf Optimizer. …”
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SUDOKU HELPER by Abdul Razak, Muhammad Asyraf

“…In this paper research, author presents an algorithm to provide a tutorial for any Sudoku player who got stuck during the solving process. …”
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Machine Learning-based Classification Of Termite Genera by Sundresan A/L Perumal, Homathevi Rahman, Valliappan Raman, Subramanian Raja Nagendran, Bala Saatvik Thanigai Arasu, Deepakkumar Senthil Kumar, Roghan Raja

Age detection from face using Convolutional Neural Network (CNN) / Hanin Hanisah Usok @ Yusoff by Usok @ Yusoff, Hanin Hanisah

“…A user-friendly desktop system is created for input of facial photos and receiving immediate age estimation results, illustrating machine learning's assure in age identification. With implications for personalised services and security, this experiment demonstrates how CNN algorithms improve accuracy, adding to successful age-related technology.…”
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Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids by Chiaverini, Luca, Macdonald, David W., Hearn, Andrew J., Kaszta, Zaneta, Ash, Eric, Bothwell, Helen M., Can, Ozgun Emre, Channa, Phan, Clements, Gopalasamy Reuben *, Haidir, Iding Achmad, Kyaw, Pyae Phyoe, Moore, Jonathan H., Rasphone, Akchousanh, Tan, Cedric Kai Wei, Cushman, Samuel A.

“…The former is a parametric regression model providing functional models with direct interpretability. The latter is a machine learning non-parametric algorithm, more tolerant than other approaches in its assumptions, which has often been shown to outperform parametric algorithms. …”
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The predictive machine learning model of a hydrated inverse vulcanized copolymer for effective mercury sequestration from wastewater by Ghumman, A.S.M., Shamsuddin, R., Abbasi, A., Ahmad, M., Yoshida, Y., Sami, A., Almohamadi, H.

“…NMDG functionalized IVP removed 100 Hg2+ from a low feed concentration (10â��50 mg/l). A predictive machine learning model was also developed to predict the amount of mercury removed () using GPR, ANN, Decision Tree, and SVM algorithms. …”
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Talkout : Protecting mental health application with a lightweight message encryption by Gavin Teo Juen

“…The investigation of lightweight message encryption algorithms is conducted with systematic quantitative literature and experiment implementation in Java and Android running environment. …”
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Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making by Chuan, Zun Liang, Chong, Teak Wei, Japashov, Nursultan, Soon, Kien Yuan, Tan, Wei Qing, Noriszura, Ismail, Liong, Choong-Yeun, Tan, Ee Hiae

“…Moreover, the introduction of the novel stacked ensemble machine learning algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. …”
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Implementation of welch pre-processing in SVM algorithm for improved accuracy on EEG data by Hariyady Hariyady, Ag Asri Ag Ibrahim, Jason Teo, Muhammad Balya Firjaun Barlaman, Muhammad Aulanas Bitaqwa, Azhana Ahmad, Fouziah Md Yassin, Carolyn Salimun, Ng, Giap Weng

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Artificial intelligence (AI) and its application in architecture design: a thematic review by Jin, Deran, Zairul, Mohd, Salih, Sarah Abdulkareem

“…Despite the growing number of publications on AI and architectural design, comprehensive reviews are lacking in exploring its evolution, strategies, and future directions. …”
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A fuzzy approach for early human action detection / Ekta Vats by Ekta, Vats

“…However, the employability of these algorithms depends on the desired application and its requirements. …”
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Object-Oriented Programming semantics representation utilizing agents by Mohd Aris, Teh Noranis

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Using Machine Learning to Optimize Green Influencer Marketing Strategies: A Study of Consumer Behavior Trends by Neetu, Sharma

“…This study fills a regional gap by offering India-specific, empirical evidence on the synergy between ML-driven marketing and green consumer behavior. Its practical implications are twofold: marketers can leverage these insights to enhance influencer selection and recommendation strategies, while policymakers and researchers gain a data-informed perspective to promote sustainable marketing practices. …”
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Multi-floor indoor location estimation system based on wireless local area network by Chua, Tien Han

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Temporal - spatial recognizer for multi-label data by Mousa, Aseel

“…The imHTM (Improved HTM) method includes improvement in two of its components; feature extraction and data clustering. …”
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A malware analysis and detection system for mobile devices / Ali Feizollah by Ali, Feizollah

“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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An approach to improve detecting and removing cross- site scripting vulnerabilities in web applications by Hydara, Isatou

“…This research work was limited to Java based web applications. In future research, the method can be extended to include other programming languages as well as other similar web application security vulnerabilities.…”
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Mental stress classification based on selected electroencephalography channels using correlation coefficient of Hjorth parameters by Hag, Ala, Al-Shargie, Fares, Handayani, Dini Oktarina Dwi, Asadi, Houshyar

“…Leveraging features from the time, frequency, and time–frequency domains of these channels, and employing machine learning algorithms, notably RLDA, SVM, and KNN, our approach achieved a remarkable accuracy of 81.56% with the SVM algorithm outperforming existing methodologies. …”
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