Integrating Machine Learning with Four Pillars of Destiny and Five Elements: A Study on Career Selection Strategies

Effective career guidance is essential for helping individuals make informed career choices, yet traditional methods often fall short, leading to dissatisfaction and misalignment with career aspirations. The Four Pillars of Destiny, a traditional chinese metaphysical framework, offers unique insights into personality traits and potential career paths but is not widely integrated into modern career coaching. Meanwhile, machine learning provides personalized, data-driven career recommendations but faces challenges such as potential biases. This study aims to explore how the four pillars of destiny can be combined with contemporary career counselling methods and evaluate the effectiveness of machine learning in career selection, addressing the gap in integrating traditional and modern approaches to enhance career decision-making processes. We collected data on billionaires from Wikidata, including their birthdate, which allowed us to calculate the pillars of day, month, and year, essential components of the Four Pillars of Destiny. Each pillar was related to the five elements (wood, fire, earth, metal, water), providing a comprehensive view of the individual's elemental composition. The dataset was meticulously cleaned and pre-processed to ensure accuracy and reliability. We employed principal component analysis and random forest algorithms to analyse the data, achieving an overall accuracy of 66%. The study revealed that while the model performed reasonably well, there is room for improvement, particularly in handling class imbalances. The development of a career advisor web solution based on the four pillars of destiny and the five elements theory represents a significant advancement in personalized career guidance. This tool offers tailored career recommendations by aligning individuals' intrinsic strengths with suitable career paths, providing a unique and culturally enriched perspective on career planning. The web solution, currently in its alpha testing phase, aims to enhance career decision-making by integrating traditional elements with modern technology. This study underlines the potential benefits of combining the four pillars of destiny and machine learning in career coaching, offering a holistic approach to career guidance.

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Publication Details

Journal
Citra Journal of Computer Science and Technology
Published
2025-06-16
DOI
https://doi.org/10.37934/cjcst.1.1.4663
Primary Topic
AI and HR Technologies
Type
article
Field-Weighted Citation Impact
0.00
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article

Integrating Machine Learning with Four Pillars of Destiny and Five Elements: A Study on Career Selection Strategies

Li‐Cheng Chan, Hwasoo Yeo, Khalida Ismail, Jeremy Chan et al.
Citra Journal of Computer Science and Technology
AI and HR Technologies
article

Integrating Machine Learning with Four Pillars of Destiny and Five Elements: A Study on Career Selection Strategies

Li‐Cheng Chan, Hwasoo Yeo, Khalida Ismail, Jeremy Chan, Wei Gan, Noor Fatihah Mazlam, Yong Quay So
article en

Abstract

Effective career guidance is essential for helping individuals make informed career choices, yet traditional methods often fall short, leading to dissatisfaction and misalignment with career aspirations. The Four Pillars of Destiny, a traditional chinese metaphysical framework, offers unique insights into personality traits and potential career paths but is not widely integrated into modern career coaching. Meanwhile, machine learning provides personalized, data-driven career recommendations but faces challenges such as potential biases. This study aims to explore how the four pillars of destiny can be combined with contemporary career counselling methods and evaluate the effectiveness of machine learning in career selection, addressing the gap in integrating traditional and modern approaches to enhance career decision-making processes. We collected data on billionaires from Wikidata, including their birthdate, which allowed us to calculate the pillars of day, month, and year, essential components of the Four Pillars of Destiny. Each pillar was related to the five elements (wood, fire, earth, metal, water), providing a comprehensive view of the individual's elemental composition. The dataset was meticulously cleaned and pre-processed to ensure accuracy and reliability. We employed principal component analysis and random forest algorithms to analyse the data, achieving an overall accuracy of 66%. The study revealed that while the model performed reasonably well, there is room for improvement, particularly in handling class imbalances. The development of a career advisor web solution based on the four pillars of destiny and the five elements theory represents a significant advancement in personalized career guidance. This tool offers tailored career recommendations by aligning individuals' intrinsic strengths with suitable career paths, providing a unique and culturally enriched perspective on career planning. The web solution, currently in its alpha testing phase, aims to enhance career decision-making by integrating traditional elements with modern technology. This study underlines the potential benefits of combining the four pillars of destiny and machine learning in career coaching, offering a holistic approach to career guidance.

Citra Journal of Computer Science and TechnologyVol. 1(1)
Southern University College (MY)
Openalex Percentile: Top 82%
AI and HR Technologies
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