PERSONALITY ANALYSIS THROUGH SOCIAL MEDIA BASED ON MACHINE LEARNING - Capstone - Capstone
M. JAKA FIRDAUS TEGUH YAHYA

Informasi Umum

Kode

24.04.5964

Klasifikasi

006.7 - Web Design

Jenis

Karya Ilmiah - Skripsi (S1) - Reference

Subjek

Web Application

Dilihat

200 kali

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Abstraksi

<a name="_Toc174741495">ABSTRACT</a><br /> Mismatch between skills, personality, and work can be a significant issue in the professional world. This mismatch can lead to a decrease in performance and make it more challenging for workers to achieve their expected maximum performance. One contributing factor is that many jobs do not align with an individual’s personality. To address this issue, it is crucial for individuals to recognize their potential and personality analytically, through increased self-awareness, which helps in identifying personal strengths and weaknesses.<br /> Such self-recognition can be facilitated by using programs designed to assess one's abilities and provide relevant job recommendations. The PSYCHEE website offers such a self-recognition tool, which identifies users' self-awareness and potential skills. The program then generates employment recommendations based on the user's data qualities. The PSYCHEE website provides approximately 89% prediction accuracy for text classification from X or Twitter and 100% accuracy for datasets processed with the GPT chat prompt. This website is integrated with Chat GPT as an assistive tool in the form of a chat prompt, and an API key is used to enable interaction between the PSYCHEE website and GPT chat.<br /> Test results indicate that the XGBoost model has the highest accuracy. This developed model will be used to classify MBTI personalities based on social media content and will be implemented into the Psyche web application. The Psyche web application undergoes two stages of development: functional development and staging. The first stage focuses on ensuring that all features function correctly. The results from this initial testing phase can be seen in Table 2.5. The second testing phase involved respondents testing the Psyche web application and providing feedback via a questionnaire. The findings from the questionnaire indicated that respondents generally agreed that Psyche functions smoothly.<br /> <strong>Keywords:</strong> job mismatch, personality, self-awareness, PSYCHEE website, XGBoost model, Psyche web application.

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