Comparison of AHP and SAW Methods for Predicting Career Interests of SMAN 1 Karanganyar Demak Students

This study compares the efficacy of the Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods in predicting career interests of students at SMAN 1 Karanganyar Demak. The research assesses seven key factors: familial influence, educational engagement, individual capabilities, academic performance, institutional resources, resilience of a career, and academic interests. Results show that AHP prioritizes familial influence (28.94%), individual capabilities (17.10%), and educational engagement (16.23%), while SAW highlights career (15.75%), educational engagement (15.61%), and individual capabilities (14.92%). Both methods achieved an accuracy of 83.02%. Career recommendations were categorized into guidance-intensive cases (AHP: 42.68%; SAW: 46.00%), employment-oriented individuals (AHP: 33.96%; SAW: 32.97%), higher education aspirants (AHP: 12.94%; SAW: 10.06%), and entrepreneurial prospects (AHP: 10.42%; SAW: 10.96%).

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Publication Details

Journal
SISTEMASI
Published
2025-03-04
DOI
https://doi.org/10.32520/stmsi.v14i2.5025
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
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article

Comparison of AHP and SAW Methods for Predicting Career Interests of SMAN 1 Karanganyar Demak Students

Ardian Adi Prabowo, Agus Supriyanto
SISTEMASI
Data Mining and Machine Learning Applications
article

Comparison of AHP and SAW Methods for Predicting Career Interests of SMAN 1 Karanganyar Demak Students

Ardian Adi Prabowo, Agus Supriyanto
article en

Abstract

This study compares the efficacy of the Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods in predicting career interests of students at SMAN 1 Karanganyar Demak. The research assesses seven key factors: familial influence, educational engagement, individual capabilities, academic performance, institutional resources, resilience of a career, and academic interests. Results show that AHP prioritizes familial influence (28.94%), individual capabilities (17.10%), and educational engagement (16.23%), while SAW highlights career (15.75%), educational engagement (15.61%), and individual capabilities (14.92%). Both methods achieved an accuracy of 83.02%. Career recommendations were categorized into guidance-intensive cases (AHP: 42.68%; SAW: 46.00%), employment-oriented individuals (AHP: 33.96%; SAW: 32.97%), higher education aspirants (AHP: 12.94%; SAW: 10.06%), and entrepreneurial prospects (AHP: 10.42%; SAW: 10.96%).

SISTEMASIVol. 14(2)
Universitas Stikubank (ID)
Openalex Percentile: Top 95%
Data Mining and Machine Learning Applications
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Comparison of AHP and SAW Methods for Predicting Career Interests of SMAN 1 Karanganyar Demak Students — Ardian Adi Prabowo, Agus Supriyanto · SISTEMASI (2025) | TGRS Research Map | TGRS