Implementasi Metode Saw Dan K-Means Clustering Dalam Sistem Pendukung Keputusan Untuk Penentuan Strategi Pembelajaran Adaptif Bagi Siswa Tunarungu: Studi Kasus Di Slb Negeri Jember

Ramadhani, Ichie Revans Ali Fikri (2026) Implementasi Metode Saw Dan K-Means Clustering Dalam Sistem Pendukung Keputusan Untuk Penentuan Strategi Pembelajaran Adaptif Bagi Siswa Tunarungu: Studi Kasus Di Slb Negeri Jember. Undergraduate thesis, Politeknik Negeri Jember.

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Abstract

The subjective and inconsistent student grouping process for deaf students (tunarungu) at SLB Negeri Jember highlights the need for a more systematic approach. This research develops a Decision Support System (DSS) using the Simple Additive Weighting (SAW) method integrated with K-Means Clustering, built on a Flutter, FastAPI, and MySQL architecture. Four criteria were used: Cognitive Ability (30%), Communication Ability (25%), Social Ability (20%), and Learning Motivation (25%), producing three student groups Smart, Sufficient, and Needs Assistance each with tailored learning strategy recommendations. Functional testing via Blackbox Testing yielded 100% Passed, UAT achieved 98.67%, and confusion matrix evaluation proved 100% decision accuracy against expert judgment, confirming the system as a valid, objective, and data-driven decision-making tool for teachers.

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