Integrasi Simple Additive Weighting dan Analisis Selisih Jarak Untuk Meminimalisir Bias Pemilihan Jurusan SMK

Abstract

Sistem Pendukung Keputusan (SPK) merupakan sistem yang dirancang untuk membantu proses pengambilan keputusan dalam memilih alternatif terbaik berdasarkan sejumlah kriteria yang telah ditentukan. Pemilihan jurusan sekolah lanjutan merupakan fase krusial bagi siswa kelas IX, namun seringkali terhambat oleh minimnya pemahaman potensi diri dan kurangnya sistem rekomendasi yang objektif. Penelitian ini bertujuan untuk membangun SPK guna merekomendasikan jurusan Sekolah Menengah Kejuruan (SMK) yang tepat bagi siswa sekolah menengah pertama menggunakan metode Simple Additive Weighting (SAW). Pengambilan keputusan didasarkan pada enam kriteria akademik, yaitu nilai Matematika, IPA, Bahasa Inggris, TIK, Bahasa Indonesia, dan Prakarya. Kebaruan penelitian ini terletak pada penerapan metode SAW dalam dua tahap, yaitu menghitung nilai prefrensi profil ideal setiap jurusan dan menghitung nilai preferensi masing-masing siswa secara terpisah. Selanjutnya, kedua nilai preferensi tersebut dibandingkan menggunakan analisis selisih (gap analysis) untuk memperoleh jurusan dengan tingkat kedekatan tertinggi terhadap profil akademik siswa. Berbeda dengan penggunaan metode SAW pada umumnya yang menentukan rekomendasi alternatif terbaik berdasarkan nilai preferensi tertinggi, penelitian ini menghasilkan rekomendasi berdasarkan nilai selisih terkecil antara siswa terhadap profil ideal jurusan. Hasil pengujian terhadap 35 data siswa dan lima alternatif jurusan menunjukkan bahwa sistem mampu menghasilkan rekomendasi jurusan secara objektif sesuai karakteristik akademik sehingga dapat membantu guru Bimbingan Konseling (BK) dalam memberikan arahan yang presisi, konsisten, dan terukur. Dengan demikian, rekomendasi jurusan tidak ditentukan berdasarkan nilai preferensi tertinggi sebagaimana implementasi SAW pada umumnya, melainkan berdasarkan nilai selisih preferensi terkecil antara profil akademik siswa dan profil ideal masing-masing jurusan.

A Decision Support System (DSS) is a computer-based system designed to assist decision-making processes by selecting the most appropriate alternative based on a set of predefined criteria. Choosing an appropriate study program for upper secondary education is a crucial stage for ninth-grade students, as it significantly influences their future academic and career development. However, this decision is often hindered by students' limited understanding of their academic potential and the lack of an objective recommendation system. This study aims to develop a Decision Support System to recommend suitable vocational majors at Vocational High Schools (SMK) for junior high school students using the Simple Additive Weighting (SAW) method. The decision-making process is based on six academic criteria, namely Mathematics, Natural Sciences, English, Information and Communication Technology (ICT), Indonesian Language, and Craftsmanship (Prakarya). The novelty of this study lies in the implementation of the Simple Additive Weighting (SAW) method through a two-stage evaluation process. In the first stage, the preference values representing the ideal profile of each vocational major are calculated. In the second stage, the preference values of individual students are computed independently using the same evaluation criteria. Subsequently, the two preference values are compared using a gap analysis approach to identify the vocational major with the highest level of similarity to the student's academic profile. Unlike conventional implementations of the Simple Additive Weighting (SAW) method, which determine the best alternative solely based on the highest preference value, the proposed approach recommends a vocational major by identifying the smallest preference gap between the student's academic profile and the ideal profile of each vocational major. Experimental results obtained from 35 student records and five vocational major alternatives demonstrate that the proposed system is capable of generating objective recommendations that accurately reflect students' academic characteristics. Consequently, the system can assist Guidance and Counseling (GC) teachers in providing more precise, consistent, and evidence-based recommendations for selecting the most appropriate vocational major. Therefore, unlike the conventional implementation of the Simple Additive Weighting (SAW) method, which selects the best alternative based on the highest preference value, the proposed approach determines the recommended vocational major by identifying the smallest preference gap between the student's academic profile and the ideal profile of each vocational major.