Analisis penggabungan metode SAW (Simple Additive Weighting) dan TOPSIS (Technique Order Preference by Similarity to Ideal Solution) dalam sistem penerimaan tutor les privat

Siswanto, Wendi (2019) Analisis penggabungan metode SAW (Simple Additive Weighting) dan TOPSIS (Technique Order Preference by Similarity to Ideal Solution) dalam sistem penerimaan tutor les privat. Diploma thesis, UIN Sunan Gunung Djati Bandung.

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Abstract

INDONESIA Lembaga Pendidikan Les Privat merupakan salah satu unit bisnis perusahaan yang ada di kota Bandung. Unit bisnis ini terbentuk karena perkembangan zaman, dimana siswa hanya memiliki waktu yang relatif sedikit untuk dapat mengikuti bimbingan belajar secara langsung. Unit bisnis ini, awalnya hanya memiliki sekitar 25 tutor saja, tetapi sekarang sudah mencapai hampir 4 kali lipatnya, dimana setiap tutor memiliki siswa antara 4-5. Dengan perkembangan unit bisnis les privat yang semakin pesat, hal ini memicu munculnya permasalahan untuk menjaring calon tutor-tutor terbaik. Salah satu cara untuk menjaring tutor-tutor terbaik adalah dengan membuat Sistem Pengambilan Keputusan (SPK) yang menggabungkan dua algoritma MCDM (Multi Criteria Decission Making) yaitu algoritma Simple Additive Weighting (SAW) dan Topsis. Penggabungan ini dilakukan karena kedua metode tersebut memiliki konsep yang sederhana, mudah dipahami, komputasinya efisien, serta memiliki kemampuan untuk mengukur kinerja relatif dari alternatif-alternatif keputusan dalam bentuk matematis yang sederhana. Terdapat 4 kriteria yang dibutuhkan perusahaan untuk menjaring tutor terbaik, diantaranya Indeks Prestasi Kumulatif (IPK), Tes Potensi Akademik (TPA), Interview, dan Microteaching. Hasil perhitungan sebanyak 5 sampel dari data yang ada dengan menggunakan algoritma Simple Additive Weighting (SAW) dan Topsis didapatkan hasil 0.709 sebagai hasil terbesar, dan hasil terkecil yaitu 0.257. ENGLISH Private Les Education Institution is one of the company's business units in the city of Bandung. This business unit was formed because of the times, where students only have relatively little time to be able to follow tutoring directly. This business unit, initially only had around 25 tutors, but now has reached almost 4 times that, where each tutor has students between 4-5. With the rapid development of private tutoring business units, this has triggered problems to attract the best prospective tutors. One way to capture the best tutors is to create a Decision Support System (DSS) which combines two MCDM (Multi Criteria Decission Making) algorithms, namely Simple Additive Weighting (SAW) and Topsis algorithm. This merging is done because the two methods have a simple concept, easy to understand, efficient computation, and have the ability to measure the relative performance of decision alternatives in a simple mathematical form. There are 4 criteria needed by companies to recruit the best tutors, including Cumulative Achievement Index (GPA), Academic Potential Test (TPA), Interview, and Microteaching. The results of the calculation of 5 samples of existing data using the Simple Additive Weighting (SAW) and Topsis algorithm obtained 0.709 results as the largest results, and the smallest result is 0.257.

Item Type: Thesis (Diploma)
Uncontrolled Keywords: SAW; Topsis; Privat; MCDM; SPK;
Subjects: Applied Physics > Computer Engineering
Divisions: Fakultas Sains dan Teknologi > Program Studi Teknik Informatika
Depositing User: Wendi Siswanto
Date Deposited: 08 Jan 2020 01:49
Last Modified: 08 Jan 2020 01:49
URI: https://etheses.uinsgd.ac.id/id/eprint/28634

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