Penerapan AHP-Topsis Untuk Memilih Kendaraan Ramah Lingkungan Berdasarkan Kriteria

Davina Azalia Tara, Yahya Nur Ifriza

Abstract

Abstrak : 

Kendaraan bermotor berbahan bakar fosil merupakan salah satu kontributor utama emisi CO₂ global yang berdampak pada perubahan iklim dan penurunan kualitas udara. Emisi CO₂ sektor energi mencapai sekitar 34 miliar ton pada tahun 2023, meningkat 49% dibanding tahun 2000, dengan sektor transportasi menyumbang sekitar 23,3% dari total emisi tersebut. Oleh karena itu, diperlukan pendekatan sistematis untuk mengevaluasi dan memilih kendaraan ramah lingkungan berdasarkan berbagai kriteria yang relevan. Penelitian ini bertujuan menerapkan metode Multi-Criteria Decision Analysis (MCDA) dengan kombinasi Analytical Hierarchy Process (AHP) dan Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) untuk menentukan kendaraan paling ramah lingkungan. Dataset yang digunakan adalah CO₂ Emissions dari Kaggle yang terdiri dari 7.385 kendaraan, dengan 1.000 sampel dipilih secara acak untuk analisis. Enam kriteria digunakan, yaitu Engine Size, Cylinders, Fuel Consumption City, Fuel Consumption Highway, Fuel Consumption Comb (mpg), dan CO₂ Emissions. AHP digunakan untuk menentukan bobot kriteria, sedangkan TOPSIS digunakan untuk perankingan alternatif. Hasil penelitian menunjukkan bahwa kriteria CO₂ Emissions memiliki bobot tertinggi sebesar 0,427, sehingga menjadi faktor paling dominan dalam evaluasi. Hasil TOPSIS menunjukkan bahwa kendaraan hybrid, seperti Toyota Prius dan Toyota Corolla Hybrid, menempati peringkat teratas karena memiliki kombinasi emisi rendah dan efisiensi bahan bakar tinggi. Analisis sensitivitas menunjukkan bahwa sistem memiliki tingkat kestabilan yang baik terhadap perubahan bobot sebesar 10%. Dengan demikian, metode AHP–TOPSIS terbukti efektif dan robust sebagai sistem pendukung keputusan dalam pemilihan kendaraan ramah lingkungan berbasis multi-kriteria.

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Abstract : 

Fossil fuel-powered motor vehicles are a major contributor to global CO₂ emissions, contributing to climate change and air quality degradation. Energy sector CO₂ emissions will reach approximately 34 billion tons in 2023, a 49% increase compared to 2000, with the transportation sector contributing approximately 23.3% of these emissions. Therefore, a systematic approach is needed to evaluate and select environmentally friendly vehicles based on various relevant criteria. This study aims to apply the Multi-Criteria Decision Analysis (MCDA) method with a combination of Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to determine the most environmentally friendly vehicles. The dataset used is CO₂ Emissions from Kaggle, consisting of 7,385 vehicles, with 1,000 samples randomly selected for analysis. Six criteria are used: Engine Size, Cylinders, Fuel Consumption City, Fuel Consumption Highway, Fuel Consumption Comb (mpg), and CO₂ Emissions. AHP was used to determine the criteria weights, while TOPSIS was used to rank alternatives. The results showed that the CO₂ Emissions criterion had the highest weight of 0.427, making it the most dominant factor in the evaluation. TOPSIS results showed that hybrid vehicles, such as the Toyota Prius and Toyota Corolla Hybrid, were ranked top due to their combination of low emissions and high fuel efficiency. Sensitivity analysis showed that the system had a good level of stability against a 10% weight change. Thus, the AHP–TOPSIS method proved effective and robust as a decision support system in selecting environmentally friendly vehicles based on multi-criteria.

Keywords

Decision Support System

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DOI: https://doi.org/10.20961/ijai.v10i2.117721

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