HARIYADI, Guruh Taufan and Purwanto, Purwanto and Isnanto, R. Rizal (2026) PENGEMBANGAN STRATEGI PEMASARAN RAMAH LINGKUNGAN UNTUK MEMBIDIK KONSUMEN HIJAU PADA PASAR DIGITAL. Doctoral thesis, UNIVERSITAS DIPONEGORO.

	Text cover awal.pdf Download (198kB)
	Text Disertasi Guruh_cover sampai abstract.pdf Restricted to Repository staff only Download (22MB)
	Text Disertasi Guruh_isi Bab 1.pdf Download (1MB)
	Text Disertasi Guruh_isi Bab 2.pdf Download (1MB)
	Text Disertasi Guruh_isi Bab 3.pdf Restricted to Repository staff only Download (1MB)
	Text Disertasi Guruh_isi Bab 4.pdf Restricted to Repository staff only Download (6MB)
	Text Disertasi Guruh_isi Bab 5.pdf Restricted to Repository staff only Download (615kB)
	Text Disertasi Guruh_Daftar Pustaka.pdf Download (403kB)
	Text Disertasi Guruh_LAMPIRAN.pdf Restricted to Repository staff only Download (532kB)

Abstract

Pertumbuhan populasi dunia yang mencapai 7,73 miliar jiwa mendorong percepatan pembangunan ekonomi, meningkatkan permintaan sumber daya, dan menimbulkan tantangan lingkungan. Pemasaran hijau menjadi solusi untuk mengatasi masalah lingkungan sekaligus menciptakan nilai ekonomi melalui produk ramah lingkungan. Namun, perilaku konsumen terhadap produk hijau di pasar digital masih kurang dipahami, terutama di Indonesia, dengan populasi digital mencapai 277,7 juta pengguna. Penelitian ini bertujuan memahami perilaku konsumen hijau di pasar digital Indonesia, mengidentifikasi segmen konsumen, dan merumuskan strategi pemasaran hijau yang efektif. Penelitian ini menggunakan pendekatan kuantitatif dengan metode K-Means untuk klasterisasi konsumen hijau, mengidentifikasi empat klaster berdasarkan 32 faktor pengambilan keputusan. Data dikumpulkan dari populasi pengguna produk ramah lingkungan. Analisis faktor dilakukan dengan Rotated Factor Analysis, sedangkan strategi pemasaran dievaluasi menggunakan metode Multi-Criteria Decision Making (MCDM) seperti TOPSIS, VIKOR, dan MOORA. Model prediksi dibangun dengan Random Forest untuk mengevaluasi efektivitas strategi. Hasil penelitian mengidentifikasi empat klaster konsumen: Eco-Considerate, Eco-Apathetic, Eco-Conscious, dan Eco-Enthusiast. Strategi pemasaran hijau yang paling efektif adalah menciptakan merek hijau ikonik, diikuti oleh mencari mitra kredibel dan edukasi masyarakat. Model prediksi Random Forest menunjukkan akurasi pelatihan 97,0% dan pengujian 81,6%, mengindikasikan performa prediksi yang baik. Penelitian ini menawarkan wawasan baru untuk pemasaran hijau di pasar digital Indonesia.
Kata Kunci: konsumen hijau, pasar digital, strategi pemasaran hijau, K-Means, MCDM, Random Forest

The global population growth, which has reached 7.73 billion, drives accelerated economic development, increases demand for resources, and presents significant environmental challenges. Green marketing has emerged as a solution to address environmental issues while simultaneously creating economic value through environmentally friendly products. However, consumer behavior toward green products in the digital marketplace remains insufficiently understood, particularly in Indonesia, where the digital population has reached 277.7 million users. This study aims to understand green consumer behavior in Indonesia’s digital market, identify consumer segments, and formulate effective green marketing strategies. A quantitative approach was employed, utilizing the K-Means method to cluster green consumers based on 32 decision-making factors. Data were collected from users of environmentally friendly products. Factor analysis was conducted using Rotated Factor Analysis, while green marketing strategies were evaluated using Multi-Criteria Decision Making (MCDM) methods, including TOPSIS, VIKOR, and MOORA. A predictive model was developed using Random Forest to assess the effectiveness of the proposed strategies. The study identified four consumer clusters: Eco-Considerate, Eco-Apathetic, Eco-Conscious, and Eco-Enthusiast. The most effective green marketing strategy was found to be the creation of an iconic green brand, followed by partnering with credible entities and educating the public. The Random Forest prediction model demonstrated a training accuracy of 97.0% and a testing accuracy of 81.6%, indicating strong predictive performance. This research provides new insights into green marketing within Indonesia’s digital market.
Keywords: green consumers, digital market, green marketing strategy, K-Means, MCMD, Random Forest

Actions (login required)

View Item