PUTRA, LUDO GANANG SURYA (2025) ANALISIS PERAMALAN PENJUALAN MOBIL LISTRIK DI INDONESIA, PENDEKATAN KUANTITATIF UNTUK PERENCANAAN OPERASIONAL. S2 thesis, Universitas Mercu Buana Jakarta.
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Abstract
This study applies a quantitative time-series forecasting approach using three methods: moving average, exponential smoothing, and trend analysis. Secondary data on electric car sales in Indonesia were analyzed to assess the predictive accuracy of each method. Forecasting performance was evaluated using the Mean Absolute Percentage Error (MAPE), a widely recognized accuracy metric. The findings indicate that the moving average method yielded the lowest MAPE for BEV sales at 9.72%, categorized as “highly accurate” (<10%), and for HEV sales at 16.94%, categorized as “accurate” (10–20%). For PHEV sales, the trend analysis method achieved superior accuracy compared to other models. These results highlight that forecasting performance varies across EV categories, reinforcing the importance of model selection based on market characteristics and data patterns. Keywords: Electric vehicle sales forecasting, time-series analysis, moving average, exponential smoothing, trend analysis, MAPE, operational planning. Penelitian ini menerapkan pendekatan peramalan deret waktu kuantitatif dengan menggunakan tiga metode: rata-rata bergerak, pemulusan eksponensial, dan analisis tren. Data sekunder penjualan mobil listrik di Indonesia dianalisis untuk menilai keakuratan prediksi setiap metode. Kinerja peramalan dievaluasi menggunakan Mean Absolute Percentage Error (MAPE), sebuah metrik akurasi yang dikenal luas. Temuan menunjukkan bahwa metode moving average menghasilkan MAPE terendah untuk penjualan BEV sebesar 9,72% yang dikategorikan ―sangat akurat‖ (<10%), dan untuk penjualan HEV sebesar 16,94% yang dikategorikan ―akurat‖ (10–20%). Untuk penjualan PHEV, metode analisis tren mencapai akurasi yang unggul dibandingkan model lainnya. Hasil ini menyoroti bahwa perkiraan kinerja bervariasi antar kategori kendaraan listrik, sehingga memperkuat pentingnya pemilihan model berdasarkan karakteristik pasar dan pola data. Kata Kunci : Peramalan penjualan kendaraan listrik, analisis deret waktu, Moving Average, Exponential Smoothing, analisis tren, MAPE, perencanaan operasional.
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