Pengembangan Strategic Dashboard dan Implementasi Model ARIMA sebagai Pendukung Kebijakan Adopsi Kendaraan Listrik di Indonesia

Ahmady, Syamsu Alam (2025) Pengembangan Strategic Dashboard dan Implementasi Model ARIMA sebagai Pendukung Kebijakan Adopsi Kendaraan Listrik di Indonesia. Masters thesis, Institur Teknologi Sepuluh Nopember.

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Abstract

Target ambisius Net Zero Emission (NZE) Indonesia di sektor transportasi menuntut percepatan adopsi Kendaraan Listrik (EV), dengan target operasional 2 juta unit mobil listrik mengaspal pada tahun 2030. Tesis ini mengembangkan kerangka kerja Strategic Dashboard yang mengintegrasikan peramalan statistik dengan evaluasi kebijakan untuk menjawab kesenjangan informasi strategis di kalangan pembuat kebijakan. Penelitian ini menerapkan model peramalan Seasonal AutoRegressive Integrated Moving Average (SARIMA) untuk menangkap pola musiman data penjualan GAIKINDO, yang kemudian dikonversi melalui mekanisme flow-to-stock untuk memproyeksikan total populasi EV di masa depan. Model terbaik yang terpilih adalah SARIMA(0, 1, 2)(0, 1, 1) dengan akurasi MAPE 23%. Proyeksi skenario Business-as-Usual (BaU) mengestimasi total populasi EV di Indonesia akan mencapai 1.870.177 unit pada akhir tahun 2030. Analisis Kesenjangan Lintasan (Trajectory Gap Analysis) mengungkap adanya defisit strategis sebesar 129.823 unit dari target pemerintah (2 juta unit). Temuan ini membuktikan bahwa dasbor berfungsi sebagai sistem peringatan dini dan mengindikasikan perlunya reorientasi kebijakan, karena faktor infrastruktur SPKLU memiliki korelasi yang lebih kuat (r = 0,822) terhadap penjualan dibandingkan insentif fiskal semata (r = 0,693).
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Indonesia’s ambitious Net Zero Emission (NZE) targets in the transportation sector necessitate the accelerated adoption of Electric Vehicles (EVs), with an operational target of 2 million electric cars on the road by 2030. This thesis addresses this strategic information gap among policymakers by developing a Strategic Dashboard framework that integrates statistical forecasting with policy evaluation. This research applies the Seasonal AutoRegressive Integrated Moving Average (SARIMA) forecasting model to capture the seasonal patterns of GAIKINDO sales data, which is then converted through a flow-to-stock mechanism to project the future total EV population. The best-selected model was SARIMA(0, 1, 2)(0, 1, 1) which achieved a Mean Absolute Percentage Error (MAPE) of 23%. The Business-as-Usual (BaU) scenario projected the total EV population would reach 1,870,177 units by the end of 2030. The Trajectory Gap Analysis revealed a strategic deficit of 129,823 units against the government's 2 million unit target. This finding serves as an early warning system, indicating the urgency of policy reorientation, as infrastructure factors (SPKLU availability) showed a stronger correlation (r = 0.822) with sales than fiscal incentives alone (r = 0.693).

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Adopsi Kendaraan Listrik, ARIMA, Strategic Dashboard, Evaluasi Kebijakan, Gap Analysis, Strategic Dashboard, Electric Vehicle Adoption, Policy Evaluation
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD30.213 Management information systems. Dashboards. Enterprise resource planning. H Social Sciences > HD Industries. Land use. Labor > HD30.23 Decision making. Business requirements analysis. H Social Sciences > HD Industries. Land use. Labor > HD30.27 Business forecasting H Social Sciences > HD Industries. Land use. Labor > HD38.7 Business intelligence. Trade secrets
Divisions:	Interdisciplinary School of Management and Technology (SIMT) > 61101-Master of Technology Management (MMT)
Depositing User:	Syamsu Alam Ahmady
Date Deposited:	29 Jan 2026 02:20
Last Modified:	29 Jan 2026 02:20
URI:	http://repository.its.ac.id/id/eprint/131128

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