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"Online business or e-commerce is now very popular and is a growing industry in Indonesia. Although the growth is high with a 15% rise from 2011, it is found that only 57% of the Indonesians used the Internet for online shopping (MasterCard, 2012). To increase purchases through online stores, a study on customer satisfaction is needed. This study designs a preferred service for fashion online shops based on customer preferences, which would then increase customer satisfaction. By analyzing service attributes that enhance satisfaction for online customers, a suitable service for fashion online shops could be generated. The Kano model is used to classify which service attributes are important for improving and developing the quality of fashion online shops. To understand customer preferences for fashion online shops, conjoint analysis is used to calculate the preferences statistically."

"Menanggapi permintaan global akan transportasi yang berkelanjutan, pasar kendaraan listrik (EV), khususnya sepeda motor listrik (EM), telah mendapatkan perhatian yang signifikan. Penelitian ini berfokus pada pemahaman faktor-faktor yang memengaruhi adopsi kendaraan listrik di Jakarta, ibu kota Indonesia, dengan menggunakan Extreme Gradient Boosting (XGBoost), dan mengatasi tantangan data yang tidak seimbang melalui Synthetic Minority Over-sampling Technique (SMOTE). Dengan menganalisis data survei, penelitian ini memprediksi adopsi EM berdasarkan berbagai faktor sikap, demografi, paparan EM, dan faktor yang berhubungan dengan kendaraan. Penelitian ini menunjukkan hasil yang menjanjikan dengan Model Evaluasi yang menunjukkan presisi tinggi (0,747), recall (0,755), dan F1 Score (0,705). Yang paling penting adalah nilai G-Mean sebesar 0.809, yang menunjukkan kinerja model yang kuat dalam menangani data yang tidak seimbang. Penerapan SMOTE secara signifikan berkontribusi pada peningkatan kinerja model, membuat analisis prediktif menjadi lebih andal. Faktor-faktor penentu utama yang memengaruhi adopsi kendaraan listrik termasuk partisipasi dalam acara promosi kendaraan listrik, pengalaman mengendarai kendaraan listrik, dan kepemilikan sepeda motor pribadi. Wawasan ini memberikan panduan yang berharga untuk kebijakan publik dan strategi pemasaran, memastikan pemahaman yang komprehensif tentang faktor-faktor yang berpengaruh terhadap adopsi kendaraan listrik di Jakarta, Indonesia.

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In response to the global demand for sustainable transportation, the electric vehicle (EV) market, particularly electric motorcycles (EM), has gained significant attention. This research focuses on understanding the factors influencing EM adoption in Indonesia, the capital city of Indonesia, utilizing Extreme Gradient Boosting (XGBoost), and addressing the challenge of imbalanced data through Synthetic Minority Over-sampling Technique (SMOTE). By analyzing Indonesia data, this research predicts EM adoption based on various attitudinal, demographic, EM exposure, and vehicle-related factors. The research shows a promising result with an Evaluation Model that demonstrates high precision (0.747), recall (0.755), and F1 Score (0.705). Especially noteworthy is the G-Mean score of 0.809, indicating a robust model performance in handling imbalanced data. The application of SMOTE significantly contributed to the improvement of model performance, making the predictive analysis more reliable. Key determinants influencing electric vehicle adoption include participation in electric vehicle promotional events, EM riding experience, and personal motorcycle ownership. These insights provide valuable guidance for public policies and marketing strategies, ensuring a comprehensive understanding of the influential factors steering EM adoption in Indonesia, Indonesia."