Abstract :

Transportation is an essential aspect of people’s lives that plays an essential role in supporting economic, social, and cultural activities. Private transportation has become a basic need for Indonesian people, increasing yearly, especially for motorcycles. One of the biggest motorcycle brands in Indonesia is Honda, and West Java is one of the most significant contributors to motorcycle usage. However, their market share is decreasing through the years. It is essential to review customer satisfaction in purchasing Honda products both in terms of product and service through their customer journey in purchasing Honda products. Therefore, this research will discover the aspects customers need from online reviews, especially Google reviews. This research conducted case studies on Dealer Daya Adicipta Motora Bandung, Dealer Bintang Niaga Jaya Bogor, and Dealer Murni Motor II Bogor.

Using Importance Performance Analysis (IPA) will recommend aspects that must be prioritized to improve. The first step is to identify the customer’s needs from Google reviews using non-negative matrix factorization (NMF) that produces matrix H and matrix W as the keywords for every aspect. Then, this research also calculates the sentiment for each review using a dependency tree and lexicon SenticNet5. With the output from NMF and sentiment, we will calculate the performance and importance levels. Ultimately, the Performance Level and Importance Level will be plotted into the graph and divided into four quadrants, with Quandrant A as the top priority for improvement. Eight aspects identified in Dealer Daya Adicipta Motora Bandung, the waiting room facility become the priority of improvement. Dealer Bintang Niaga Jaya Bogor has 7 aspects identified, and the services and buying experience become the top priority of improvement; meanwhile, there are 4 aspects identified in Dealer Murni Motor II Bogor, with the waiting time and waiting room facility become the top priority for improvement.

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Keywords :

Dependency tree, Importance Performance Analysis, Motorcycles Honda, Sentiment analysis, Text mining

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