The background of what this report discussed is the problem on the food menu due to the unsold food menu causes that make the restaurant loose their money because of the unused food menu. In this case K-Means can be used to cluster consumer interest where the interest will be adjusted with the season. K-Means algorithm will be used in software to find consumer interest from existing sales data, in this case can be said as data mining where the data will be made and sorted by customer’s interest like summer or rainy season. The determination of these problems based on the season due to consumer interest that will be more easily to calculated when we following the season in Indonesia where Indonesia itself is a tropical country which has a diverse diet. With the grouping of data from sales data restaurant can determine the menu of food and beverages in accordance with consumer interest where the menu will be adjusted to the season in Indonesia that is summer and rainy season. And the results of data processing will be implemented on online reservation software and food reservations previously made in previous research entitled Online Food Place and Food Packages In Food Garden Miko Mall. This is intended to facilitate the restaurant to determining in the purchase settings of feed ingredients. If there is a lot of menus sold then raw materials will be reproduced and if there is a food menu that is less enthusiastic or the sale is spelled out less then the raw material will be reduced.