Ornamental plants are plants that have aesthetic value in terms of color, shape, and characteristics. Planting and maintaining ornamental plants has now become a hobby that housewives are interested in, especially in the Palaran subdistrict, East Kalimantan. Housewives take advantage of their free time to do quality and business value things and generate side income, one of which is farming. The ornamental plant business is an agribusiness business. Agribusiness is a business activity of cultivating agricultural products both on a narrow and wide scale. However, it is difficult to find a contractor, demotivating housewives in the ornamental plant business. This raises the need for technology that can provide information, bring together sellers and contractors in a practical way, with minimal costs, able to communicate and transact at any time. From these problems, an Android-based Mobile E-Commerce application was designed using the UX Interface by JJ method. Garrett. The application that has been designed is then tested for usability using a measuring tool for effectiveness, efficiency, and user satisfaction. The usability value obtained is 88.69%. This proves that the application designed has helped users in caring for ornamental plants and has created a desire to do ornamental plant business because they get relevant price recommendations and information on what plants are currently hot so that the collection of ornamental plants which can be of commercial value.

<p class="Abstrak">Obyek dinyatakan bergerak jika terjadi perubahan posisi dimensi disetiap <em>frame</em>. Pergerakan obyek menyebabkan obyek memiliki perbedaan bentuk pola disetiap <em>frame-</em>nya. <em>Frame</em> yang memiliki pola terbaik diantara <em>frame</em> lainnya disebut <em>frame</em> dominan. Penelitian ini bertujuan untuk menyeleksi <em>frame</em> dominan dari rangkaian <em>frame</em> dengan menerapkan metode K-means <em>clustering</em> untuk memperoleh <em>centroid</em> dominan (<em>centroid</em> dengan nilai tertinggi) yang digunakan sebagai dasar seleksi <em>frame</em> dominan. Dalam menyeleksi <em>frame</em> dominan terdapat 4 tahapan utama yaitu akuisisi data, penetapan pola obyek, ekstrasi ciri dan seleksi. Data yang digunakan berupa data video yang kemudian dilakukan proses penetapan pola obyek menggunakan operasi pengolahan citra digital, dengan hasil proses berupa pola obyek RGB yang kemudian dilakukan ekstraksi ciri berbasis NTSC dengan menggunakan metode statistik orde pertama yaitu <em>Mean</em>. Data hasil ekstraksi ciri berjumlah 93 data <em>frame</em> yang selanjutnya dikelompokkan menjadi 3 <em>cluster</em> menggunakan metode K-Means. Dari hasil <em>clustering</em>, <em>centroid</em> dominan terletak pada <em>cluster</em> 3 dengan nilai <em>centroid</em> 0.0177 dan terdiri dari 41 data <em>frame</em>. Selanjutnya diukur jarak kedekatan seluruh data <em>cluster</em> 3 terhadap <em>centroid</em>, data yang memiliki jarak terdekat dengan <em>centroid</em> itulah <em>frame</em> dominan. Hasil seleksi <em>frame</em> dominan ditunjukkan pada jarak antar <em>centroid</em> dengan anggota <em>cluster</em>, dimana dari seluruh 41 data frame tiga jarak terbaik diperoleh adalah 0.0008 dan dua jarak bernilai  0.0010 yang dimiliki oleh <em>frame</em> ke-59, ke-36 dan ke-35.</p><p class="Abstrak"> </p><p class="Abstrak"><em><strong>Abstract</strong></em></p><p class="Abstract"><em>The object is declared moving if there is a change in the position of the dimensions in each frame. The movement of an object causes the object to have different shapes in each frame. The frame that has the best pattern among other frames is called the dominant frame. This study aims to select the dominant frame from the frame set by applying the K-means clustering method to obtain the dominant centroid (the highest value centroid) which is used as the basis for the selection of dominant frames. In selecting dominant frames, there are 4 main stages, namely data acquisition, determination of object patterns, feature extraction and selection. The data used in the form of video data which is then carried out the process of determining the pattern of objects using digital image processing operations, with the results of the process in the form of an RGB object pattern which is then performed NTSC-based feature extraction using the first-order statistical method, Mean. The data from feature extraction are 93 data frames which are then grouped into 3 clusters using the K-Means method. From the results of clustering, the dominant centroid is located in cluster 3 with a centroid value of 0.0177 and consists of 41 data frames. Furthermore, the proximity of all data cluster 3 to the centroid is measured, the data having the closest distance to the centroid is the dominant frame. The results of dominant frame selection are shown in the distance between centroids and cluster members, where from all 41 data frames the three best distances obtained are 0.0008, 0.0010, and 0.0010 owned by 59th, 36th and 35th frames.</em></p><p class="Abstrak"><em><strong><br /></strong></em></p><p> </p>