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All Journal Teika Generation Journal
Wahyu Hidayat, Eka
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Languange, Linguistic, Communication & Media

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Analisis Usability Aplikasi LegoBoost Builder Dengan Metode System Usability Scale Henanda, Yestrada; Wahyu Hidayat, Eka; Putra Aldya, Aldy
TeIKa Vol 14 No 1 (2024): TeIKa: April 2024
Publisher : Fakultas Teknologi Informasi - Universitas Advent Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36342/teika.v14i1.3249

Abstract

The objective of this research is to evaluate and analyze the usability of the LegoBoost Builder application by employing the System Usability Scale (SUS) method. The LegoBoost Builder application is an in-house developed product by Lego Corporation, featuring animations of robot models that can be assembled using Lego kits. The application is intended for user as an interactive learning tool for animation and robotics. The selection of the System Usability Scale (SUS) method is considered an appropriate and significant evaluation approach to measure the usability of the application. Based on the conducted tests, the LegoBoost Builder application obtained an average of 70.52, categorizing it as GOOD with grade scale C. This score indicates that users find the application useful and beneficial in the educational context. In other words, the LegoBoost Builder application has fulfilled the needs and goals of users in supporting the learning process of animation and robotics.
Classification of Guava Fruit Types Using Principal Component Analysis and K-Nearest Neighbor Algorithms Andrean Nugraha, Rezky; Wahyu Hidayat, Eka; Nur Shofa, Rahmi; Eka Wahyu Hidayat, S.T., M.T.; Rahmi Nur Shofa, S.T., M.T.
Generation Journal Vol 7 No 1 (2023): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/gj.v7i1.17900

Abstract

The maturity level of guava fruit can be determined by looking at various factors. Shape is one of the factors that play a role in identifying certain objects. The classification of guava fruit can be seen from the shape, texture and color. The shape of the guava fruit is quite diverse ranging from round (Round shape) to oval (Pear shape). So a Matlab application was built to determine the type of guava based on its color, shape and texture. K-Nearest Neighbor can classify objects based on learning data that is closest to the object so that the results can be more accurate. Principal Component Analysis (PCA) is a statistical technique for simplifying many-dimensional data sets into lower dimensions (extration features). The combination of K-Nearest Neighbor with Principal Component Analysis produces a fairly high accuracy for determining the type of guava using a total of 45 images and divided into two data including training data with a total of 36 guava data and test data with a total of 9 guava data.
Co-Authors Andrean Nugraha, Rezky Eka Wahyu Hidayat, S.T., M.T. Henanda, Yestrada Nur Shofa, Rahmi Putra Aldya, Aldy Rahmi Nur Shofa, S.T., M.T.