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PENERAPAN METODE MULTIMEDIA DEVELOPMENT LIFE CYCLE (MDLC) PADA A MAGICAL AUGMENTED REALITY BOOK BERBASIS ANDROID Agus Kurniasari, Arvita; Trismayanti Dwi Puspitasari; Argista Dwi Septya Mutiara
Antivirus : Jurnal Ilmiah Teknik Informatika Vol 17 No 1 (2023): Mei 2023
Publisher : Universitas Islam Balitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35457/antivirus.v17i1.2801

Abstract

The development of Information and Communication Technology is currently very rapid, so it is either used or utilized in the world of education, which has a positive impact. On the other hand, technology can also hurt children under 6 years of age who are still in developmental stages, such as being lazy to move and not interacting with the outside world, so the desire to learn at school and home will decrease. One example of good learning media for children is Augmented Reality (AR) technology. AR is a technology that combines two-dimensional and or three-dimensional virtual objects into a real three-dimensional environment and then projects these virtual objects in real-time. This AR technology can insert certain information into the virtual world and display it in the real world. AR technology helps to create a moving 3D object. This is the background for making applications that help introduce technology into books with the theme of Suro and Boyo folklore which can be used as learning tools and an introduction to the origins of regions in Indonesia. The Multimedia Development Life Cycle (MDLC) method was implemented in this application. The main target of this application is Kindergarten-aged children, which has been implemented to determine the application acceptance rate of 70%.
Geographic Information System Mapping of Plantation Pramuditha Shinta Dewi Puspitasari; Agus Kurniasari, Arvita; Trismayanti Dwi Puspitasari
Journal of Applied Science, Engineering, Technology, and Education Vol. 4 No. 2 (2022)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1178.954 KB) | DOI: 10.35877/454RI.asci1162

Abstract

Perusahaan Daerah Perkebunan (PDP) Kahyangan is a Regional Owned Enterprise in Jember Regency which was formed to realize the prosperity of the community. In Regional Regulation Number 2 of 2012-chapter 3 clauses 2, the government can manage regional finances by exploring sources of Regional Original Income, one of which is from the PDP. In addition, the purpose of the establishment of the PDP is as a means of developing the economy in the context of regional development by increasing productivity from all aspects to increase regional income. The main commodities are coffee and rubber, cloves, Mahoni, and Sengon wood are supporting commodities. Based on interviews PDP's profit contribution to Jember's income has continued to decline in recent years due to the absence of good management of its potential. So, this research will manage a system that can assist in obtaining information about the distribution of plantation land commodities in Jember, as well as mapping existing commodities by Geographic Information System (GIS). The method for developing GIS uses a Design Sprint. The output of this method prototypes and will implement in the GIS application.
Content-Dependent Image Search System with Automatic Weighting Mechanism for Aggregating Color, Shape, and Texture Features Agus Kurniasari, Arvita; Ali Ridho Barakbah; Achmad Basuki
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 10 No 1 (2024): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v10i1.3501

Abstract

The existing image search system extracts features from the database images and performs queries thoroughly without considering the weight of each feature. Currently, all features are assigned the same weight, even though each image has different characteristics. This study proposes a new approach to image search systems that relies on content with automatic weighting. The automatic weighting process starts by calculating each moment. The first moment is obtained from the color matrix and is calculated as the average value. The second moment is obtained from the texture matrix and is calculated as the variance value. The third moment is obtained from the shape matrix and is calculated as the skewness value. These three moments are normalized to give the same weight to each feature for each picture. The results obtained for accuracy were: 70.38% for color, 60.99% for shape, 71.21% for texture, 72.65% for color-shape combinations, 78.43% for color-texture combinations, 72.65% for texture-shape combinations, and 80.5% for overall texture-color-shape features.