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Journal : Building of Informatics, Technology and Science

Implementasi Metode Linear Discriminant Analysis (LDA) Pada Klasifikasi Tingkat Kematangan Buah Nanas Destriana, Rachmat; Nurnaningsih, Desi; Alamsyah, Dedy; Sinlae, Alfry Aristo Jansen
Building of Informatics, Technology and Science (BITS) Vol 3 No 1 (2021): June 2021
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (588.903 KB) | DOI: 10.47065/bits.v3i1.1007

Abstract

Pineapple is a fruit commodity that is Indonesia's flagship. This is because pineapple is a fruit that has the highest export volume in Indonesia. To obtain pineapples with perfect ripeness, generally manually selected, this becomes inefficient if large numbers of pineapples are selected. So, in this study, an image processing system will be developed that can classify pineapple ripeness based on its image. In this study, the color feature extraction used is feature extraction based on hue and saturation values. Color feature extraction with hue and saturation is used to obtain various information from the colors in the image so as to facilitate the identification process. Furthermore, Linear Discriminator Analysis will obtain optimal projections to be able to enter spaces with smaller dimensions by performing pattern recognition that can be separated so that they can be grouped based on boundary lines obtained from linear equations. Based on the results of the accuracy test, the accuracy rate reaches 83%, it is in the good category
Penerapan Metode Pengembangan Sistem Extreme Programing (XP) Pada Aplikasi Presensi Karyawan dengan QR Code Fazrin, Qubaila Ega; Lisnawati, Tuti; Nurhayati, Sri; Satya, Juli Budi; Alamsyah, Dedy
Building of Informatics, Technology and Science (BITS) Vol 3 No 3 (2021): December 2021
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (510.658 KB) | DOI: 10.47065/bits.v3i3.1018

Abstract

Attendance is the process of recording and managing attendance data that is carried out daily during working hours at each company. Errors in recording employee attendance greatly affect employee earnings. So, the validity of the recording is needed. The attendance recording system manually is error-prone and its recapitulation takes a long time. To overcome this, it is necessary to develop an attendance system that can be done quickly and produce valid reports regarding the time of entry and exit. In this study, a presence application will be developed using QR Code scanning by applying the Extreme Programming (XP) method. The extreme programming (XP) method offers stages in a relatively short time. Based on black box testing, the generated QR Code presence application is in accordance with user needs with a functionality test value of 100%
Identifikasi Citra Tanaman Obat Jenis Rimpang dengan Euclidean Distance Berdasarkan Ciri Bentuk dan Tekstur Nurnaningsih, Desi; Alamsyah, Dedy; Herdiansah, Arief; Sinlae, Alfry Aristo Jansen
Building of Informatics, Technology and Science (BITS) Vol 3 No 3 (2021): December 2021
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (427.459 KB) | DOI: 10.47065/bits.v3i3.1019

Abstract

In the midst of the Covid-19 pandemic, increasing the body's immunity is very important. Some experts suggest consuming medicinal plants or herbs to boost immunity. In addition to being used as a cooking spice, this rhizome type plant turns out to have properties and benefits for health, especially to increase immunity. However, many people do not know and it is difficult to distinguish the type of rhizome plant. This type of rhizome plant can be identified based on the characteristics seen from the shape and texture. However, most people judge the type of rhizome has a shape that is difficult to distinguish. This study aims to determine the type of medicinal plant rhizome with Euclidean distance and extraction of shape and texture. Extraction of shape features using metric and eccentricity parameters. This parameter is considered to be able to recognize shape objects and can distinguish them from other objects. Meanwhile, texture feature extraction uses Gray Level Co-occurence Matrix (GLCM) with contrast, correlation, energy, and homogeneity parameters. For the identification process, Euclidean distance is used which serves to represent the level of two images that consider the distance value from Euclidean. From the results of the evaluation using a confusion matrix by calculating precision, recall and accuracy, it gets a precision value of 83%, recal 87% and an accuracy of 85%. These results indicate that the Euclidean distance and extraction of shape and texture features can identify the object image of medicinal plants with rhizome types well