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All Journal JURNAL NASIONAL TEKNIK ELEKTRO Logic : Jurnal Rancang Bangun Dan Teknologi
Lindawati
Politeknik Negeri Sriwijaya
Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Journal : Logic : Jurnal Rancang Bangun Dan Teknologi

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Design and Construction of Crop Suitability Prediction System Using Fuzzy Logic Classifier Method Meli Gustina; Irma Salamah; Lindawati
Logic : Jurnal Rancang Bangun dan Teknologi Vol. 21 No. 3 (2021): November
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2494.415 KB) | DOI: 10.31940/logic.v21i3.139-148

Abstract

The potential of land in Indonesia which is quite large and has not been used optimally is one of the problems. this study focused on developing fuzzy logic models to predict plants that are suitable for planting on agricultural land to enable the land use more optimal. In conducting this study, there were two stages of implementation, namely hardware design, and software design which included system workflow design using the Fuzzy Logic Classifier method where three input variables were used, namely soil pH, soil temperature, and humidity. The findings of this study are in the form of predictions consisting of eight outputs, namely Unfavorable Land, Spinach, Cayenne Pepper, Beans, Long Beans, Cucumber, Eggplant, and Tomatoo. The prediction results generated were directly displayed on the LCD of the instrument that has been designed.
Design & Build Banknote Nominal Identification Tools for Visual Impairment Using Convolutional Neural Network Algorithm and Tensorflow with Android Based Selvia Rossa; Lindawati; Suzanzefi
Logic : Jurnal Rancang Bangun dan Teknologi Vol. 22 No. 3 (2022): November
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2559.096 KB) | DOI: 10.31940/logic.v22i3.244-252

Abstract

The buying and selling transactions that we usually do in our daily lives are difficult for people with visual impairment because it is difficult to distinguish the denomination of rupiah banknotes because of the limitation of sight, so it becomes one of the problems. This research focused on making a voice-based rupiah banknote nominal detection tool, using convolutional neural network algorithms in machine learning as the core of this system. This tool was also equipped with a voice-based android application to monitor the remaining money used when making buying and selling transactions-testing the tool used real test data of 20 images per class, producing an accuracy of 83%, as evidenced by Confusion matrix calculations.
Co-Authors Irma Salamah Meli Gustina Michelle Valerie Selvia Rossa Suzanzefi