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

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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.
Innovative Personal Assistance: Speech Recognition and NLP-Driven Robot Prototype Michelle Valerie; Irma Salamah; Lindawati
JURNAL NASIONAL TEKNIK ELEKTRO Vol 12, No 2: July 2023
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v12n2.1105.2023

Abstract

This paper presents the development and evaluation of a personal assistant robot prototype with advanced speech recognition and natural language processing (NLP) capabilities. Powered by a Raspberry Pi microprocessor, it is the core component of the robot's hardware. It is designed to receive commands and promptly respond by performing the requested actions, utilizing integrated speech recognition and NLP technologies. The prototype aims to enhance meeting efficiency and productivity through audio-to-text conversion and high-quality image capture. Results show excellent performance, with accuracy rates of 100% in Indonesian and 99% in English. The efficient processing speed, averaging 9.07 seconds per minute in Indonesian and 15.3 seconds per minute in English, further enhances the robot's functionality. Additionally, integrating a high-resolution webcam enables high-quality image capture at 1280 x 720 pixels. Real-time integration with Google Drive ensures secure storage and seamless data management. The findings highlight the prototype's effectiveness in facilitating smooth interactions and effective communication, leveraging NLP for intelligent language understanding. Integrating NLP-based speech recognition, visual documentation, and data transfer provides a comprehensive platform for managing audio, text, and image data. The personal assistant robot prototype presented in this research represents a significant advancement in human-robot interaction, particularly in meeting and collaborative work settings. Further refinements in NLP can enhance efficiency and foster seamless human-robot interaction experiences.
Implementasi dan Perbandingan Performa Algoritma Fuzzy Tsukamoto dan Mamdani pada Sistem Exhaust Fan Berbasis IoT Nadia Putri; Lindawati; Aryanti
Tech-E Vol. 8 No. 1 (2024): The Tech-E Journal Vol. 8 No. 1 publishes research papers in such informatics:
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v8i1.3169

Abstract

Dalam produksi kerupuk, proses penggorengan sering menghasilkan asap dan panas berlebih yang dapat berdampak buruk pada kesehatan pekerja. Asap dapur mengandung senyawa berbahaya seperti sulfur oksida, nitrogen dioksida, dan karbon monoksida. Diperlukan kipas pembuangan untuk mengeluarkan asap dan menstabilkan suhu, namun kontrol manual kurang efektif. Sistem kontrol otomatis, termasuk mikrokontroler, set points, PID, dan logika fuzzy, telah dikembangkan. Kontrol berbasis fuzzy dianggap paling baik untuk beradaptasi dengan kondisi lingkungan. Penelitian ini mengevaluasi perbedaan antara metode fuzzy Mamdani dan fuzzy Tsukamoto dalam mengontrol kipas pembuangan. Pengujian dilakukan dengan 100 titik data selama 5 kali percobaan untuk masing-masing metode. Hasil penelitian menunjukkan bahwa metode logika fuzzy Tsukamoto mencapai akurasi lebih baik yaitu 99,35%, dibandingkan dengan logika fuzzy Mamdani yang hanya mencapai 95,45%. Oleh karena itu, sistem kontrol kipas pembuangan lebih efektif menggunakan metode logika fuzzy Tsukamoto. Metode fuzzy Tsukamoto memberikan respon yang lebih cepat dan tepat dalam menyesuaikan kecepatan kipas terhadap perubahan kondisi asap dan suhu di dapur. Hal ini dikarenakan metode Tsukamoto mampu menangani perubahan input yang lebih kompleks dan menghasilkan output yang lebih halus. Di sisi lain, metode fuzzy Mamdani memiliki kelebihan dalam hal kesederhanaan dan kemudahan implementasi, namun kurang responsif terhadap perubahan kondisi yang cepat.
Co-Authors Aryanti Irma Salamah Meli Gustina Michelle Valerie Nadia Putri Selvia Rossa Suzanzefi