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All Journal Jurnal Edukasi Elektro CogITo Smart Journal APTEK Jurnal Surya Teknika Jurnal Teknik Mesin, Industri, Elektro dan Informatika Jurnal Penelitian Rumpun Ilmu Teknik
Dila Marta Putri
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Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Pengembangan Sensor Elektrokimia Berbasis Material Nano untuk Deteksi Ion Timbal (Pb²⁺) Menggunakan Sistem Elektronika Terintegrasi Rahmawati, Asde; Nurjanah, Siti; Fahrizal, Fahrizal; Marta Putri, Dila; Ikhsan, M; Wajhi Akramunnas, Bastul
JURNAL SURYA TEKNIKA Vol. 12 No. 1 (2025): JURNAL SURYA TEKNIKA
Publisher : Fakultas Teknik UMRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jst.v12i1.9544

Abstract

Electrochemical sensors are a reliable method for detecting the presence of heavy metal ions such as lead (Pb²⁺) in aquatic environments. In this study, a sensor was developed based on a carbon paste electrode modified with ZnO nanomaterials and polyaniline, and integrated with a data acquisition system using a microcontroller. Voltammetric characterization results showed that the sensor could detect Pb²⁺ with high sensitivity at low concentrations. This system is expected to be applied for real-time and portable water quality monitoring.
A Machine Learning-Based Ambiguous Alphabet Recognition for Indonesian Sign Language System (SIBI) Purbolingga, Yoan; Ridwan, Ahmad; Putri, Dila Marta
CogITo Smart Journal Vol. 11 No. 1 (2025): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v11i1.816.1-14

Abstract

One of the communication problems in deaf people is the inhibition of verbal communication. This is due to the limited hearing function which has an impact on the imperfection of language sound reception. To communicate with deaf people, extraordinary communication is needed so that the meaning of the conversation can be conveyed properly. Sign language is the main communication medium for deaf people. However, in the use of sign language, there are ambiguous letters, namely “D “,“E“,“M“,“N“,“R“, “S“, and “U“. This research uses the chain code method to identify and reconstruct the shape of hand gesture objects. Then, to solve the problem of ambiguity of alphabet letters, an artificial intelligence method, namely K-Nearest Neighbors (K-NN), is used. The sample used consists of 350 real-time images with variations in object recognition accuracy. Based on the research using chain code and K-NN classification method, it can be concluded that the recognition of ambiguous letters in sign language has 245 training data for K-NN which has 88.76% accuracy, and 105 test data with 90% accuracy. This test data is divided into seven letters: “D“, “E”, “M”, “R” and “U” at 100%, and “N” and “S” at 98.88%.
Co-Authors Ahmad Ridwan Akramunnas, Bastul Wajhi Asde Rahmawati Bastul Wajhi Akramunnas FAHRIZAL Fahrizal Fahrizal Fahrizal Fahrizal Fahrizal Fahrizal Lukman Hakim Nasution Lukman Hakim Nasution M Ikhsan M IKHSAN Putra, Nanda Okta Siti Nurjanah SITI NURJANAH Siti Nurjanah Wajhi Akramunnas, Bastul Yoan Purbolingga Zulfatri Aini