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All Journal CogITo Smart Journal Jurnal Nasional Komputasi dan Teknologi Informasi APTEK Jurnal Teknik Industri Terintegrasi (JUTIN) Jurnal Surya Teknika Journal of Computer Networks, Architecture and High Performance Computing CHIPSET (Journal on Computer Hardware, Signal Processing, Embedded System and Networking) Jurnal Penelitian Rumpun Ilmu Teknik Innovative: Journal Of Social Science Research
Yoan Purbolingga
Universitas Andalas
Aerospace Engineering Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Neuroscience Public Health Transportation Other

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Comparison of MDKA Stock Price Prediction using Multi-Layer Perceptron, Long Short-Term Memory, and Gated Recurrent Unit Wajhi Akramunnas, Bastul; Hakim, Legisnal; Marta Putri, Dita; Fahrizal, Fahrizal; Rahmawati, Asde; Purbolingga, Yoan
JURNAL SURYA TEKNIKA Vol. 10 No. 1 (2023): JURNAL SURYA TEKNIKA
Publisher : Fakultas Teknik UMRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jst.v10i1.5004

Abstract

Shares are rights owned by a person against a company due to the delivery of capital, either in part or in whole. Investors invest in stocks and try to get maximum results, but many investors are still unsure about the risks involved in investing. To minimize risk, investors need to predict stock prices with an accurate method. Several methods that can be implemented to predict stock data include Multi-Layer Perceptron (MLP), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). The research objective to be achieved in this study is to compare the performance of each algorithm in producing a more accurate stock price forecasting model by testing neurons (10, 20, 30) and epochs (50, 75, 100). The research was conducted on the stock price data of PT. Merdeka Copper Gold Tbk (MDKA) which is a mining sector share with the largest capitalization value. Tests on some of the algorithms above got the best results using 82% training data and 18% test data, namely the MLP model with 10 neurons and 100 epochs with a MAPE training data result of 2.325 and a MAPE test data of 2.014. Based on the test results, MLP can predict MDKA stock prices for the 2018-2022 period with good performance and a relatively small error rate, while tests using the LSTM and GRU methods still produce large errors. Thus, it can be concluded that MLP can predict stock prices with more accurate results.
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%.
Animal Protection System Cats and Dogs Approaching The Substance With The Mini Computer Aulia Ramadhani, Shafira; Anandika, Arrya; Syahputra, Ronaldo; Purbolingga, Yoan
CHIPSET Vol. 6 No. 01 (2025): Journal on Computer Hardware, Signal Processing, Embedded System and Networkin
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/chipset.6.01.18-29.2025

Abstract

Litter bins that do not have lids, as well as the time span of garbage collection, especially when garbage is accumulating, can attract animals to enter the bin, some of the animal patterns are to carry garbage out of the bin, so that it can be consumed by dogs/cats. The purpose of this problem is to help the community in preventing and minimizing animals that litter and prevent the spread of diseases in animals due to consuming garbage, for example diseases caused by bacteria from garbage, namely rabies. This final project results in the detection of cats and dogs using YOLO with 90% accuracy, when a cat or dog is detected the system will issue an output so that the animal does not get closer and out of the trash, the output will continue to be issued until the animal is no longer detected by the camera.
Parameter Control System of Aeroponic Method on Plants Based on Internet of Things (IoT) Zahran, Dzaki; Yolanda, Desta; Purbolingga, Yoan
CHIPSET Vol. 6 No. 02 (2025): Journal on Computer Hardware, Signal Processing, Embedded System and Networkin
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/chipset.6.02.186-194.2025

Abstract

The Internet of Things (IoT)-based Aeroponic System is an innovation in the cultivation of crops, especially potatoes, on limited land. This research aims to design an aeroponic parameter control system that integrates real-time measurement of temperature, humidity, and pH to improve the efficiency and productivity of urban agriculture. The system uses the ESP32 as the main data processor, with a DHT11 sensor for temperature and humidity measurements, as well as a pH sensor for nutrient regulation. Automation is carried out through relays and control modules connected to the Blynk app for remote monitoring and control. Tests show that this system is able to maintain the stability of the growing environment with an average parameter error of less than 5%. The system offers sustainable solutions for urban agriculture, reducing water consumption, and overcoming the limitations of narrow land.
Design Of A Portable Mini Pump It Up System Based On Mini Computer For Children's Gross Motor Improvement Prima, Lucky; Anandika, Arrya; Purbolingga, Yoan; Syahputra, Ronaldo
CHIPSET Vol. 5 No. 02 (2024): Journal on Computer Hardware, Signal Processing, Embedded System and Networkin
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/chipset.5.02.126-131.2024

Abstract

The increasing influence of smartphones on young children has raised concerns about the delayed development of gross motor skills, particularly in early childhood. This issue is significant in Indonesia, which ranks fifth in ASEAN for birth rates, resulting in a large population of children at risk. Excessive smartphone use by children leads to decreased physical activity, potentially causing health problems such as obesity and reduced physical fitness. The objective of this study is to design and develop a portable system, called the "Mini Pump It Up," based on a mini-computer (Raspberry Pi 5), that encourages children to engage in more physical activities. This device is intended to divert children from excessive smartphone usage, thereby stimulating their gross motor skills development. Additionally, the system is designed to be used anywhere without requiring an external power source. The research concludes that the system successfully operates in portable mode without the need for a power supply, sustaining functionality for 3 hours, 10 minutes, and 15 seconds. Furthermore, the system effectively captures the interest of children, as evidenced by 84.21% of the 19 children participants choosing to interact with the product instead of engaging with smartphones.
Penerapan Metode SDLC dalam Rancang Bangun Sistem Informasi Koperasi UED-SP Berbasis Website Rahmayani, Mentari Tri Indah; Andriani, Fitri; Utami, Dini; Purbolingga, Yoan
Innovative: Journal Of Social Science Research Vol. 4 No. 3 (2024): Innovative: Journal Of Social Science Research (Special Issue)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i3.12413

Abstract

Usaha Ekonomi Desa Simpan Pinjam (UED-SP) adalah suatu lembaga yang bergerak di bidang simpan pinjam dan merupakan milik Masyarakat desa/kelurahan yang diusahakan serta dikelola oleh masyarakan desa/kelurahan. Dengan adanya lembaga ini, Masyarakat desa bisa mengajukan pinjaman uang untuk tujuan tertentu. Seiring dengan perkembangan zaman, hal ini dapat memudahkan masyarakat dengan pemanfaatan teknologi Informasi dan Komunikasi (TIK). Metode yang digunakan yaitu metode SDLC merupakan salah satu metode pengembangan system informasi yang mengembangkan suatu sistem agar dapat menghasilkan output sistem berkualitas tinggi yang memenuhi ekspektasi user. Pengumpulan data dilakukan dengan menggunakan metode observasi dan wawancara terkait perkembangan pengoperasian UED-SP Desa Api-Api. Dengan dibentuknya perancangan sistem informasi ini, penulis berharap dapat membantu dalam memudahkan masyarakat dan meningkatkan kualitas pelayanan UED-SP Desa Api-Api.
Co-Authors Ahmad Ridwan Ahmad Ridwan Anandika, Arrya Asde Rahmawati Aulia Ramadhani, Shafira Bastul Wajhi Akramunnas Desi Ratna Sari Dila Marta Putri Dini Utami FAHRIZAL Fahrizal Fahrizal Fahrizal Fahrizal Fahrizal Fahrizal Fitri Andriani, Fitri Hanisah Hanisah Hanisah, Hanisah Legisnal Hakim Lukman Hakim Nasution Lukman Hakim Nasution Marta Putri, Dita Mentari Tri Indah Rahmayani Nurhayati Nurhayati Prima, Lucky Rahmawati, Asde Rahmayani, Mentari Tri Indah Restu Dian Saputri Siti Nurjanah Syahputra, Ronaldo Wajhi Akramunnas, Bastul Yolanda, Desta Zahran, Dzaki