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Menampilkan 1–10 dari 19 artikel
Penerapan Jaringan Saraf Tiruan dengan Metode Backpropagation untuk Memprediksi Curah Hujan di Kota Medan
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Vol 4
, No 1
(2026)
Rainfall is a crucial factor in the stability of the Earth's ecosystem and has a significant impact on agriculture, forestry, energy, and water management. However, increasingly unstable climate change makes rainfall patterns difficult to predict accurately using traditional methods. The city of Medan, the capital of North Sumatra Province, has a tropical rainforest climate with an average annual rainfall of approximately ±2200 mm and an average temperature of 27°C. Significant weather fluctuati...
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Implementasi Jaringan Syaraf Tiruan dalam Peramalan Harga Cpo Menggunakan Backpropagation
Saturnus: Jurnal Teknologi dan Sistem Informasi
Vol 4
, No 1
(2026)
This study examines the development of a Crude Palm Oil (CPO) price forecasting model using an artificial neural network algorithm, specifically the backpropagation algorithm. As one of Indonesia’s main export commodities, CPO has a significant economic impact and influences the income of oil palm farmers. The CPO price data used in this study were obtained from CIF Rotterdam, covering the period from January 2019 to December 2023. The research methodology consists of several stages, including d...
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Penerapan Jaringan Saraf Buatan untuk Pengenalan Pola Tanda Tangan dalam Identifikasi Potensial Diri Menggunakan Metode Backpropagation
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Vol 4
, No 1
(2026)
This study develops a computational-based system to identify individual potential through the analysis of signature patterns using Artificial Neural Networks (ANN) and the Backpropagation algorithm. The research aims to explore and examine the effectiveness of applying ANN in recognizing and identifying signature patterns that are assumed to be related to an individual’s potential. In the data processing stage, Principal Component Analysis (PCA) is employed as a dimensionality reduction and feat...
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Penggunaan Transfer Learning untuk Peningkatan Akurasi Deteksi Penyakit Tanaman Bunga
Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika
Vol 3
, No 4
(2025)
Flower disease detection is a common challenge in modern agriculture. Various factors, such as changes in leaf color, shape, petal structure, and environmental conditions, make it difficult to achieve high accuracy with conventional models. Transfer learning is an effective solution to improve model performance in image detection, especially when available data is limited. This study used several pre-trained models, namely VGG16, ResNet50, and EfficientNet-B0, to detect three types of flower dis...
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Implementasi Algoritma Jaringan Syaraf Tiruan Backpropagation untuk Prediksi Penyakit Diabetes
Mars: Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer
Vol 3
, No 6
(2025)
Diabetes Mellitus is a chronic disease that requires early detection to prevent serious complications. This study aims to implement the Artificial Neural Network (ANN) algorithm with the Backpropagation method to predict the risk of diabetes. The dataset used is the Pima Indians Diabetes Dataset, consisting of 768 medical records with 8 feature attributes. This study employs the Multi-Layer Perceptron method with an architecture of 8 input neurons, two hidden layers, and 1 output neuron. Model e...
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Penggunaan Transfer Learning Untuk Peningkatan Akurasi Deteksi Penyakit Tanaman Bunga
Mars: Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer
Vol 3
, No 6
(2025)
Flower disease detection is a significant challenge in modern agriculture, particularly with factors such as changes in leaf color, petal shape and structure, and environmental conditions affecting the accuracy of conventional models. These factors make it difficult to achieve optimal results using traditional methods. Transfer learning is an effective solution to improve image detection performance, especially when data is limited. This study used several pre-trained models, namely VGG16, ResNe...
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Perancangan dan Analisis Kinerja Sistem Penghitung Lalu Lintas Otomatis Berbasis YOLOv8
Mars: Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer
Vol 3
, No 6
(2025)
Traffic congestion is a persistent challenge in urban areas in Indonesia, where increasing vehicle density creates the need for intelligent traffic monitoring systems. This study aims to develop a real-time vehicle parking system using the YOLOv8 object detection model to provide efficient traffic analysis from live CCTV broadcasts and recorded videos. This study uses a quantitative experimental approach with the implementation of the YOLOv8m model using the Ultralytics library in Python, tested...
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Analisis Pola Tanda Tangan untuk Identifikasi Kepribadian Diri Menggunakan Jaringan Syaraf Tiruan Backpropagation Berbasis Citra Digital
Mars: Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer
Vol 3
, No 6
(2025)
This study discusses the introduction of digital signature patterns using the Backpropagation method on Artificial Neural Network (JST) to identify a person's characteristics and potential. The increasing use of digital identities demands a verification system that is more secure, accurate, and adaptive to the variations of each individual's signature. The main problem faced in the signature recognition system is the low level of accuracy when the visual features of the signature have similariti...
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Implementasi Jaringan Syaraf Tiruan Backpropagation pada Klasifikasi Jenis Kopi Berdasarkan Cita Rasa dan Aroma
Mimi Sartika Ritonga
; Lailan Sofinah
; Saiba Siregar
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Vol 3
, No 4
(2025)
Coffe is one of Indonesia’s leading commodities, known for its diverse flavors and aromas. Traditionally, coffee quality assessment is conducted manually through cupping tests performed by expert panelists. However, this method is subjective and requires considerable time and cost. This study aims to implement an Artificial Neural Network (ANN) using the backpropagation algorithm to classify coffee types based on sensory parameters such as flavor, aroma, acidity level, and body. Simulated data w...
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Pengenalan Objek pada Citra Digital Menggunakan Metode Template Matching
Mars: Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer
Vol 3
, No 3
(2025)
Object detection in digital images is a crucial aspect of image processing and computer vision, with applications ranging from surveillance systems and robotics to image-based search. One commonly used approach is template matching, a technique that compares a template image with sections of the target image to identify similar patterns. This study explores the implementation of the template matching method for object recognition in digital images. The process begins with image preprocessing to...
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