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Penerapan Jaringan Saraf Tiruan dengan Metode Backpropagation untuk Memprediksi Curah Hujan di Kota Medan
Tiara Bela Harahap
; Lailan Sofinah Harahap
; Naina Nazwa Hasibuan
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
Eva Andini
; Lailan Sofinah Harahap
; Siti Nurjanah
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
Ferdi Frans Dirga
; Lailan Sofinah Harahap
; Fiqih Syahputra
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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Perancangan dan Analisis Kinerja Sistem Penghitung Lalu Lintas Otomatis Berbasis YOLOv8
Dwiky Oldi Amsyah
; Lailan Sofinah Harahap
; Ahmad Fariz Fuady
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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Implementasi Algoritma Jaringan Syaraf Tiruan Backpropagation untuk Prediksi Penyakit Diabetes
Alwi Syahputra
; Lailan Sofinah Harahap
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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Analisis Pola Tanda Tangan untuk Identifikasi Kepribadian Diri Menggunakan Jaringan Syaraf Tiruan Backpropagation Berbasis Citra Digital
Muhammad Farhan
; Lailan Sofinah Harahap
; Rusma Riansyah
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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Pengenalan Objek pada Citra Digital Menggunakan Metode Template Matching
Tia Ramadani
; Lailan Sofinah Harahap
; Rika Khairani
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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Implementasi Jaringan Syaraf Tiruan untuk Menentukan Penutupan Kompetensi Keahlian SMK berdasarkan Minat Siswa
Alisya Alfina Rizki Ritonga
; Lailan Sofinah Harahap
; Cici Pratiwi
Saturnus: Jurnal Teknologi dan Sistem Informasi
Vol 3
, No 2
(2025)
The development of vocational education requires Vocational High Schools (SMK) to align their competencies with student interests and industry needs. However, a mismatch between student interests and the competencies offered can result in low enrollment, requiring schools to consider closing certain programs. This study proposes the application of Artificial Neural Networks (ANNs) as a predictive method to determine the potential closure of vocational competencies based on an analysis of student...
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Penerapan Jaringan Saraf Tiruan untuk Mengelolah Data Perubahan Cuaca sebagai Dasar Prediksi Kondisi Iklim
Winda Yunia Purnama
; Lailan Sofinah Harahap
; Nur Azizah Hidayat
Saturnus: Jurnal Teknologi dan Sistem Informasi
Vol 3
, No 1
(2025)
This study aims to analyze the application of Deep Neural Networks (DNN) as an artificial intelligence approach in processing weather data to support more accurate and stable climate predictions. Increasingly unpredictable and fluctuating weather patterns demand modern analytical methods capable of capturing non-linear relationships among atmospheric variables. DNN is utilized due to its ability to learn complex data structures through multilayer representations that extract deeper features from...
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Perancangan Model Jaringan Syaraf Tiruan untuk Memprediksi Penyakit Demam Berdarah Menggunakan Algoritma Hebb Rule
Adinda Tarisyah Hsb
; Mazayah Tsaqofah
; Lailan Sofinah Harahap
Mars: Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer
Vol 2
, No 6
(2024)
Dangeu dengue fever or what we often call dengue fever is a disease transmitted by the Aedes aegypti mosquito and caused by the dengue virus. This disease can potentially cause serious complications if it does not receive proper treatment. In this research, the author uses the application of artificial neural networks with the Hebb rule approach to predict the risk level of dengue fever. Predictions are made based on factors such as weather conditions, population density and historical case data...
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