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All Journal Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Nuansa Informatika
Gunawan
STMIK Tegal
Computer Science & IT Control & Systems Engineering

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PENGENALAN MOTIF BATIK PESISIR PULAU JAWA MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK Bagus Untung Saputra; Gunawan; Wresti Andriani
NUANSA INFORMATIKA Vol. 17 No. 2 (2023): Volume 17 No 2 Tahun 2023
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v17i2.32

Abstract

Coastal Batik is made outside of Solo and Yogyakarta. The use of the term "coastal" is due to the majority of batik production being located in the northern coast of Java, such as Indramayu, Cirebon, Pekalongan, Lasem, and others. Coastal batik is characterized by flexible color selection and patterns, influenced by foreign influences, particularly after the introduction of Islam in the 16th century. The Convolutional Neural Network (CNN) method is commonly used in classifying digital image data. Neurons in CNN are represented in a two-dimensional form, differing in linear function and weight parameters. The CNN extraction process consists of hidden layers, including convolutional, pooling, and ReLU (activation function) layers. The evaluation results of the Convolutional Neural Network model show that it can perform classification and recognize coastal batik images of Java Island, achieving the best results in the first scenario with a training data ratio of 70% and testing data ratio of 30%, resulting in an accuracy of 83%. For future research, it is recommended to increase the number of batik images and capture them directly, while incorporating segmentation or extraction features to measure efficiency and accuracy levels. This will help obtain better results in recognizing the characteristics of coastal batik in Java Island.
Penerapan Metode Association Rule Dan Algoritma Apriori Untuk Analisis Pola Frekuensi Tinggi Prediksi Curah Hujan Di Kota Tegal Gunawan; Wresti Andriani; Fikri Zain Hidayatullah
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 11 No 2 (2023): TEKNOIF OKTOBER 2023
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21063/jtif.2023.V11.2.45-53

Abstract

Rainfall is a very important factor in daily life, especially in agriculture and water resources management. Accurate rainfall forecasts are essential to mitigate the impact of floods, droughts, and water shortages. This study aimed to predict rainfall in Tegal City using data on rainfall, temperature, humidity, and barometric pressure. Explore association rules to define relationships between elements to predict weather. Then, the data is processed using a priori algorithms to find patterns of relationships between variables in the data. The results showed that a priori algorithms can be used to find ways of association that can be used to predict rainfall in Tegal City. Based on the research results and discussions that have been carried out, it can be concluded that the Association Rule method using a priori algorithm can be applied quite well in rainfall forecasting simulations in Tegal City. Based on the analysis, it was found that some association rules have a lift ratio value greater than 1, thus indicating that these rules have a significant level of strength and can be relied upon as a guideline in forecasting rainfall in Tegal City. This method can help predict weather conditions and provide useful information for the public and authorities to decide on outdoor activities.
Co-Authors Bagus Untung Saputra Fikri Zain Hidayatullah Wresti Andriani Wresti Andriani