Proceedings of the 1st International Conference on Neural Networks and Machine Learning 2022 (ICONNSMAL 2022)
23 articles
Proceedings Article
The Analysis of Airport Passengers Flow by Using Spatial Temporal Graph Neural Networks and Resolving Efficient Dominating Set
A. Muklisin, I. M. Tirta, Dafik, R. I. Baihaki, A. I. Kristiana
The advanced development of airport infrastructure is intended to improve airport services for air flight costumers. Thus, it is compulsory to maintain the sustainability system for service establishment. The purpose of this research is to apply the concept of Spatial Temporal Graph Neural Network (STGNN)...
Proceedings Article
Comparison of the Normalization Method of Data in Classifying Brain Tumors with the k-NN Algorithm
Rinci Kembang Hapsari, Abdullah Harits Salim, Budanis Dwi Meilani, Tutuk Indriyani, Aery Rachman
One way to examine patients with brain tumors is the radiological examination, including Magnetic Resonance Image (MRI) with contrast. The classification process is needed to differentiate MRI images of people with brain tumors from those without brain tumors. The classification was based on MRI image...
Proceedings Article
Classification of Tobacco Leaf Quality Using Feature Extraction of Gray Level Co-occurrence Matrix (GLCM) and K-Nearest Neighbor (K-NN)
Aeri Rachmad, Rinci Kembang Hapsari, Wahyudi Setiawan, Tutuk Indriyani, Eka Mala Sari Rochman, Budi Dwi Satoto
Tobacco is one of the largest agricultural products and is widely traded in the world market, including in Indonesia. In Indonesia, tobacco leaves are used as raw material for cigarettes which are mostly produced by cigarette companies. The quality of tobacco leaves greatly affects the quality of cigarettes,...
Proceedings Article
Steganography on Color Images Using Least Significant Bit (LSB) Method
Tutuk Indriyani, S. Nurmuslimah, Audita Taufiqurrahman, Rinci Kembang Hapsari, Citra Nurina Prabiantissa, Aeri Rachmad
In some fields, high data security is required for data transmission. This raises concerns about misuse of data to irresponsible parties. To protect it, efforts were made to hide factual information on top of other information, namely steganography using the Least Significant Bit (LSB) method. This method...
Proceedings Article
Haploid Diploid Maize Seeds Classification Using Residual Network
Wahyudi Setiawan, Yoga Dwitya Pramudita
Maize seed breeding is an important basis for getting better production. Maize seeds consist of two types: diploid and haploid. Haploid seed can accelerate maize breeding results in just two to three generations. In contrast to diploid (normal) which requires up to eight generations. In this article,...
Proceedings Article
Tourism Destination Recommendation System Using Collaborative Filtering and Modified Neural Network
Kurniawan Eka Permana, Sri Herawati, Wahyudi Setiawan
Tourism is one of the driving sectors of the national economy. Nowadays, the normal opening of tourist destinations after COVID-19 pandemic, tourist visits are currently increasing rapidly. Indonesia has a unique culture, nature, language, and cuisine. This is certainly a potential that can attract tourists...
Proceedings Article
Implementation of the Fuzzy Analytical Network Process Method in Decision Making on the Granting of Non-occupied Building Permits
Muhammad Ali Syakur, Eka Mala Sari Rochman, Aeri Rachmad, Wahyudi Setiawan, Sigit Susanto Putro
Building Permit (BP) is one of the authorities that can be given by local governments to people who will construct buildings, both residential and non-residential buildings. The requirements for applying for BP for residential buildings are different from those for non-residential buildings. The criteria...
Proceedings Article
Comparing the Architecture of Convolutional Neural Network for Corn Leaves Diseases Image Classification
Aeri Rachmad, Wahyudi Setiawan, Eka Mala Sari Rochman
This article discusses the comparison of the Convolutional Neural Net- work (CNN) architecture for image classification of corn leaves diseases. This study uses public data on from Plantvillages. The data be contained in four classes: gray leaf spot, common rust, leaf blight, and healthy. Each class...
Proceedings Article
The Classification of Tea Leaf Disease Using CNN Image Classifier
Eliana Aida Rosyidah, Alfian Futuhul Hadi, Yuliani Setia Dewi
Technological developments have encouraged advances in plant disease control. One plant disease that needs to be controlled quickly is tea leaf disease. Tea leaf diseases are numerous. In this study, we took 4 disease samples. Image recognition of tea leaf diseases with Convolutional Neural Networks...
Proceedings Article
Weight of Evidence and Information Value on Support Vector Machine Classifier
M Dika Saputra, Zahroatul Fitria, Bagus Sartono, Evi Ramadhani, Alfian Futuhul Hadi
In building a classification model, variables containing low predictive information are sometimes used. This can increase the bias on classification. Weight of Evidence (WoE) and Information Value (IV) provide a good theoretical foundation to explore, filtering, and transforming variables in binary classification....
Proceedings Article
The Comparison of Convolutional Neural Networks Architectures on Classification Potato Leaf Diseases
Rifki Ilham Baihaki, Dafik, Ika Hesti Agustin, Zainur Rasyid Ridlo, Elsa Yuli Kurniawati
Potato is a plant from the Solanaceae tribe and one of the staple crops for human consumption. Potatoes have several benefits such as being low in fat and having a better carbohydrate content than rice. Behind the relatively easy cultivation of potato plants, there are problems that are often faced by...
Proceedings Article
Detection Model for URL Phishing with Comparison Between Shallow Machine Learning and Deep Learning Models
Nizam Aditya Zuhayr, Girinoto, Nurul Qomariasih, Hermawan Setiawan
In the report on trends in phishing activity released by the Anti-Phishing Working Group (APWG), global phishing cases continued to increase throughout 2021 to the first quarter of 2022. This study compares shallow machine learning algorithms that have been used by governments with deep learning in classifying...
Proceedings Article
RBL-STEM Model Learning Activity Framework: VCO (Virgin Coconut Oil) Development Analysis Using Artificial Neural Network to Improve Student Metacognition
Rina Sugiarti Dwi Gita, Waris, H. B. A. Jayawardana
The ability to metacognition students is needed in welcoming the era of the industrial revolution 4.0 and technological disruption as it is today. Metacognition is a person’s ability to regulate and control cognitive processes in learning and thinking so that they become more effective and efficient....
Proceedings Article
The Modification of the Building Structural Design Using Steel-Concrete Composite and Eccentrically Braced Frames (EBF) System Structure
Mahdan Kintara Sanie, Budi Suswanto, Triwulan
The construction of high-rise buildings nowadays must be designed to be economical, have a symmetrical and good structure, and must be designed to be earthquake-resistant. Steel structure is one of the earthquake-resistant constructions that are better than concrete structure, since steel structure has...
Proceedings Article
Classification of Disease in Rice Plant Leaves Using the Method Convolutional Neural Networks
Laila Badriyatuz Zahro, Dafik, Ika Hesti Agustin, Zainur Rasyid Ridlo
Rice plant disease is one of the factors causing high losses due to crop failure. Plant-disturbing organisms often attack rice plants, especially on the leaves. This can damage rice plants and cause crop failure. Manual diagnostic activities on rice plant leaves will help identify and classify the types...
Proceedings Article
RBL-STEM Learning Activities: Analysis of Transgenic Sugarcane Development Using Artificial Neural Networks in Improving Students’ Combinatorial Thinking Skills
Ahdatu Uli Khikamil Maulidiya, Bambang Sugiharto, Joko Waluyo, Dafik, Indrawati
Science integration, Technology, Engineering and Mathematics (STEM) in learning activities is now increasingly important. STEM approach can improve students' combinatorial thinking skills. The implementation of research-based learning together with STEM education will be a good model in designing...
Proceedings Article
On Time Series Forecasting Analysis of Soil Moisture by Using Artificial Neural Networks Based - on Rainbow Antimagic Coloring for Autonomous Irrigation System on Horizontal Farming
Dini Mufidati, Zainur Rasyid Ridlo, Slamin, Ika Nur Maylisa, Dafik
Precision agriculture is one of the fields that play an important role in improving the social economy, it is due to that many people depend on the agricultural products. One of the supporting factors in agriculture is advancement the precision agriculture under the development of autonomous irrigation....
Proceedings Article
Application of Spatial Temporal Graph Neural Networks for Forecasting Data Time Series River Pollution Waste Content in Probolinggo
Nur Mauliska, Wahyu Lestari, Endah Tri Wisudaningsih, Muhammad Hifdil Islam
Flooding has become a serious problem in Probolinggo. One of the causes of flooding is the accumulation of garbage in the river. Garbage can also cause river water pollution. To measure water pollution, we use a pH meter. SRAC (Strong Rainbow Antimagic Coloring) is the smallest number of colors taken...
Proceedings Article
Text Processing Using Support Vector Machine for Scientific Research Paper Content Classification
Hasanuddin Al-Habib, Elly Matul Imah, Riskyana Dewi Intan Puspitasari, Binar Kurnia Prahani
Research related to text processing is carried out to analyze information in text data which can then be used in strategies for the development of the field of science and technology, one of which is the text processing of scientific research paper. Classification of scientific research paper is carried...
Proceedings Article
Application of Convolutional Neural Network for Identifying Cocoa Leaf Disease
Annisa Fitri Maghfiroh Harvyanti, Rifki Ilham Baihaki, Dafik, Zainur Rasyid Ridlo, Ika Hesti Agustin
Cocoa or Theobroma cacao L. is a plantation product that has high economic value and is very popular for its processed fruit. The large market demand for cocoa is not proportional to the low level of productivity. The main issue in cocoa plantations is the high incidence and rapid spread of disease....
Proceedings Article
On the Spatial Temporal Graph Neural Network Analysis Together with Local Vertex Irregular Reflexive Coloring for Time Series Forecasting on Passenger Density at Bus Station
Adidtiya Dwi Harliyuni, Dafik, Slamin, Zainur Rasyid Ridlo, Ridho Alfarisi
The transportation problem that occurs in urban areas is how to meet the demand for the increasing number of trips and avoid traffic jams on the highway. In Indonesia, traffic density occurs during office hours, holidays, and national holidays. The solution to this problem is to use an effective public...
Proceedings Article
The Development of Precision Agriculture Design by Using a Smart Sensor for Time Series Forecasting Analysis on Relative Humidity
Zainur Rasyid Ridlo, Sudarti, Joko Waluyo, Dafik
This research aims to design IoT effective and efficient tools for precision agriculture using NodemCu Board for measuring Temperature and Rh (Relative Humidity). The sensor for measuring Temperature and Rh uses DHT 11, a type of sensor DHT 11 using NTC (Negative Temperature Coefficient) as resistance...