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  • Support Vector Machine for Satellite Images Classification 

    Using Radial Basis Function Kernel Method

    Authors: Nur Suhaili Mansor ; Hapini Awang ; Sarkin Tudu Shehu Malami ; Amirulikhsan Zolkafli ; Mohammed Ahmed Taiye ; Hanhan Maulana 

    DOI: 10.1007/978-981-99-9589-9_23

    Abstract

    Machine learning, particularly Support Vector Machines (SVM), has gained popularity in geospatial data processing and image classification. Geospatial data from various sources may contain errors, impacting image classification accuracy. Traditional pixel-based and object-based methods struggle to classify complex land cover classes accurately. Previous studies explored machine learning algorithms like Random Forests, K-Nearest Neighbors, and Neural Networks. Still, they faced challenges capturing intricate relationships within images and required substantial labeled training data, leading to computational expenses. SVM with polynomial kernels was attempted in some studies, but it suffered from potential overfitting and inefficiency for large datasets. To overcome these issues, this study employed SVM with RBF and Linear kernels to classify multispectral satellite images from the SPOT-6 Satellite Imagery dataset in Sungai Kelang, Malaysia. Previous research evaluated each kernel’s performance accuracy compared using a test dataset, utilizing open-source tools like Jupyter Notebooks and Python libraries to explore SVM’s potential as a high-performance satellite image classification technique. The findings revealed that SVM with RBF kernel outperformed SVM with polynomial or linear kernels in classifying satellite images. The RBF kernel’s robustness allowed SVM to model intricate decision boundaries and capture complex patterns in the image data, making it suitable for tasks with non-linearly separable data. The study introduces a new methodology and theoretical contribution to image classification-related literature, shedding light on the efficacy of SVM-RBF for geospatial data processing. It provides an alternative to traditional approaches for complex image classification tasks. Moreover, the research assists in selecting the optimal algorithm for remote sensing and satellite imagery applications. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

    Author keywords

    Geospatial; Image Classification; Linear Kernel; Radial basis function (RBF) Kernel; Support Vector Machine

    Indexed keywords

    Engineering controlled terms

    Classification (of information); Complex networks; Data handling; Forestry; Large datasets; Learning algorithms; Nearest neighbor search; Radial basis function networks; Remote sensing; Satellite imagery; Statistical tests; Support vector machines

    Engineering uncontrolled terms

    Geo-spatial; Geospatial data processing; Images classification; Kernel-methods; Linear kernel; Performance; Polynomial kernels; Radial basis function kernels; Satellite image classification; Support vectors machine

    Engineering main heading

    Image classification

    This article can be accessed at https://www.scopus.com/pages/publications/85185723250

  • IoT (Internet of Things) as a Tool to Help Regulate Water Altitude on Dams

    Authors: Sri Supatmi, Dita Ardisura Pamungkas, Desta Rifaldi Nugraha, A Febrian, Audi Citra Fadilah

    DOI: 10.1109/INCITEST64888.2024.11121455

    Abstract

    In each dam in the Citarum River, workers from the management officers must go to each dam to arrange the doors of irrigation and record for the report if the officers who visit each dam and make irrigation reports can be minimized to be more efficient. Therefore, this research aims to help regulate water altitude on dams through a dam monitoring system employing the Internet of Things (IoT). IoT is a structure where objects, people who are provided with an exclusive identity, and the ability to move data over a network without requiring two-way between humans to humans is the source of human purpose or interaction to a computer. The way it works from IoT is that objects must have an Internet Protocol (IP) address. Furthermore, Internet Protocol (IP) addresses in these objects are connected to the Internet network. The idea is expected to be an alternative solution for dam officers in managing irrigation in the dam to raise the officers’ performance in working because of the many times created from this monitoring system. Data collection was conducted through interviews in the hall of Management of River Basin Water Resources (PSDA WS) in Citarum, West Java Province. This research result is the prototype of irrigation monitoring tools to facilitate the modeling of the devices. © 2024 IEEE.

    Author keywords

    dam monitoring system; IoT; regulate water altitude

    This article can be accessed at https://www.scopus.com/pages/publications/105015867292

  • Comparison of SAW and MABAC Methods in Determining Strategic Tourism Destinations with Entropy Weighting Integration

    Authors: Muhlas Adiputra, Yeffry Handoko Putra

    DOI: 10.1109/INCITEST64888.2024.11121470

    Abstract

    Bima Regency, with its natural and cultural diversity, has great potential as a strategic tourism destination that requires proper management. However, the main challenge faced is determining the most potential destinations appropriately and supported by accurate data. In an effort to address the problem, this research utilizes the Entropy method for criteria weighting and applies two multi-criteria decisionmaking methods, Simple Additive Weighting (SAW) and MultiAttributive Border Approximation area Comparison (MABAC), to evaluate their effectiveness in selecting tourist destinations in Bima Regency. The results show that both methods consistently identify Lariti Beach as a superior destination. From the comparison of the two methods, the SAW method provides more stable and consistent results, is suitable for less complex conditions, and requires long-term reliability. Meanwhile, the MABAC method shows higher sensitivity to data changes, with more significant fluctuations in results. Thus, the SAW method is considered more appropriate for use in the selection of strategic tourist destinations in Bima Regency, considering that this method provides consistent results as well as efficiency and ease of application. © 2024 IEEE.

    Author keywords

    determination of strategic tourism destinations; DSS; entropy; MABAC; MCDM; SAW

    This article can be accessed at https://www.scopus.com/pages/publications/105015860453

  • Technology Acceptance Model Analysis on The Implementation 

    of Accounting Information Systems

    Authors: Harpa Sugiharti; Lulu Sri Hamdiati; Ajang Mulyadi; Apriani Puti Purfini; Nurul Amalia Ramdan

    DOI: 10.1109/INCITEST64888.2024.11121488

    Abstract

    This research aims to find out the level of reception users through the Technology Acceptance Model (TAM) analysis of the Accounting Information System implementation for MSMEs using the Paper.id application. This research is quantitative research with methods of descriptive verification. The research sample consisted of 155 MSME users of the Paper.id application that implements the Accounting Information System. Calculation method samples using the Inverse Square Root technique. Validity test instrument using convergent validity and reliability tests using composite reliability. The primary data in this research is the respondents’ answers collected by distributing questionnaires. The data analysis technique used is Structural Equation Modeling Analysis Based on Partial Least Square (PLS-SEM) with the help of SmartPLS 4.1 software. They are testing the hypothesis using the T-Test with the help of Bootstrapping. Test results show that perception usability and perception convenience influence attitude to usage positively, and perception usability and perception convenience influence positive use in an actual way. Furthermore, the attitude to use influential positives should be used in an actual way. © 2024 IEEE.

    Author keywords

    attitude to usage; paper.id application; perceived uses; perception ease; use by actual

    Indexed keywords

    Engineering controlled terms

    Inverse problems

    Engineering uncontrolled terms

    Accounting Information Systems; Attitude to usage; Id application; Modeling analyzes; Paper.; Perceived use; Perception ease; Technology acceptance model; Use by actual; Validity tests

    Engineering main heading

    Information systems; Information use

    This article can be accessed at https://www.scopus.com/pages/publications/105015850795

  • Comparison of Bidirectional-LSTM and GRU Models for Sentiment Analysis in Bahasa Indonesia

    Authors: Muhammad Rajab Fachrizal, Annisa Paramitha Fadillah, Lusi Melian

    DOI: 10.1109/INCITEST64888.2024.11121460

    Abstract

    Bidirectional-LSTM and GRU are models that can be used to process sequential data, including text data. This study, compares the two deep learning models to classify text for sentiment analysis using the Bahasa. The dataset used is the JKN BPJS Kesehatan mobile application user review data obtained from the Google Play Store site. After text preprocessing, the amount of data to be processed is 93517 with three target labels, positive, negative, and neutral. By using several model parameters such as Number of Units, Activation, Batch Size, Dropout, and other parameters, the test results obtained are that the Bidirectional-LSTM model has a slight accuracy value of 96.70% and higher precision, recall, and F1Score values compared to the GRU model. © 2024 IEEE.

    Author keywords

    Bahasa; Bi-LSTM; deep learning; GRU; sentiment analysis; text classification

    This article can be accessed at https://www.scopus.com/pages/publications/105015853213

  • Digital Encyclopedia: The Product of the Integration between Islam and Science

    Authors: Buchori Muslim; Nahadi; Sjaeful Anwar; Heli Siti Halimatul Munawaroh; Neng Sri Nuraeni; Tatan Tawami

    DOI: 10.1109/INCITEST64888.2024.11121463

    Abstract

    Digital encyclopedia is produced from the integration of Islam with science. Integration between religious knowledge and general knowledge or vice versa seeks to provide information that all knowledge comes from God, while the content and development of both are a form of worship to the creator. The presence of a dichotomy between faith education (religious sciences) and general education (science) makes it interesting to study in more depth. This causes the integration between scientific disciplines to be lost. In fact, today’s educational products tend to be oriented towards intellectual development, but are not balanced with spiritual, emotional, social and moral aspects. The aim of this research is to produce a digital encyclopedia based on the integration of Islam and science. The research method used in this research is descriptive with the Design and Development model popularized by Allesi and Trollip. The instruments used in this research are the alpha test instrument and the beta test instrument. Data analysis is carried out by simplifying the data into a form that is easier to read and interpret. The research results show that religion and science need each other and do not conflict. Because, any knowledge does not stand alone (self-sufficient). The presence of the digital encyclopedia brings the message that knowledge can be enjoyed by anyone, is no longer limited by time and space, and is more interesting. © 2024 IEEE.

    Author keywords

    dichotomy; digital encyclopedia; islam and science; islamic integration; learning media

    Indexed keywords

    Engineering uncontrolled terms

    Dichotomy; Digital Encyclopedias; General education; General knowledge; Islam and (religious science) and general education; Islamic integration; Learning media; Science education; Scientific discipline; Test instruments

    Engineering main heading

    Integration

    This article can be accessed at https://www.scopus.com/pages/publications/105015889788

  • Sigma Level Quality Analysis with Simulation Approach at PT. Mitra Rajawali Banjaran

    Authors: Diana Andriani, Iyan Andriana, I Made Aryantha Anthara, Muhammad Rifky Naufal, Ira Rustiendah

    DOI: 10.1109/INCITEST64888.2024.11121464

    Abstract

    PT. Rajawali Mitra Banjaran is a company engaged in the field of medical devices. One of the products of this company is the ADS (Auto Disable Syringe) syringe, but production in 2022 has a fairly high defect rate of 13% of total production and shows a sigma level of 3.56. It is known that the factors causing defects are man, machine, and method. To increase the company’s sigma level, quality control and the creation of a conceptual model from a simulation using ProModel are needed, then a comparison is made between actual production conditions and simulation conditions, it is hoped that this can reduce the number of defects and increase the company’s sigma level. Based on the results of the study using the ProModel application, the output of the proposed product has a difference of 18%, defective products decreased to 6.5% from the initial model, and the sigma value increased to 4.02. © 2024 IEEE.

    Author keywords

    model simulation; Production process; quality control; sigma level

    This article can be accessed at https://www.scopus.com/pages/publications/105015892369

  • Optimizing Forest Fire Detection Using PSO, Neural Networks, 

    and k-Fold Cross-Validation

    Authors: Nina Kurnia Hikmawati; Yudi Ramdhani; Doni Purnama Alamsyah

    DOI: 10.1109/ICIC64337.2024.10956756

    Abstract

    Preventing Forest fires by identifying events based on specific criteria using the Neural Network (NN) algorithm. To ensure result stability, test and training data are divided using k-fold cross-validation with variations k-5, k-10, and k-20. The NN algorithm performed significantly better after being optimized with Particle Swarm Optimization (PSO), with the average accuracy value going from 97% to 98.78% and the AUC value increasing from 0.997 to 0.999. A weight study of PSO reveals variability in values for each attribute, with Day and Month having no significant effect on classification. The results of the Paired Two-sample t-test for Means show that using PSO improves accuracy significantly. The merging of PSO with Neural Networks has a considerable positive influence on forest fire prediction and is suggested for applications requiring high accuracy. © 2024 IEEE.

    Author keywords

    Forest Fires; Machine Learning; Neural Networks; Particle Swarm Optimization

    Indexed keywords

    Engineering controlled terms

    Stability criteria

    Engineering uncontrolled terms

    Forest fire detection; Forest fires; K fold cross validations; Machine-learning; Neural networks algorithms; Neural-networks; Particle swarm; Particle swarm optimization; Particle swarm optimization-neural networks; Swarm optimization

    Engineering main heading

    Particle swarm optimization (PSO)

    This article can be accessed at https://www.scopus.com/pages/publications/105004579202

  • Design and Implementation of Temperature and Humidity Monitoring and Control System in IoTbased Chicken Eggs Incubator

    Authors: Hidayat, Aditia Dwi Subhana Putra, Mochamad Fajar Wicaksono

    DOI: 10.1109/INCITEST64888.2024.11121478

    Abstract

    Temperature and humidity during the hatching of chicken eggs greatly determine its success. Inconsistent egg turning causes slow embryo development. The number of eggs can affect temperature and humidity if not managed properly. This research aims to build an IoT-based control and monitoring system for hatching chicken eggs using ESP32 WROOM, DHT22, ESP32-CAM and PIR sensors. This research uses an experimental method. The research benefit is monitoring temperature and humidity values in the incubator and controlling the eggs’ turning. ESP32 WROOM 32 is used as a data processing unit. DHT22 is used as a temperature and humidity sensor. ESP32-CAM is used to monitor the condition of the eggs in the incubator. The PIR sensor is used to detect hatching eggs. In addition, a stepper motor is used to rotate the roller rack so that the eggs can be turned over. The research results show that the temperature in the incubator can be stabilized at 37° C-39°C. Egg turning can be done automatically and regularly every day. The Blynk application can display the temperature and humidity in the incubator and stream the incubator conditions. It is hoped that the results of this research will increase the ease of managing the hatching of chicken eggs. © 2024 IEEE.

    Author keywords

    Blynk application; eggs incubator; Internet of Things; monitoring system; temperature and humidity

    This article can be accessed at https://www.scopus.com/pages/publications/105015874296

  • Android Based Arduino Learning Model by Implementing Multi Marker Augmented Reality

    Authors: John Adler; Selvia Lorena Br Ginting; Mochamad Fajar Wicaksono; Dianto Setiyadi; Yogie Rinaldy Ginting

    DOI: 10.1109/INCITEST59455.2023.10396965

    Abstract

    This research aims to develop an interactive learning system based on Arduino Uno basic material. To realize this system, Augmented Reality technology is used which will explain each Arduino Uno pin function along with an explanation of each example of the basic circuit provided. This started with the Arduino Uno learning process which often caused damage to the Arduino or the components that were connected to the Arduino itself during the process of making the circuit. This problem can occur due to a lack of basic understanding of theory. The use of Augmented Reality technology is able to display objects in the form of Arduinos in virtual 3D, so that 3D objects can appear, markers are used to mark each object, the introduction of the Arduino Uno itself can be simulated by providing a real picture using the multi marker method where there is a main marker containing 3D objects in the Arduino series and supporting markers containing explanations of the series. Thus, learning is not limited to conventional learning and minimizes errors in trials. The method used to develop the system is the waterfall method. The waterfall method itself is part of implementing a design with a good and reasonable target. Based on the tests obtained, the Arduino Uno learning application is able to run well using multiple markers, 3D or 2D objects can be run on a smartphone, and black box testing and marker reading testing are carried out with different lighting levels and reading from different sides. © 2023 IEEE.

    Author keywords

    arduino; augmented reality; learning; markers; smartphones

    This article can be accessed at: https://www.scopus.com/pages/publications/85185201436