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Scientific Journal of Informatics
Published by Universitas Negeri Semarang
ISSN : 24077658     EISSN : 24600040     DOI : -
Core Subject : Science,
Computer Science & IT
Scientific Journal of Informatics published by the Department of Computer Science, Semarang State University, a scientific journal of Information Systems and Information Technology which includes scholarly writings on pure research and applied research in the field of information systems and information technology as well as a review-general review of the development of the theory, methods, and related applied sciences.
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Articles 564 Documents
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Metadata Modeling of LoRa Based Payload Information for Precision Agriculture Tea Plantation Eddy Prasetyo Nugroho; Taufik Djatna; Imas Sukaesih Sitanggang; Irman Hermadi; Agus Mulyana; Sri Wahjuni; Heru Sukoco
Scientific Journal of Informatics Vol 10, No 2 (2023): May 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i2.43432

Abstract

Purpose: The purpose of this study is to model the metadata of Payload Information on Agriculture Drones which consists of the results of images computational and the Onboard system of the Drone.Methods: The stages of the research were carried out with the process of forming Payload information metadata from the Agriculture Drone with sensors/actuators based on the architecture and computing with Image Processing or Computer Vision on the camera captures. This study describes the metadata modeling process formed from the Internet of Things system with Drone and GCS communication based on the Long Range or Long-Range Wide Area Network protocols with Payload information consisting of drone data and image computation results. Result: The result obtained is the formation of Payload information from LoRa-based Drones with a frame size of 142 bytes. Novelty: Payload information is formed into a metadata model indicator with the formation scheme being part of the tea plantation dataset. The metadata model will be test expected to obtain field data on Drones and GCS communication in the LoRaWAN Network in tea plantations which are rural environments. 
Responsible Urban Innovation Working with Local Authorities a Framework for Artificial Intelligence (AI) Ida Farida; Wahyu Ningsih; Ninda Lutfiani; Qurotul Aini; Eka Purnama Harahap
Scientific Journal of Informatics Vol 10, No 2 (2023): May 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i2.43818

Abstract

Purpose: By demonstrating that by adopting the principles of responsible urban innovation, we can harness the potential of digital technology to address urbanization issues and can minimize potential negative impacts.Methods: The paper proposes a conceptual framework for accountable urban innovation, focusing on government AI systems, and draws on a literature review, practical examples, and research. The authors argue that responsible urban innovation must balance the costs, benefits, risks, and impacts of developing, implementing, and using AI systems in local government management. This approach emphasizes the importance of achieving desired urban outcomes while ensuring accountability.Results: The framework provides potential directions for future research and development, offering an overview of recognized topics and a schedule for analysis. This research may assist urban managers, planners, and decision-makers in understanding the critical role that government AI systems play in achieving accountable outcomes. By adopting responsible urban innovation principles, we can harness the potential of digital technology to address urbanization issues while minimizing potential negative impacts.Novelty: The conceptual framework presented in this study offers a new view in understanding the role of local government AI systems in achieving accountable outcomes.
Simulation Coordination Control of PVAnd Battery On Microgrid With PI Controller Adhi Kusmantoro; Takashi Hiyama
Scientific Journal of Informatics Vol 10, No 2 (2023): May 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i2.43923

Abstract

Purpose: The output power of PV (photovoltaic) changes according to changes in the intensity of solar radiation. Therefore, the purpose of this study is to use a utility grid connected system to overcome changes in solar energy sources and loads. This is done to maintain an uninterrupted power supply to the load.Methods: In this study, we propose a grid-connected PV system with several DC-DC converters connected in parallel with several PV sources and batteries with PI control coordination. The proposed method includes two stages, namely the DC-DC converter development stage and the battery management strategy stage.Results: The study results show that within 0 seconds to 0.45 seconds the DC bus is supplied with PV. Due to the change in PV, within 0.45 seconds to 0.65 seconds the DC bus is supplied with unit-1 battery. When there is a change in the unit-1 battery, within 0.65 seconds to 0.8 seconds the DC bus is supplied with the unit-2 battery. By using PV coordination arrangements and battery units, the microgrid can still supply power to the load even if changes occur in the PV or grid.Novelty: The novelty in this study is a new microgrid configuration to increase the demand for electrical loads. The new configuration uses multi-PV and multi-battery. Multi-PV is used to supply the load and is stored in the multi-battery, while multi-battery is used at night and if there is a disturbance at the PV output.
Coastal Sentiment Review Using Naïve Bayes with Feature Selection Genetic Algorithm Somantri, Oman; Maharrani, Ratih Hafsarah; Purwaningrum, Santi
Scientific Journal of Informatics Vol 10, No 3 (2023): August 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i3.43988

Abstract

Purpose: The tourism potential in the maritime sector can be Indonesia's mainstay at this time, especially in enjoying the charm of the natural beauty of the coast as people know Indonesia is an archipelagic country. The purpose of this study is to find the best model by applying the feature selection genetic algorithm (GA) and Information Gain (IG) to get the best Naïve Bayes (NB) model and the best features to produce the best level of sentiment classification accuracy.Methods: The stages of the research were carried out by going through the process of searching, pre-processing, analyzing research data using the Naïve Bayes model and optimizing genetic algorithms, validating data, and model evaluation.Result: The experimental results show that the best model is naïve Bayes based on information gain and the genetic algorithm yields an accuracy rate of 86.34%.Novelty: The main contribution to this research is proposing a new model of the best NB optimization model by applying an optimization algorithm in the search for feature selection to increase sentiment classification accuracy.
The Impact of System and Information Quality on User Satisfaction and Continuance Intention: An Analysis of Online Motorcycle Taxi (Ojek-Online) Applications Novita Mariana; Isworo Nugroho; Saefurrohman Saefurrohman; Agus Prasetyo Utomo
Scientific Journal of Informatics Vol 10, No 2 (2023): May 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i2.43830

Abstract

Purpose: The study’s goal was to analyze the adoption of online motorcycle taxi (in Indonesia it is called an ojek online) technology with the purpose to keep using the application.Methods: The study used the System Success Model to develop this research model. It was conducted based on the premise that information quality and system quality positively influence the ease and usefulness of the system application. The ease and usefulness of the system application have implications for user satisfaction and the intention to continue using the system. The study employed Structural Equation Modeling (SEM) using PLS (SEM) 4.0 to test and evaluate the measurement model and structural model. A sample of 235 respondents who are users of the online motorcycle taxi system in Semarang City was used in the study.Result: Out of 10 hypotheses tested, 9 hypotheses were accepted and 1 hypothesis was rejected. The usefulness of the system had a negative and insignificant influence on the intention to continue using the system. The intention to continue using the online motorcycle taxi application was strongly determined by the ease of the application system and user satisfaction. The discoveredings also showed that the quality of the system had the strongest influence on the ease of the system. Novelty: This study was unique in combining the Technology Acceptance Model and Mclean Delone approach to test the quality of the online motorcycle taxi application towards user satisfaction and intention to continue using the application.
Optimization of Polynomial Functions on the NuSVR Algorithm Based on Machine Learning: Case Studies on Regression Datasets Setyo Budi; Muhamad Akrom; Gustina Alfa Trisnapradika; Totok Sutojo; Wahyu Aji Eko Prabowo
Scientific Journal of Informatics Vol 10, No 2 (2023): May 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i2.43929

Abstract

Purpose: Experimental studies are usually costly, time-consuming, and resource-intensive when it comes to investigating prospective corrosion inhibitor compounds. Machine learning (ML) based on the quantitative structure-property relationship model (QSPR) has become a massive method for testing the effectiveness of chemical compounds as corrosion inhibitors. The main challenge in the ML method is to design a model that produces high prediction accuracy so that the properties of a material can be predicted accurately. In this study, we examine the performance of polynomial functions in the ML-based NuSVR algorithm in evaluating the regression dataset of corrosion inhibition efficiency of pyridine-quinoline compounds.Methods: Polynomial functions for NuSVR algorithm-based ML.Result: The outcomes demonstrate that the NuSVR model's prediction ability is greatly enhanced by the application of polynomial functions. Originality: The combination of polynomial functions and deep machine learning based NuSVR algorithms to increase the accuracy of predictive models.
Alphabet Classification of Sign System Using Convolutional Neural Network with Contrast Limited Adaptive Histogram Equalization and Canny Edge Detection Raharjo, Ahmad Solikhin Gayuh; Sugiharti, Endang
Scientific Journal of Informatics Vol 10, No 3 (2023): August 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i3.44137

Abstract

Purpose: There are deaf people who have problems in communicating orally because they do not have the ability to speak and hear. The sign system is used as a solution to this problem, but not everyone understands the use and meaning of the sign system, even in terms of the alphabet. Therefore, it is necessary to classify a sign system in the form of American Sign Language (ASL) using Artificial Intelligence technology to get good results.Methods: This research focuses on improving the accuracy of ASL alphabet classification using the VGG-19 and ResNet50 architecture of the Convolutional Neural Network (CNN) method combined with Contrast Limited Adaptive Histogram Equalization (CLAHE) to improve the detail quality of images and Canny Edge Detection to produce images that focus on the objects in it. The focused result is the accuracy value. This study uses the ASL alphabet dataset from Kaggle.Result: Based on the test results, there are three best accuracy results. The first is using the ResNet50 architecture, CLAHE, and an image size of 128 x 128 pixels with an accuracy of 99.9%, followed by the ResNet50 architecture, CLAHE + Canny Edge Detection, and an image size of 128 x 128 pixels with an accuracy of 99.82 %, and in third place are the VGG-19 architecture, CLAHE, and an image size of 128 x 128 pixels with an accuracy of 98.93%.Novelty: The novelty of this study is the increase in the accuracy value of ASL image classification from previous studies.
Classification of Spiral and Non-Spiral Galaxies using Decision Tree Analysis and Random Forest Model: A Study on the Zoo Galaxy Dataset Lulut Alfaris; Ruben Cornelius Siagian; Aldi Cahya Muhammad; Ukta Indra Nyuswantoro; Nazish Laeiq; Froilan Delute Mobo
Scientific Journal of Informatics Vol 10, No 2 (2023): May 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i2.44027

Abstract

Purpose: The goal of this research is to create a precise prediction model that can differentiate between spiral and non-spiral galaxies using the Zoo galaxy dataset. Decision tree analysis and random forest models will be used to construct the model, and various conditions within the dataset will be employed to classify the data accurately. The model's performance will be evaluated using a confusion matrix, and the probability of predicting spiral galaxies will be analyzed. The research will also investigate the differences in Total Power among signal types and identify Peak Frequency and Bandwidth values consistent across all signal types. This study is expected to provide important insights into galaxy classification and signal characteristics, specifically in the fields of astronomy and astrophysics.Methods: This study utilized the decision tree analysis research method to create a predictive model for identifying spiral galaxies using the Zoo galaxy dataset. The research approach focused on analyzing data before constructing a prediction model. The study did not involve random sampling, making it an observational study. Decision tree analysis was employed to classify galaxies into homogeneous groups, and a random forest model was used to classify galaxy types. This research provides insights into how decision tree analysis can be utilized to comprehend galaxy classification and can serve as a foundation for future research. To strengthen the conclusions, combining this research with other approaches such as experiments or random sampling can be considered.Result: This study developed a predictive model for classifying galaxies based on their Spiral type using decision tree analysis on the Zoo galaxy dataset. The model divided the data into specific groups based on certain conditions, and the results demonstrated exceptional accuracy of the random forest model in categorizing galaxy types. In addition, the study investigated various signal types in galaxies and found variations in Total Power, but consistent values for Peak Frequency and Bandwidth at 2 in all signals. These findings provide valuable insights into galaxy classification and signal characteristics, which could have practical applications in communication, signal processing, and analysis. The utilization of decision tree analysis and random forest models for galaxy classification and signal analysis represents an innovative approach in this field.Novelty: The novelty of this research lies in the new approach to categorizing galaxy types using decision tree and random forest models. Previously, the approach used to categorize galaxy types was through visual methods and observations via telescopes. This new approach provides a new and potentially more efficient way of processing galaxy image data, resulting in faster and more accurate categorization. Moreover, this research contributes to the development of signal analysis applications such as Total Power, Peak Frequency, and Bandwidth, which were previously only used in the fields of astronomy and astrophysics. However, they have the potential for wider applications in the fields of communication, signal processing, and analysis beyond astronomy
Partial Least Square Algorithm (PLS) with Technology Acceptance Model (TAM) in User Analysis of Public Health Center Management Information System (SIMPUS) Applications Sri Mulyono Mulyono; Wahyul Amien Syafei; Retno Kusumaningrum
Scientific Journal of Informatics Vol 10, No 2 (2023): May 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i2.44148

Abstract

Purpose: The most important information system application at the health center is the health center management information system or can be called SIMPUS. The SIMPUS is an application program specifically designed to help facilitate recording of patient data, processing and presenting data into information in a short time. With the SIMPUS application, it is necessary to examine whether the application is very helpful for users in completing work at the public health center or Puskesmas. Therefore, the purpose of this study is to analyze the SIMPUS application users by combining the Partial Least Square (PLS) algorithm with the Technology Acceptance Model (TAM) method.Methods: SIMPUS application user analysis is carried out using a combination of the Partial Least Square (PLS) algorithm with the Technology Acceptance Model (TAM) method. The variables used are Perceived Usefulness, Perceived Ease of Use, Attitude Towards Using, Behavioral Intention to Use, and Actual System Use. Data collection techniques by distributing closed questionnaires and taking samples with the solvency formula. Sampling was carried out using a multistage random sampling technique, the number of 12 Puskesmas in each Puskesmas from the calculation results determined 40 samples.Result: From the statistical test results, the effect of the perceived usefulness on the ease of use has the highest level of influence, which obtaining a test value of 3.6. Furthermore, the effect of the attitude towards using on the behavioral intention to use has the lowest level of influence, which obtaining a test value of 1.2.Value: Analysis and testing of variables that influence user acceptance of the SIMPUS application using the Partial Least Square (PLS) algorithm and the Technology Acceptance Model (TAM) approach, that acceptance of the SIMPUS application is influenced by the level of usability and ease of use of the application.
A Systematic Literature Review of Multimodal Emotion Recognition Yeni Dwi Rahayu; Lutfi Ali Muharrom; Ika Safitri Windiarti; Auratania Hadisah Sugianto
Scientific Journal of Informatics Vol 10, No 2 (2023): May 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i2.43792

Abstract

Purpose: This literature review aims to identify Multimodal Emotion Recognition (MER) in depth and breadth by analysing the topics, trends, modalities, and other supporting sources discussed in research over the years and between 2010 and 2022. Based on the screening analysis, a total of 14,533 articles were analysed to achieve this goal.Methods: This research was conducted in 3 (three) phases, including Planning, Conducting and Reporting. The first step was defining the research objectives by searching for systematic reviews with similar topics to this study, then reviewing them to develop research questions and systematic review protocols for this study. The second stage is to collect articles according to a pre-determined protocol, selecting the articles obtained and then conducting an analysis of the filtered articles in order to answer the research questions. The final stage is to summarize the results of the analysis so new findings from this research can be reported.  Result: In general, the focus of MER research can be categorised into two issues, namely the object background and the source or modality of emotion recognition. When looking at the object background, most of the 55% to support emotion recognition with a health background, especially brain function decline, 34% based on age, 10% based on gender, 1% data collection situation and a small portion of less than 1% related to ethnic culture. In terms of the source of emotion recognition, research is divided into electromagnetic signals, voice signals, text, photo/video and the development of wearable devices. Based on the above results, there are at least 7 scientific fields that discuss MER research, namely health, psychology, electronics, grammar, communication, socio-culture and computer science.Novelty: MER research has the potential to develop further. There are still many areas that have received less attention, while the ecosystem that uses them has grown massively. Emotion recognition modalities are numerous and diverse, but research is still focused on validating the emotions of each modality, rather than exploring the strengths of each modality to improve the quality of recognition results.

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