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Edi Sutoyo
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Indonesian Scientific Journal (Jurnal Ilmiah Indonesia) Jl. Pasar Atas No 3, Kompleks Setramas Kota Cimahi, Bandung
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International Journal of Advances in Data and Information Systems
Published by Indonesian Scientific Journal
ISSN : -     EISSN : 27213056     DOI : https://doi.org/10.25008/ijadis
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal of Advances in Data and Information Systems (IJADIS) (e-ISSN: 2721-3056) is a peer-reviewed journal in the field of data science and information system that is published twice a year; scheduled in April and October. The journal is published for those who wish to share information about their research and innovations and for those who want to know the latest results in the field of Data Science and Information System. The Journal is published by the Indonesian Scientific Journal. Accepted paper will be available online (free access), and there will be no publication fee. The author will get their own personal copy of the paperwork. IJADIS welcomes all topics that are relevant to data science, and information system. The listed topics of interest are as follows: Data clustering and classifications Statistical model in data science Artificial intelligence and machine learning in data science Data visualization Data mining Data intelligence Business intelligence and data warehousing Cloud computing for Big Data Data processing and analytics in IoT Tools and applications in data science Vision and future directions of data science Computational Linguistics Text Classification Language resources Information retrieval Information extraction Information security Machine translation Sentiment analysis Semantics Summarization Speech processing Mathematical linguistics NLP applications Information Science Cryptography and steganography Digital Forensic Social media and social network Crowdsourcing Computational intelligence Collective intelligence Graph theory and computation Network science Modeling and simulation Parallel and distributed computing High-performance computing Information architecture
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 168 Documents
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Business Intelligence Based on Kimball Nine-Steps Methodology for Monitoring the Feasibility of Goods in Market I Putu Agus Eka Pratama; I Made Sunia Raharja
International Journal of Advances in Data and Information Systems Vol. 4 No. 2 (2023): October 2023 - International Journal of Advances in Data and Information System
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i2.1301

Abstract

Consumer protection is of great concern to the Government of Indonesia through the supervision of goods on the market by the Department of Industry and Trade in each province. The Bali Provincial Office of Industry and Trade has transactional data from various data sources but has not been able to optimize it to support monitoring of goods circulating in the market. This research designs and implements a Data Warehouse-based Business Intelligence system using the Kimball Nine-Steps Methodology and Pentaho BI tools, to facilitate the storage and processing of goods data on the market, and monitor their feasibility. The results of this research show that the system can assist the Bali Province Industry and Trade Office in monitoring the feasibility of goods circulating in the market through the selection process for determining query priorities and query modes, as well as supporting decision-making processes and determining business strategies.
Implementation of Random Search Algorithm with FSSRS (Fixed Step Size Random Search) for Applicating the Patrol System Based on Mobile Computing Sasmitoh Rahmad Riady; Rika Apriani; Jafar Shadiq
International Journal of Advances in Data and Information Systems Vol. 4 No. 2 (2023): October 2023 - International Journal of Advances in Data and Information System
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i2.1303

Abstract

Environmental security is very influential for the sustainability of human life. In order for environmental security to remain in a safe condition, a system is needed that can control the environment, such as patrolling at every point to ensure that the environmental conditions are safe. However, it is felt that this is not enough if the patrol system is not assisted by tools or systems that are digitalized and integrated with community service officers, such as firefighters, ambulances, and police, and are easy for officers to use when conducting patrols. So, it is necessary to schedule patrols to several points with different routes for each activity so that it is not easily read by unwanted parties in terms of crime. In order for the system to obtain patrol scheduling in a timely and efficient manner, an appropriate and efficient algorithm is needed, the algorithm is random search with FSSRS (Fixed Step Size Random Search) which can suggest random and precise patrol scheduling. From the results of training using four iterations, namely 50, 100, 150, and 200, the best value was produced in the 200th iteration. Data was taken from the results of a case study survey with eight patrol points using coordinates at each point. So, it can be concluded that the FSSRS algorithm is effectively used to randomize patrol points and can be implemented in the application patrol system.
Enhancing Soil-Transmitted Helminth Detection in Microscopic Images Using the Chain Code for Object Feature Extraction Rio Andika Malik; Marta Riri Frimadani; Dwipa Junika Putra
International Journal of Advances in Data and Information Systems Vol. 4 No. 2 (2023): October 2023 - International Journal of Advances in Data and Information System
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i2.1305

Abstract

Soil-Transmitted Helminth (STH) infections are a grave global health issue, which involves particularly in countries that are developing with insufficient sanitation and limited access to healthcare. With better intestinal helminth egg detection technology, health facilities in areas with limited resources can identify and treat these infections more promptly. It is necessary to create a strong framework and an effective method to solve this challenge. The outcomes of this study could assist in parasite infection discovery and public health. Chain code-based feature extraction strategy can also be the foundation for the development of comparable approaches for diagnosing various parasitic diseases. Overall, the neural network design used in this study makes the model that is produced a good model that assigns well to never-before-seen data. The significance of image processing technologies in the medical field is shown by this study.
Hoax Detection News Using Naïve Bayes and Support Vector Machine Algorithm Nur Elyta Febriyanty; M. Amin Hariyadi; Cahyo Crysdian
International Journal of Advances in Data and Information Systems Vol. 4 No. 2 (2023): October 2023 - International Journal of Advances in Data and Information System
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i2.1306

Abstract

Websites and blogs are well-known as media for broadcasting news in various fields such as broadcasting news. The validity of news articles can be valid or fake. Fake news is also known as hoax news. The purpose of making hoax news is to persuade, manipulate, and influence news readers to do things that contradict or prevent correct action. This study proposes to experiment with the Support Vector Machine and Naïve Bayes classifications to detect hoax news in Indonesian. This study uses a dataset from public data, namely news between valid news and hoaxes. The system can classify online news in Indonesian with the term frequency feature the machine vector Support algorithm and naïve Bayes classification. While the evaluation model used is the Confusion Matrix. The results of the comparison of the two models as a Support Vector Machine have an accuracy rate of 75,5%, and Naive Bayes has an accuracy rate of 88%. Therefore, for the classification of hoax news, we recommend the Naive Bayes model because it has a better level of accuracy than the Support Vector Machine.
The Evaluation of Computer Science Curriculum for High School Education Based on Similarity Analysis Syaifudin Ramadhani; Mokhammad Amin Hariyadi; Cahyo Crysdian
International Journal of Advances in Data and Information Systems Vol. 4 No. 2 (2023): October 2023 - International Journal of Advances in Data and Information System
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i2.1307

Abstract

The government is currently developing regulations to regulate education curriculum For High School Students. In this regulation, curriculum standards have been created that can be developed by educators in schools. Computer science teachers at the school level develop a curriculum that has been set as a standard curriculum. However, measurable evaluation to optimize the development of the new curriculum has not been available yet. This research proposes a form of evaluation that can be used as a benchmark by analyzing the similarity of curriculum content developed by teachers using a text mining approach. This is conducted by comparing computer science documents with applicable documents, namely knowledge field documents. It is expected that the results of optimizing competency development in the computer science curriculum can be achieved better. The average similarity checking performances using Cosine Similarity and Word2Vec are 40.9850 and 97.3558 respectively. Meanwhile, in the process of fulfilling the knowledge sector, with Cosine Similarity an average percentage of 40.98% was obtained, and with Word2Vec an average percentage of 97.36% was obtained. The results of this trial will be used as a basis for measurable evaluation of teacher contributions to be able to develop the curriculum better according to the applicable curriculum. The results of this evaluation are also used by the government to make future curriculum evaluations more measurable and the standards used are clear and help facilitate curriculum development in schools.
Data-Driven Analytical Model Using Machine Learning Algorithms: A Case Study on Clean and Healthy Living Behaviour in Surabaya City's Coastal Areas Harun Al Azies; Noval Ariyanto; Ishak Bintang Dikaputra
International Journal of Advances in Data and Information Systems Vol. 5 No. 1 (2024): April 2024 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v5i1.1309

Abstract

The objective of this article is to use machine learning technology, specifically the Support Vector Machine (SVM) approach with a linear kernel, to analyze and predict clean and healthy living behavior (CHLB) in coastal dwellings in Surabaya City. To train the SVM model, researchers collect health and environmental data from the region. As a result, our model predicts house CHLB status with an 83% accuracy rate. The most important variables in this prediction are the amount of community access to appropriate sanitary facilities, the health of households, and the sustainability of public areas that meet health requirements. These findings have crucial implications for attempts to improve CHLB in Surabaya's coastal areas in compliance with the National Medium-Term Development Plan (RPJMN) aims. Furthermore, the findings of this study can be used to build more targeted and long-term health policies in coastal communities.
Classification of Students' Academic Performance Using Neural Network and C4.5 Model Sulika Sulika; Ririen Kusumawati; Yunifa Miftachul Arif
International Journal of Advances in Data and Information Systems Vol. 5 No. 1 (2024): April 2024 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v5i1.1311

Abstract

ducation involves deliberately creating an environment and learning process to empower students to fully utilize their academic and non-academic potential. It encompasses fostering spiritual qualities, religious understanding, self-discipline, cognitive abilities, and skills necessary for personal, societal, national, and state development. Madrasah Aliyah, in particular, emphasizes preparing participants for higher studies in areas of their interest, thereby showcasing their academic prowess. The evaluation of educational models like Neural Networks is crucial for ensuring their effectiveness in problem-solving. This involves testing and assessing the performance of the Neural Network model to ensure its accuracy and reliability. Similarly, the C4.5 method, based on condition data mining, is utilized to measure classification performance by assessing accuracy, precision, and recall. Research findings indicate that the neural network algorithm is more adept at accurately classifying students' academic abilities compared to the C4.5 algorithm. With an accuracy of 92.6% for the neural network algorithm and 80.6% for the C4.5 algorithm, it is evident that the former is more precise in determining the classification of students' academic abilities. This highlights the suitability of the neural network approach for classifying academic abilities in Madrasah Aliyah. Furthermore, the insights gained from this classification process can be extrapolated to benefit other madrasas.
Integrated Multi-Income Stream Performance Dashboard: a Japanese Corporate Banking Case Krisnhu Hananta Rachansa; Wasesa Meditya
International Journal of Advances in Data and Information Systems Vol. 5 No. 1 (2024): April 2024 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v5i1.1313

Abstract

In response to the complex operational challenges faced by Japanese Corporate Banking (JCB), arising from the coexistence of disparate core banking systems post-merger, this study aims to address inherent issues affecting marketing performance monitoring. The existing condition at JCB is characterized by data inconsistency, limited system interoperability, and fragmented income tracking through multiple Excel reports and management systems. Recognizing the gaps in the current setup, the research question revolves around how to enhance marketing performance monitoring effectively. The research objectives, therefore, encompass the development and implementation of a tailored integrated report utilizing the CRISP-DM methodology. This innovative performance dashboard harmoniously consolidates data from diverse sources, presenting a cohesive representation crucial for comprehensive marketing performance assessment. Leveraging advanced methodologies like data normalization and cross-platform integration, the research approach ensures streamlined income tracking, mitigating existing limitations. The data, drawn from various product applications, undergoes meticulous processing to facilitate a unified view on the integrated dashboard. The anticipated result is a significant improvement in monitoring efficiency, heightened data accuracy, and an empowered decision-making process within JCB's operations. The business implication of this initiative is the tangible enhancement of the bank's ability to comprehensively assess income performance, thereby elevating the quality of strategic decision-making and reinforcing JCB's competitive positioning in the banking sector.
Managing Inherent IT Business Risk against Cyber Threats: a Decision Analysis Case Study of an Oil and Gas Company I Wayan Novit Marhaendra Putra; Meditya Wasesa
International Journal of Advances in Data and Information Systems Vol. 5 No. 1 (2024): April 2024 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v5i1.1315

Abstract

XYZ, an anonymized oil and gas company, aims to enhance cyber resilience by strategically managing inherent risk profiles in cybersecurity, aligned with business needs and stakeholder expectations. This research addresses challenges including Information Security Control determination, proficiency improvement in risk management, and ISMS preparedness. Additionally, it tackles procurement strategy for Security Operations Control across XYZ Group, operating under PSC Gross Split, Cost Recovery, and Non-PSC statuses. Utilizing diverse frameworks such as problem tree analysis, stakeholders’ power-interest matrix, MITRE ATT&CK, NIST 800-53, COBIT 2019, ISO 27005:2022, KAMI 5.0, and SMART, data analysis includes risk documents, interviews, and cyber-attack data. The research establishes effective IS Control for risk mitigation, readiness for Information Security Management System ISMS implementation, strategic programs enhancing risk management capability, and refined Security Operations Control procurement. These outcomes, incorporated into a collaborative contract structure, significantly mitigate cyber threats and potential impacts, such as disruptions to operations, revenue reduction, increased costs, data theft, and non-compliance.
Recommendation of Prospective Construction Service Providers in Government Procurement Using Decision Tree Eva Yustina; Mokhamad Amin Hariyadi; Cahyo Crysdian
International Journal of Advances in Data and Information Systems Vol. 5 No. 1 (2024): April 2024 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v5i1.1316

Abstract

The determination of prospective construction service providers using the direct procurement method is the authority of the Goods/ Services Procurement Officer. Administrative requirements are an important factor in selecting prospective construction service providers. The use of the decision tree method in this study is to find out, determine, and analyse the variables that influence the assessment of the feasibility of prospective construction service providers, and get an accuracy value in providing an assessment of the feasibility of prospective construction service providers. The data used in this study are 153 datasets consisting of 13 variables. The existing variables are divided into basic variables and additional variables. The basic variables consist of 5 variables, namely experts, work experience, quality of work, winning tenders and contract value. While the additional variables consist of 8 variables namely business entity status, business entity form, business entity NPWP, business entity domicile, business entity qualification, type of business licence, percentage of work and construction services business licence. By using the decision tree method, the accuracy on the basic variable is 84.84%. The addition of additional variables to the basic variables resulted in an accuracy of 90.91%. This shows that by adding additional variables the accuracy results are higher than using only the basic variables.

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