International Journal of Artificial Intelligence Research

Journal Information
EISSN : 2579-7298
Published by: STMIK Dharma Wacana (10.29099)
Total articles ≅ 68
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Latest articles in this journal

Inta Budi Setya Nusa,
International Journal of Artificial Intelligence Research, Volume 5, pp 200-204;

This present study at identifying the influence of information technology toward the use of e-Filing and the influence of perception of usefulness toward the use of e-Filing. The research method used is descriptive and verification with quantitative approach. The data used is primary data, while data collection techniques used are field research and library research. The sample in this research are 34 individual taxpayers of Weat Java Provincial Secretariat Office. The analysis model used is SEM PLS. The results of this study show that information technology has an effect on the use of e-Filingand usability perception has an effect on the use of e-Filing
International Journal of Artificial Intelligence Research, Volume 5, pp 138-156;

IT Service Management (ITSM) is a framework used to support businesses by increasing IT service quality. Several studies have tried to examine the development of ITSM based on their respective interests. However, the development of ITSM in Indonesia has not been widely studied, such as the types of research that are most often investigated, what domains are often researched, the areas and types of companies being studied. The things above are the main objectives of this research. The method used in capturing data, screening, and analysis is the systematic literature review method. There are many findings obtained from this research. One of them is the domination of the service operation research area (45%) among other areas. Meanwhile, applied research had been researched quite consistently over the last five years. From these results, it can be noticed that a deeper understanding of the synchronization between business and IT is needed. This is in accordance with the objectives of ITSM implementation so that future research is expected to provide balance in other areas, such as service strategy, design, transition, operation, and continuous service improvement.
International Journal of Artificial Intelligence Research, Volume 5, pp 123-131;

Artificial neural networks (ANN) are now widely used and are becoming popular among researchers, especially in the geotechnical field. In general, data normalization is carried out to make ANN whose range is in accordance with the activation function used. Other studies have tried to create an ANN without normalizing the data and ANN is considered capable of making predictions. In this study, a comparison of ANN with and without data normalization was carried out in predicting SPT values based on CPT data and soil physical properties on cohesive soils. The input data used in this study are the value of tip resistance, sleeve resistance, effective soil overburden pressure, liquid limit, plastic limit and percentage of sand, silt and clay. The results showed that the ANN was able to make predictions effectively both on networks with and without data normalization. In this study, it was found that the ANN without data normalization showed a smaller error value than the ANN with data normalization. In the network model without data normalization, RMSE values were 3.024, MAE 1.822, R2 0.952 on the training data and RMSE 2.163, MAE 1.233 and R2 0.976 on the test data. Whereas in the ANN with data normalization, the RMSE values were 3.441, MAE 2.318, R2 0.936 in the training data and RMSE 2.785, MAE 2.085 and R2 0.963 in the test data. ANN with normalization provides a simpler architecture, which only requires 1 hidden layer compared to ANN without normalization which requires 2 hidden layer architecture.
Mardison Mardison, Sarjon Defit, Shaza Alturky
International Journal of Artificial Intelligence Research, Volume 5;

Obtaining a scholarship is the desire of every student or student who studies, especially those who come from poor families. The scholarship can lighten the burden on parents who pay for these students and can streamline the lecture process. However, students do not know exactly what they have to do to get the scholarship. Aside from that, students naturally want to know what causes and conditions have the greatest impact on achievement. The objective of this research is how to predict which number of students among them are predicted to get a scholarship at the opening of the scholarship acceptance using the K-Means and C4.5 methods. Apart from that, the aim of this research is to discover how the K-Means algorithm conducts data clustering (clustering) of student data to determine if they will succeed or not, as well as how the C4.5 algorithm makes predictions against students who have been clustered together. The Rapid Miner program version 9.7.002 was used to process the data in this report. The results of this study were that out of 100 students, 32 students were not scholarship recipients and 68 students were scholarship recipients. Another result of this research is that out of 100 students it is predicted that 9 (9%) will receive scholarships and 91 (91%) will not receive scholarships.
International Journal of Artificial Intelligence Research, Volume 5, pp 190-199;

Electronic administration system is one of the best solutions in the current digital era, electronic-based systems are considered to make it easier for an organization to process data and can reduce the possibility of data loss due to human error or natural disasters. The current administrative data management application is called the Electronic Office (E-Office). The E-Office handles data for incoming mail, outgoing mail and mail disposition. There are frequent delays in receiving information and validating letter files that are still carried out using physical files, so the mobile e-office is a solution that can be used by an agency to make it easier for workers to access information more quickly and can be done anywhere. Data security is an important thing that needs to be considered in an electronic transaction, so this research will add data security to the mobile e-office using sha-256 and lamport schemes. We present data on the results of this mobile e-office test on mobile devices and virtual private servers (vps), the data is in the form of functional application performance testing results and records of processing time performed by mobile and vps devices. From this data an analysis will be carried out to determine the appropriateness of the devices that can be used in running a mobile e-office.
Wulan Stau Fana, Rini Sovia, Randi Permana, Ataul Islam
International Journal of Artificial Intelligence Research, Volume 5;

Data Warehouse is a technology use to analyze, extract and evaluate data into information which produce knownledge in the form of analysis to provide an advice in decision making process. Designing a Data Warehouse using ETL (Extract, Transformation and Load) process serves as the collection of data from different data sources into a multitude of integrated data sets. By using snowflake scheme for the design of the data warehouse make data prepare well and ready for analyze on Data Warehouse. The result of this reseach is to applied Data Warehouse that use to support company decision making progress make easier and has a good decision since its come from Data Warehouse
International Journal of Artificial Intelligence Research, Volume 5, pp 205-209;

The availability of certified seeds is a very important strategy to maintain food security. When farmers plant their farms with certified seeds, it can increase the production yields grown by farmers. To answer the availability of sources according to the needs of farmers or consumers, it is necessary to design an information system for forecasting the demand for certified seeds, with a methodology Rational Unified Process (RUP) so that this method can be useful to identify the system that is running and can describe the system to be built. Meanwhile, to produce an estimate of the demand for certified seeds, a linear regression approach will be used which will be included in the design of the system. The design of this system will produce a function to assist producer farmers in estimating certified seed production, assisting the availability of certified seed information for consumers, and assisting the PSBTPH Installation in the Subang Region in carrying out evaluation and monitoring.
International Journal of Artificial Intelligence Research, Volume 5, pp 157-167;

Distributed Denial of Service or better known as DDoS is an attempted attack from several computer systems that target a server so that the amount of traffic becomes too high so that the server cannot handle the request. DDoS is usually done by using several computer systems that are used as sources of attacks. So they attack one server through several computers so that the amount of traffic can also be higher. A DDoS attack is like a traffic jam that prevents a driver from reaching their desired destination on time. According to data, 33% of businesses in the world have fallen victim to DDoS attacks. DDoS is hard to trace. Some types of DDoS attacks can be very powerful and even reach speeds of 1.35 Tbps. Additionally, DDoS attacks can cause losses of $ 40,000 per hour if they occur. ZigBee is a standard from IEEE 802.15.4 for data communication on personal consumer devices as well as for business scale. ZigBee is designed with low power consumption and works for low level personal networks. ZigBee devices are commonly used to control another device or as a wireless sensor. ZigBee has a feature which is able to manage its own network, or manage data exchange on the network [1]. Another advantage of ZigBee is that it requires low power, so it can be used as a wireless control device which only needs to be installed once, because only one battery can make ZigBee last up to a year. In addition, ZigBee also has a "mesh" network topology so that it can form a wider network and more reliable data. In the previous research of Muhammad Aziz, Rusydi Umar, Faizin Ridho (2019) based on the results of the analysis carried out that the attack information that has been detected by the IDS based on signatures needs to be reviewed for accuracy using classification with statistical calculations. Based on the analysis and testing carried out with the artificial neural network method, it was found that the accuracy was 95.2381%. The neural network method can be applied in the field of network forensics in determining accurate results and helping to strengthen evidence at trial. The Naïve Bayes model performed relatively poor overall and produced the lowest accuracy score of this study (45%) when trained with the CICDDoS2019 dataset [47]. For the same model, precision was 66% and recall was 54%, meaning that almost half the time, the model misses to identify threats.
International Journal of Artificial Intelligence Research, Volume 5, pp 180-189;

Getting academic achievement is the dream of every student who studies at higher education, especially undergraduate level. Undergraduate students aspire to the highest achievement (champion) at the last achievement of their studies. However, students cannot predict whether these students with the habits that have been done and the current conditions will make them excel or not. Apart from that, of course, students also want to know what factors and conditions influence the achievement the most. The objective to be achieved in this research is how to predict which number of students among them are predicted to excel (champion) at the end of the semester with a combination of the K-Means and C4.5 methods. Besides, the purpose of this study reveals how the K-Means algorithm performs data clustering of student data who will excel or not and how the C4.5 algorithm predicts students who have been grouped. Data processing in this study uses the Rapid Miner software version 9.7.002. The result of this research is that it is easier to group data in numerical form than data in polynomial form. Other results in this study were that out of 100 students, 27 students (27%) were predicted to excel (champions) and 73 (73%) did not achieve (not champions).
International Journal of Artificial Intelligence Research, Volume 5, pp 111-122;

The outbreak of coronavirus disease (COVID-19) has forced major countries to apply strict policy toward society. People must wear a facemask and always keep their distance from each other's to avoid virus contamination. Government employ officers to monitor citizen and warn them if not wearing a face mask. The warning message also spread through SMS and social media to ensure people about safety and awareness. This paper aims to provide face mask detection using the Deep Learning Network(DLN) and warning system through video stream input from CCTV or images then analyzed. If people not wearing a mask are detected, they will alert them through the speaker and remind them about a penalty. AR distancing very useful to give position toward violator location based on the detected person in a certain area. The system is designed to work intelligently and automatically without human intervention. With the accuracy of 99% recognition, it's expected that the system can help the government to increase people awareness toward the safety of themselves and people around them.
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