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International Journal of Artificial Intelligence Research

IJAIR
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Published by STMIK Dharma Wacana

ISSN : - EISSN : 25797298 DOI : -

Core Subject : Science, Engineering,

Computer Science & IT Electrical & Electronics Engineering

International Journal Of Artificial Intelligence Research (IJAIR) is a peer-reviewed open-access journal. The journal invites scientists and engineers throughout the world to exchange and disseminate theoretical and practice-oriented topics of Artificial intelligent Research which covers four (4) majors areas of research that includes 1) Machine Learning and Soft Computing, 2) Data Mining & Big Data Analytics, 3) Computer Vision and Pattern Recognition, and 4) Automated reasoning. Submitted papers must be written in English for initial review stage by editors and further review process by minimum two international reviewers.

Arjuna Subject : -

Articles 621 Documents

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Design and Analysis of an Intelligent Integrity Checking Watermarking Scheme for Ubiquitous Database Access Darwish, Saad Mohamed; Selim, Hosam A.
International Journal of Artificial Intelligence Research Vol 3, No 1 (2019): June 2019
Publisher : Universitas Dharma Wacana

As a result of the highly distributed nature of ubiquitous database accessing, it is essential to develop security mechanisms that lend themselves well to the delicate properties of outsourcing databases integrity and copyright protection. Researchers have begun to study how watermarking computing can make ubiquitous databases accessing more confident work environments. One area where database context may help is in supporting content integrity. Initially, most of the research effort in this field was depending on distortion based watermark while the few remaining studies concentrated on distortion-free. But there are many disadvantages in previous studies; most notably some rely on adding watermark as an extra attributes or tuples, which increase the size of the database. Other techniques such as permutation and abstract interpretation framework require much effort to verify the watermark. The idea of this research is to adapt an optimized distortion free watermarking based on fake tuples that are embedded into a separate file not within the database to validate the content integrity for ubiquitous database accessing. The proposed system utilizes the GA, which boils down its role to create the values of the fake tuples as watermark to be the closest to real values. So that it's very hard to any attacker to guess the watermark. The proposed technique achieves more imperceptibility and security. Experimental outcomes confirm that the proposed algorithm is feasible, effective and robust against a large number of attacks.

A modeling approach for short-term load forcasting using fuzzy logic type-2 in sulselrabar system Muhammad Ruswandi Djalal
International Journal of Artificial Intelligence Research Vol 3, No 1 (2019): June 2019
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v3i1.68

This research proposed a modeling approach for 24-hour short-term load forcasting based on fuzzy logic type-2. In this research we get an approach in designing load forecasting model, where previously still using conventional fuzzy logic. Implementation of load forecasting in this research is done on electrical system 150 kV Sulselrabar. Sulselrabar electrical system in its development has grown rapidly, therefore needed a study that to improve system performance, one of which is the study of short-term load forcasting. As the input data used load data from 2010 to 2016 on the same day that is January 8th. To see the accuracy of the results, two approaches are performed, ie fuzzy logic type-1 modeled using Simulink and fuzzy logic type-2 modeled using m-file Matlab. From the analysis results obtained, Mean Percentage Error (MAPE) is the smallest by using Fuzzy Logic Type-2 method, compared with Fuzzy Logic Type-1 method.. Where, MAPE for fuzzy logic type-1 method is 2.133371219%, and by using fuzzy logic type-2 method, MAPE is 1.729778866%.

Machine Learning Based Prediction versus Human-as-a-Security-Sensor Haque, Safwana
International Journal of Artificial Intelligence Research Vol 3, No 1 (2019): June 2019
Publisher : Universitas Dharma Wacana

Phishing is one of the most common cyber threats in the world today. It is a type of social engineering attack where the attacker lures unsuspecting victims into carrying out certain tasks mostly to steal personal and sensitive information. These stolen information are exploited to commit further crimes e.g. blackmails, data theft, financial theft, malware installation etc. This study was carried out to tackle this problem by designing an anti-phishing learning algorithm to detect phishing emails and also to study the accuracies of human phishing prediction to machine prediction. A graphical user interface was designed to emulate an email-client system that popped-up a warning on detecting a phishing mail successfully and collection of predictions made by expert and non-expert users on anti-phishing techniques. These predictions were compared to the predictions made by the machine learning algorithm to compare the efficiencies of all predictions considered in this research. The performance of the classifier used was measured with metrics such as confusion matrix, accuracy, receiver operating characteristic curve and area under graph

The Implementation of AHP for Determining Dominant Criteria in Higher Education Competitiveness Development Strategy Based on Information Technology Yulmaini, Yulmaini; Sanusi, Anuar; Yusendra, M. Ariza Eka
International Journal of Artificial Intelligence Research Vol 3, No 1 (2019): June 2019
Publisher : Universitas Dharma Wacana

The existence of Higher Education has a huge role in nation and stateâ€™s life through tri dharma of Higher Education named education, research and community service. Higher Education can produce economic innovations based on knowledge so that, it will increase productivity and nation competitiveness. Higher Education must have strategies that will be carried out, therefore they are able to compete with other higher education according to stakeholder needs. The purposes of this research are to analyze 2 (two) models of information technology relations in the higher education competitiveness development strategy determining the most dominant criteria according to the higher education development direction (Relevance, Academic Atmosphere, Internal Management, Sustainability, Efficiency and Productivity, Access and Equit and Leadership). The method of this reserach is AHP method in wich the data are collected through questionnaires to respondents in collage. The criteria of this research are internal management & organization, academic atmosphere and university competitive sustainability. The results of this research are the information technology relations model with internal management, and the relation model between internal management and efficiency & productivities, and also the most dominant criteria in the higher education competitiveness development strategy are the criteria of Academic Atmosphere, Efficiency and Productivity.

Quantum Inspired Genetic Programming Model to Predict Toxicity Degree for Chemical Compounds Darwish, Saad Mohamed
International Journal of Artificial Intelligence Research Vol 3, No 1 (2019): June 2019
Publisher : Universitas Dharma Wacana

Cheminformatics plays a vital role to maintain a large amount of chemical data. A reliable prediction of toxic effects of chemicals in living systems is highly desirable in domains such as cosmetics, drug design, food safety, and manufacturing chemical compounds. Toxicity prediction topic requires several new approaches for knowledge discovery from data to paradigm composite associations between the modules of the chemical compound; such techniques need more computational cost as the number of chemical compounds increases. State-of-the-art prediction methods such as neural network and multi-layer regression that requires either tuning parameters or complex transformations of predictor or outcome variables are not achieving high accuracy results.Â This paper proposes a Quantum Inspired Genetic Programming â€œQIGPâ€ model to improve the prediction accuracy. Genetic Programming is utilized to give a linear equation for calculating toxicity degree more accurately. Quantum computing is employed to improve the selection of the best-of-run individuals and handles parsimony pressure to reduce the complexity of the solutions. The results of the internal validation analysis indicated that the QIGP model has the better goodness of fit statistics and significantly outperforms the Neural Network model.

An Inflation Rate Prediction Based on Backpropagation Neural Network Algorithm Purnawansyah, Purnawansyah; Haviluddin, Haviluddin; Setyadi, Hario Jati; Wong, Kelvin; Alfred, Rayner
International Journal of Artificial Intelligence Research Vol 3, No 2 (2019): December 2019
Publisher : Universitas Dharma Wacana

This article aims to predict the inflation rate in Samarinda, East Kalimantan by implementing an intelligent algorithm, Backpropagation Neural Network (BPNN). The inflation rate data was obtained from the Provincial Statistics Bureau of Samarinda https://samarindakota.bps.go.id/ for the period January 2012 to January 2017. The method used to measure accuracy algorithm prediction was the mean square error (MSE). Based on the experiment results, the BPNN method with architectural parameters of 5-5-5-1; the learning function was trainlm; the activation functions were logsig and purelin; the learning rate was 0.1 and able to produce a good level of prediction error with an MSE value of 0.00000424. The results showed that the BPNN algorithm can be used as an alternative method in predicting inflation rates in order to support sustainable economic growth, so that it can improve the welfare of the people in Samarinda, East Kalimantan.

Journal ClassificationÂ UsingÂ Cosine SimilarityÂ MethodÂ on Title and Abstract withÂ Frequency-BasedÂ Stopword RemovalÂ Nurfadila, Piska Dwi; Wibawa, Aji Prasetya; Zaeni, Ilham Ari Elbaith; Nafalski, Andrew
International Journal of Artificial Intelligence Research Vol 3, No 2 (2019): December 2019
Publisher : Universitas Dharma Wacana

Classification of economic journal articles has been done using the VSM (Vector Space Model) approach and the Cosine Similarity method. The results of previous studies are considered to be less optimal because Stopword Removal was carried out by using a dictionary of basic words (tuning). Therefore, the omitted words limited to only basic words. This study shows the improved performance accuracy of the Cosine Similarity method using frequency-based Stopword Removal. The reason is because the term with a certain frequency is assumed to be an insignificant word and will give less relevant results. Performance testing of the Cosine Similarity method that had been added to frequency-based Stopword Removal was done by using K-fold Cross Validation. The method performance produced accuracy value for 64.28%, precision for 64.76 %, and recall for 65.26%. The execution time after pre-processing was 0, 05033 second.

Solution of class imbalance of k-nearest neighbor for data of new student admission selection Siti Mutrofin; Ainul Mu'alif; Raden Venantius Hari Ginardi; Chastine Fatichah
International Journal of Artificial Intelligence Research Vol 3, No 2 (2019): December 2019
Publisher : STMIK Dharma Wacana

The objective of this research is to correct the inconsistencies associated with the response differences by each examiner with respect to the assessment of each hafiz candidate. To carry out this research, 259 students were selected within a week using 4testers. However, the examiners are also tasked with another essential mandate which must be immediately fulfilled asides testing candidates for hafiz. In order to overcome this problem, the Educational Data Mining (EDM) system is applied during classification. The problems associated with the use of this technique however, is the limited number of attributes and the imbalance data class. This study was proposed to apply the kNN (k-Nearest Neighbor) technique. The results obtained indicates that kNN can provide recommendations to testers who are students and it is suitable for the solving the problem associated with class imbalance as indicated by the application of Shuffled and Stratified sampling techniques which has values of accuracy, precision, recall and AUC > 0.8%.

Design of a-based smart meters to monitor electricity usage in the household sector using hybrid particle swarm optimization - neural network Yunus, Muhammad Yusuf; Marhatang, Marhatang; Pangkung, Andareas; Djalal, Muhammad Ruswandi
International Journal of Artificial Intelligence Research Vol 3, No 2 (2019): December 2019
Publisher : Universitas Dharma Wacana

The procedure is training and testing the nerves that will be made. Matlab software has a Neural Network tool, which in this study will be used. Load sampling data is used as input data for neural network training. As output / target load classification is used. Load classification method, which is 1 for TV load classification, 2 for fan load, 3 for iron load, 4 for water pump load, 5 for lamp load, 6 for dispenser load, and 7 for fan iron load combination. The total load is 6 single loads and 1 combination load. One load combination was chosen because, on the combination load characteristics after the fan has characteristics that are not the same as the others. Data sampling of the current of each load will be used as neural network training. Load data used is 30 samples or for 30 seconds, with every minute the data is taken. From the results of the training, it can be seen that the biggest training error is in the seventh data, namely the identification of the load on the classification of the fan-iron load. This is because the current pattern on the iron and fan with the iron or fan itself has almost the same characteristics. However, for this process networks will be used and then the PSO optimization method is used to reduce the error, in the next study. From the test results, it is shown that by varying the input current data of each load, the network has been able to identify well, even though in the data classification load 7, the load of the iron-fan combination still has a large error. This will be corrected in subsequent studies with Particle Swarm Optimization (PSO) algorithm optimization.

A protocol for Enhanced imaging and Quantification of Cervical Cell Under Scanning electron Microscope Jusman, Yessi; Jamal, Agus; Valzon, May; Hasikin, Khairunnisa; Cheok Ng, Siew
International Journal of Artificial Intelligence Research Vol 3, No 2 (2019): December 2019
Publisher : Universitas Dharma Wacana

The application of Field Emission Scanning Electron Microscopy and Energy Dispersive X-Ray (FE-SEM/EDX) for the characterization of biological samples can produce promising results for classification purpose. The limitations of the established sample preparation technique of cervical cells for FE-SEM/EDX study that differentiate between normal and abnormal cells prompted the development of a proposed protocol for the preparation of cervical cells. The proposed protocol was conducted by a McDowell-Trump fixative prepared in 0.1M phosphate buffer without osmium tetroxide at 4Â°C for 2 h in the fixation process. Morphologically, the cervical cells scanned under the FE-SEM/EDX did not present blackening effects, and the structure of the cells was not broken based on the FE-SEM images. Quantitatively, the possible elemental distributions in the cells, such as carbon, nitrogen, oxygen, and sodium, are detected in samples prepared by the proposed protocol. The analysed elements were validated using the Attenuated Total Reflection and Fourier Transform Infrared (ATR/FTIR) spectroscopy. Moreover, by avoiding osmium tetroxide fixation, the time required for sample preparation decreased significantly. This sample preparation protocol can be used for normal and abnormal cervical cells in achieving better results in terms of morphological, detected elemental distribution, and rapid in time.

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Contact Name
Heri Nurdiyanto

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Heri Nurdiyanto

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Journal Mail Official
internationaljournalair@gmail.com

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Location
Kota metro,

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INDONESIA