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International Journal of Advances in Intelligent Informatics
International journal of advances in intelligent informatics (IJAIN) e-ISSN: 2442-6571 is a peer reviewed open-access journal published three times a year in English-language, provides scientists and engineers throughout the world for the exchange and dissemination of theoretical and practice-oriented papers dealing with advances in intelligent informatics. All the papers are refereed by two international reviewers, accepted papers will be available on line (free access), and no publication fee for authors.
Articles
49
Articles
Systematic feature analysis on timber defect images

Hashim, Ummi Rabaah, Mohd Hashim, Siti Zaiton, Muda, Azah Kamilah, Kanchymalay, Kasturi, Abd Jalil, Intan Ermahani, Othman, Muhammad Hakim

International Journal of Advances in Intelligent Informatics Vol 3, No 2 (2017): July 2017
Publisher : Universitas Ahmad Dahlan

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Abstract

Feature extraction is unquestionably an important process in a pattern recognition system. A defined set of features makes the identification task more efficiently. This paper addresses the extraction and analysis of features based on statistical texture to characterize images of timber defects. A series of procedures including feature extraction and feature analysis was executed to construct an appropriate feature set that could significantly separate amongst defects and clear wood classes. The feature set aimed for later use in a timber defect detection system. For Accessing the discrimination capability of the features extracted, visual exploratory analysis and confirmatory statistical analysis were performed on defect and clear wood images of Meranti (Shorea spp.) timber species. Results from the analysis demonstrated that there was a significant distinction between defect classes and clear wood utilizing the proposed set of texture features.

Performance IEEE 802.14.5 and zigbee protocol on realtime monitoring augmented reality based wireless sensor network system

Editya, Arda Surya, Sumpeno, Surya, Pratomo, Istas

International Journal of Advances in Intelligent Informatics Vol 3, No 2 (2017): July 2017
Publisher : Universitas Ahmad Dahlan

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Abstract

The internet of Thing (IoT)technology has much development in this era. It has various wireless media transmission systems such as ESP and XBEE. Some IoT device can monitor website or application. On the other hand, Augmented Reality (AR) is a technology that used more on the entertainment sector. Here, we try to use AR to monitor the xbee based IoT device. As a result, there is the different result between Zigbee Protocol and IEEE 802.14.5 real time monitoring system. The optimum estimation of realtime time tolerance of those monitoring systems is >1500 ms (IEEE 804.14.5) and > 50 ms (Zigbee protocol).

Wavelet discrete transform, ANFIS and linear regression for short-term time series prediction of air temperature

Munandar, Devi

International Journal of Advances in Intelligent Informatics Vol 3, No 2 (2017): July 2017
Publisher : Universitas Ahmad Dahlan

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Abstract

This paper investigates the ability of Discrete Wavelet Transform and Adaptive Network-Based Fuzzy Inference System in time-series data modeling of weather parameters. Plotting predicted data results on Linear Regression is used as the baseline of the statistical model. Data were tested in every 10 minutes interval on weather station of Bungus port in Padang, Indonesia. Mean absolute errors (MAE), the coefficient of determination (R2), Pearson correlation coefficient (r) and root mean squared error (RMSE) are used as performance indicators. The result of Plotting ANFIS data against linear regression using 1-input data is the optimal values combination of output predictions.

K-Means cluster analysis in earthquake epicenter clustering

Novianti, Pepi, Setyorini, Dyah, Rafflesia, Ulfasari

International Journal of Advances in Intelligent Informatics Vol 3, No 2 (2017): July 2017
Publisher : Universitas Ahmad Dahlan

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Abstract

Bengkulu Province, Indonesia, which lies in two active faults, Semangko fault and Mentawai fault, is an area that has high seismic activity. As earthquake-prone area, the characteristic of each earthquake in Bengkulu Province needs to be studied. This paper presents the earthquake epicenter clustering in Bengkulu Province. Tectonic earthquake data at Bengkulu Province and surrounding areas from January 1970 to December 2015 are used. The data is taken from single-station Agency Meteorology, Climatology and Geophysics (BMKG) Kepahiang Bengkulu. K-Means clustering using Euclidean distance method is used in this analysis. The variables are latitude, longitude and magnitude. The optimum number of cluster is determined using Krzanowski and Lai (KL) index which is 7. The analysis for each clustering experiment with variation number of cluster is presented.

Circular(2)-linear regression analysis with iteration order manipulation

Nurhab, Muhamad Irpan, Nurhab, Badaruddin, Purwaningsih, Tuti, Teng, Ming Foey

International Journal of Advances in Intelligent Informatics Vol 3, No 2 (2017): July 2017
Publisher : Universitas Ahmad Dahlan

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Abstract

The development of data analysis still predominantly uses linear statistics. Whereas the research world there are other types of data is data direction. One type of data direction is the data circular. The statistical analysis aimed at modelling the causal relationship between the independent variable and the dependent variable is regression analysis. So, as to model, the relationship between wind direction and cloud direction against rainfall is circular–linear-multiple regression analysis. The purpose of this research is to build a model of circular–linear regression analysis of m order with circular variable α and β against linear variable (Y). This research used the simulation data, seen from the sum square of error, p-value, and r-square.

Spatial data modeling in disposable income per capita in china using nationwide spatial autoregressive (SAR)

Purwaningsih, Tuti, Ghosh, Anusua, Chumairoh, Chumairoh

International Journal of Advances in Intelligent Informatics Vol 3, No 2 (2017): July 2017
Publisher : Universitas Ahmad Dahlan

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Abstract

China is a country that became the economic centre of the world. The factors that play an important role in the economic progress in China is industrial factors: Per Capita Disposable Income Nationwide, Total Value of Exports of operating units, Registered Unemployed Persons in Urban Area, and Number of Industrial Enterprises and tourism factors. However, the prosperity among 1.3 billion of the population, is unequal. Thus, it is necessary to investigate the extent to which these factors influence the per capita income. Since the economic development of a region usually affects the surrounding area, this study includes the Spatial Autoregressive Model (SAR) method.

Human action recognition using support vector machines and 3D convolutional neural networks

Latah, Majd

International Journal of Advances in Intelligent Informatics Vol 3, No 1 (2017): March 2017
Publisher : Universitas Ahmad Dahlan

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Abstract

Recently, deep learning approach has been used widely in order to enhance the recognition accuracy with different application areas. In this paper, both of deep convolutional neural networks (CNN) and support vector machines approach were employed in human action recognition task. Firstly, 3D CNN approach was used to extract spatial and temporal features from adjacent video frames. Then, support vector machines approach was used in order to classify each instance based on previously extracted features. Both of the number of CNN layers and the resolution of the input frames were reduced to meet the limited memory constraints. The proposed architecture was trained and evaluated on KTH action recognition dataset and achieved a good performance.

Vehicle pose estimation for vehicle detection and tracking based on road direction

Prahara, Adhi, Azhari, Ahmad, Murinto, Murinto

International Journal of Advances in Intelligent Informatics Vol 3, No 1 (2017): March 2017
Publisher : Universitas Ahmad Dahlan

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Abstract

Vehicle has several types and each of them has different color, size, and shape. The appearance of vehicle also changes if viewed from different viewpoint of traffic surveillance camera. This situation can create many possibilities of vehicle poses. However, the one in common, vehicle pose usually follows road direction. Therefore, this research proposes a method to estimate the pose of vehicle for vehicle detection and tracking based on road direction. Vehicle training data are generated from 3D vehicle models in four-pair orientation categories. Histogram of Oriented Gradients (HOG) and Linear-Support Vector Machine (Linear-SVM) are used to build vehicle detectors from the data. Road area is extracted from traffic surveillance image to localize the detection area. The pose of vehicle which estimated based on road direction will be used to select a suitable vehicle detector for vehicle detection process. To obtain the final vehicle object, vehicle line checking method is applied to the vehicle detection result. Finally, vehicle tracking is performed to give label on each vehicle. The test conducted on various viewpoints of traffic surveillance camera shows that the method effectively detects and tracks vehicle by estimating the pose of vehicle. Performance evaluation of the proposed method shows 0.9170 of accuracy and 0.9161 of balance accuracy (BAC).

Exploring natural language understanding in robotic interfaces

Giachos, Ioannis, Papakitsos, Evangelos C., Chorozoglou, Georgios

International Journal of Advances in Intelligent Informatics Vol 3, No 1 (2017): March 2017
Publisher : Universitas Ahmad Dahlan

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Abstract

Natural Language Understanding is a major aspect of the intelligence of robotic systems. A main goal of improving their artificial intelligence is to allow a robot to ask questions, whenever the given instructions are not complete, and also by using implicit information. These enhanced communicational abilities can be based on the voids of an output data structure that corresponds to a systemic-semantic model of language communication, as grammar formalism. In addition, the enhancing process also improves the learning abilities of a robot. Accordingly, the presented herein experimental project was conducted by using a simulated (by a plain PC) robot and a simple constructed language that facilitated semantic orientation.

Review implementation of linguistic approach in schema matching

Martono, Galih Hendro, SN, Azhari

International Journal of Advances in Intelligent Informatics Vol 3, No 1 (2017): March 2017
Publisher : Universitas Ahmad Dahlan

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Abstract

Research related schema matching has been conducted since last decade. Few approach related schema matching has been conducted with various methods such as neuron network, feature selection, constrain based, instance based, linguistic, and so on. Some field used schema matching as basic model such as e-commerce, e-business and data warehousing. Implementation of linguistic approach itself has been used a long time with various problem such as to calculated entity similarity values in two or more schemas. The purpose of this paper was to provide an overview of previous studies related to the implementation of the linguistic approach in the schema matching and finding gap for the development of existing methods. Futhermore, this paper focused on measurement of similarity in linguistic approach in schema matching.