cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota yogyakarta,
Daerah istimewa yogyakarta
INDONESIA
International Journal of Advances in Intelligent Informatics
Published by Universitas Ahmad Dahlan
ISSN : 24426571     EISSN : 25483161     DOI : 10.26555
Core Subject : Science,
Computer Science & IT
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.
Arjuna Subject : -
Articles 314 Documents
 1   2   3   4   5 
Automatic Text Summarization Using Latent Drichlet Allocation (LDA) for Document Clustering Erwin Yudi Hidayat; Fahri Firdausillah; Khafiizh Hastuti; Ika Novita Dewi; Azhari Azhari
International Journal of Advances in Intelligent Informatics Vol 1, No 3 (2015): November 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v1i3.43

Abstract

In this paper, we present Latent Drichlet Allocation in automatic text summarization to improve accuracy in document clustering. The experiments involving 398 data set from public blog article obtained by using python scrapy crawler and scraper. Several steps of clustering in this research are preprocessing, automatic document compression using feature method, automatic document compression using LDA, word weighting and clustering algorithm The results show that automatic document summarization with LDA reaches 72% in LDA 40%, compared to traditional k-means method which only reaches 66%.
Echo voltage reflected by turtle on various angles Sunardi Sunardi; Anton Yudhana; Azrul Mahfurdz; Sharipah Salwa Mohamed
International Journal of Advances in Intelligent Informatics Vol 1, No 1 (2015): March 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v1i1.9

Abstract

This research proposes the acoustic measurement by using echo sounder for green turtle detection of 1 year, 12 and 18 years. Various positions or angles of turtles are head, tail, shell, lung, left and right side. MATLAB software and echo sounder are used to analyse the frequency and the response of the turtle as echo voltage and target strength parameter. Based on the experiment and analysis have been conducted, the bigger size of the turtle, the higher echo voltage and target strength. The target strength of turtle for lung and shell for all ages are -26.52 dB and –26.17 dB respectively. The target strength of turtles in this research is different with target strength of fish in our previous research. Therefore, for future research, the repellant system based on differences of target strength the turtle and fish for avoided the turtle trapping in the net can be implemented to protect the population of turtle from extinction
Automatic differentiation based for particle swarm optimization Steepest descent direction Aris Thobirin; Iwan Tri Riyadi Yanto
International Journal of Advances in Intelligent Informatics Vol 1, No 2 (2015): July 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v1i2.29

Abstract

Particle swam optimization (PSO) is one of the most effective optimization methods to find the global optimum point. In other hand, the descent direction (DD) is the gradient based method that has the local search capability. The combination of both methods is promising and interesting to get the method with effective global search capability and efficient local search capability. However, In many application, it is difficult or impossible to obtain the gradient exactly of an objective function. In this paper, we propose Automatic differentiation (AD) based for PSODD. we compare our methods on benchmark function. The results shown that the combination methods give us a powerful tool to find the solution.
Short-term wind speed forecasting by an adaptive network-based fuzzy inference system (ANFIS): an attempt towards an ensemble forecasting method Moslem Yousefi; Danial Hooshyar; Amir Remezani; Khairul Salleh Mohamed Sahari; Weria Khaksar; Firas B. Ismail Alnaimi
International Journal of Advances in Intelligent Informatics Vol 1, No 3 (2015): November 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v1i3.45

Abstract

Accurate Wind speed forecasting has a vital role in efficient utilization of wind farms. Wind forecasting could be performed for long or short time horizons. Given the volatile nature of wind and its dependent on many geographical parameters, it is difficult for traditional methods to provide a reliable forecast of wind speed time series. In this study, an attempt is made to establish an efficient adaptive network-based fuzzy interference (ANFIS) for short-term wind speed forecasting. Using the available data sets in the literature, the ANFIS network is constructed, tested and the results are compared with that of a regular neural network, which has been forecasted the same set of dataset in previous studies. To avoid trial-and-error process for selection of the ANFIS input data, the results of autocorrelation factor (ACF) and partial auto correlation factor (PACF) on the historical wind speed data are employed. The available data set is divided into two parts. 50% for training and 50% for testing and validation. The testing part of data set will be merely used for assessing the performance of the neural network which guarantees that only unseen data is used to evaluate the forecasting performance of the network. On the other hand, validation data could be used for parameter-setting of the network if required. The results indicate that ANFIS could not outperform ANN in short-term wind speed forecasting though its results are competitive. The two methods are hybridized, though simply by weightage, and the hybrid methods shows slight improvement comparing to both ANN and ANFIS results. Therefore, the goal of future studies could be implementing ANFIS and ANNs in a more comprehensive ensemble method which could be ultimately more robust and accurate
Target threat assessment using fuzzy sets theory Ehsan Azimirad; Javad Haddadnia
International Journal of Advances in Intelligent Informatics Vol 1, No 2 (2015): July 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v1i2.18

Abstract

The threat evaluation is significant component in target classification process and is significant in military and non military applications. Small errors or mistakes in threat evaluation and target classification especial in military applications can result in huge damage of life and property. Threat evaluation helps in case of weapon assignment, and intelligence sensor support system. It is very important factor to analyze the behavior of enemy tactics as well as our surveillance. This paper represented a precise description of the threat evaluation process using fuzzy sets theory. A review has been carried out regarding which parameters that have been suggested for threat value calculation. For the first time in this paper, eleven parameters are introduced for threat evaluation so that this parameters increase the accuracy in designed system. The implemented threat evaluation system has been applied to a synthetic air defense scenario and four real time dynamic air defense scenarios. The simulation results show the correctness, accuracy, reliability and minimum errors in designing of threat evaluation system
RETRACTED: RCE-Kmeans Method for Data Clustering Izmy Alwiah Musdar; Azhari Azhari
International Journal of Advances in Intelligent Informatics Vol 1, No 2 (2015): July 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v1i2.38

Abstract

RETRACTEDFollowing a rigorous, carefully concerns and considered review of the article published in International Journal of Advances in Intelligent Informatics to article entitled “RCE-Kmeans Method for Data Clustering” Vol 1, No 2, pp. 107-114, July 2015, DOI: http://dx.doi.org/10.26555/ijain.v1i2.38.This paper has been found to be in violation of the International Journal of Advances in Intelligent Informatics Publication principles and has been retracted.The article contained redundant material, the editor investigated and found that the paper published in Indonesian Journal of Computing and Cybernetics Systems, Vol. 9, No. 2 (July 2015), pp. 157-166, DOI: http://doi.org/10.22146/ijccs.7544, entitled "Metode RCE-Kmeans untuk Clustering Data".The document and its content has been removed from International Journal of Advances in Intelligent Informatics, and reasonable effort should be made to remove all references to this article.
GPU Accelerated Number Plate Localization in Crowded Situation Adhi Prahara; Andri Pranolo; Rafał Dreżewski
International Journal of Advances in Intelligent Informatics Vol 1, No 3 (2015): November 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v1i3.46

Abstract

Number Plate Localization (NPL) has been widely used as part of Automatic Number Plate Recognition (ANPR) system. NPL method determines the accuracy of ANPR system. Although it is a mature research, the challenge stills persist especially in crowded situation where many vehicles present. Therefore, a method is proposed to localize number plate in crowded situation. The proposed NPL method uses vertical edge density to extract potential region of number plate then detect the number plate using combination of Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM). The method employs GPU to deal with multiple number plate detection, to handle multi-scale detection window, and to perform real time detection. The test result shows good results, 0.9883 value of AUC (Area Under Curve), and 0.9362 of BAC (Balance Accuracy). Moreover, potential real time detection is foreseen because total process is executed in less than 50 ms. Errors are mainly caused by background that contain letters, non-standard number plate and highly covered number plate
A review on fuzzy multi-criteria decision making land clearing for oil palm plantation Hamdani Hamdani; Retantyo Wardoyo
International Journal of Advances in Intelligent Informatics Vol 1, No 2 (2015): July 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v1i2.26

Abstract

Our review paper research categorize the methods in the method of Fuzzy Multi-Criteria Decision Making (FMCDM) to find the method is widely used in the case of land clearing for plantation. Model FMCDM is used to assess the parameter in multi-criteria-based decision making. The dominant percentage of the result was obtained using Fuzzy Analytic Hierarchy Process (FAHP) method. While the application of other methods for the same problem are Fuzzy Ordered Weighted Averaging (FOWA), Fuzzy Elimination Et Choix Traduisant la Realite or Elimination and Choice Translating Reality (FELECTRE), Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS), Fuzzy, Artificial Neural Networks (FANNs) has less. Some the research result also implemented hybrid in FMCDM Method to give some weight in the assessment of decision making. There was also a paper which integrates FMCDM to the GIS method on the land clearing. Therefore, it is concluded that the issue on the land clearing can be done through collaboration of several models of FMCDM, so that it can be developed by involving the decision model using multi-stakeholder model
Signature recognition using neural network probabilistic Heri Nurdiyanto; Hermanto Hermanto
International Journal of Advances in Intelligent Informatics Vol 2, No 1 (2016): March 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v2i1.53

Abstract

The signature of each person is different and has unique characteristics. Thus, this paper discusses the development of a personal identification system based on it is unique digital signature. The process of preprocessing used gray scale method, while Shannon Entropy and Probabilistic Neural Network are used respectively for feature extraction and identification. This study uses five signature types with five signatures in every type. While the test results compared to actual data compared to real data, the proposed system performance was only 40%.
Association Rule Algorithm Sequential Pattern Discovery using Equivalent Classes (SPADE) to Analyze the Genesis Pattern of Landslides in Indonesia Muhammad Muhajir; Berky Rian Efanna
International Journal of Advances in Intelligent Informatics Vol 1, No 3 (2015): November 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v1i3.50

Abstract

Landslide is one of movement of soil, rock, soil creep, and rock debris that occurred the move of the slopes. It is caused by steep slopes, high rainfall, deforestation, mining activities, and erosion. The impacts of the landslide are loss of property, damage to facilities such as homes and buildings, casualties, psychological trauma, disrupted economic and environmental damage. Based on the impacts of landslide, mitigation required to take early precautions are to know how the pattern of association between the sequence of events landslides and to know how the associative relationship pattern of earthquakes. Based on the impacts, the results of this research is associative relationship pattern is obtained from data flood that occurs in Indonesia, namely in case of heavy rain will occur labile soil structure to support the value of 0.37, confidence level of 41% and the power of formed ruled is 1.02.

Page 2 of 32 | Total Record : 314

 1   2   3   4   5 

Filter by Year

2015 2025


Reset
Filter By Issues
All Issue Vol 11, No 4 (2025): November 2025 Vol 11, No 3 (2025): August 2025 Vol 11, No 2 (2025): May 2025 Vol 11, No 1 (2025): February 2025 Vol 10, No 3 (2024): August 2024 Vol 10, No 2 (2024): May 2024 Vol 10, No 1 (2024): February 2024 Vol 9, No 3 (2023): November 2023 Vol 9, No 2 (2023): July 2023 Vol 9, No 1 (2023): March 2023 Vol 8, No 3 (2022): November 2022 Vol 8, No 2 (2022): July 2022 Vol 8, No 1 (2022): March 2022 Vol 7, No 3 (2021): November 2021 (Issue in Progress) Vol 7, No 3 (2021): November 2021 Vol 7, No 2 (2021): July 2021 (Issue in Progess) Vol 7, No 2 (2021): July 2021 Vol 7, No 1 (2021): March 2021 Vol 6, No 3 (2020): November 2020 Vol 6, No 2 (2020): July 2020 Vol 6, No 1 (2020): March 2020 Vol 5, No 3 (2019): November 2019 Vol 5, No 2 (2019): July 2019 Vol 5, No 1 (2019): March 2019 Vol 4, No 3 (2018): November 2018 Vol 4, No 2 (2018): July 2018 Vol 4, No 1 (2018): March 2018 Vol 3, No 3 (2017): November 2017 Vol 3, No 2 (2017): July 2017 Vol 3, No 1 (2017): March 2017 Vol 2, No 3 (2016): November 2016 Vol 2, No 2 (2016): July 2016 Vol 2, No 1 (2016): March 2016 Vol 1, No 3 (2015): November 2015 Vol 1, No 2 (2015): July 2015 Vol 1, No 1 (2015): March 2015 More Issue