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Publisher: Universitas Ahmad Dahlan   (Total: 18 journals)   [Sort by number of followers]

Showing 1 - 18 of 18 Journals sorted alphabetically
Ahmad Dahlan J. of English Studies     Open Access   (Followers: 2)
Bahastra     Open Access  
Berkala Fisika Indonesia     Open Access  
Bulletin of Electrical Engineering and Informatics     Open Access   (Followers: 8)
HUMANITAS (Jurnal Psikologi Indonesia)     Open Access   (Followers: 4)
Intl. J. of Advances in Intelligent Informatics     Open Access   (Followers: 7)
J. of Education and Learning     Open Access   (Followers: 11)
J. of Education, Health and Community Psychology     Open Access   (Followers: 9)
Jurnal Citizenship     Open Access   (Followers: 2)
Jurnal Hukum Novelty     Open Access  
Jurnal Ilmiah AdMathEdu     Open Access  
Jurnal Informatika     Open Access   (Followers: 1)
Kes Mas : Jurnal Fakultas Kesehatan Masyarakat     Open Access   (Followers: 2)
Media Farmasi     Open Access  
Pharmaciana     Open Access  
Psikopedagogia : Jurnal Bimbingan dan Konseling     Open Access   (Followers: 2)
Spektrum Industri : Jurnal Ilmiah Pengetahuan dan Penerapan Teknik Industri     Open Access  
TELKOMNIKA (Telecommunication, Computing, Electronics and Control)     Open Access   (Followers: 9, SJR: 0.265, CiteScore: 1)
Journal Cover
International Journal of Advances in Intelligent Informatics
Number of Followers: 7  

  This is an Open Access Journal Open Access journal
ISSN (Print) 2442-6571
Published by Universitas Ahmad Dahlan Homepage  [18 journals]
  • A coarse-grained parallelization of genetic algorithms

    • Authors: Muhamad Radzi Rathomi, Reza Pulungan
      Pages: 1 - 10
      Abstract: Genetic algorithms are frequently used to solve optimization problems. Nowadays, the problems to be solved by genetic algo-rithms become increasingly complex and require large computa-tion times. One solution to speed up genetic algorithm processing is to use parallelization. In this paper, a new method to increase the speed of genetic algorithms in finding the optimal solutions by parallelizing the processing of subpopulations is proposed. The proposed parallelization method is coarse-grained and em-ploys two levels of parallelization: message passing with MPI and Single Instruction Multiple Threads with GPU. Experimental results show that the accuracy of the proposed parallel genetic algorithm is similar to the sequential genetic algorithm. Parallel-ization with coarse-grained method, however, can improve the processing speed of genetic algorithms. Convergence speed of the parallel genetic algorithm is also much better than the se-quential genetic algorithm.
      PubDate: 2018-04-01
      DOI: 10.26555/ijain.v4i1.137
      Issue No: Vol. 4, No. 1 (2018)
  • A novel intelligent approach for detecting DoS flooding attacks in
           software-defined networks

    • Authors: Majd Latah, Levent Toker
      Pages: 11 - 20
      Abstract: Software-Defined Networking (SDN) is an emerging networking paradigm that provides an advanced programming capability and moves the control functionality to a centralized controller. This paper proposes a two-stage novel intelligent approach that takes advantage of the SDN approach to detect Denial of Service (DoS) flooding attacks based on calculation of packet rate as the first step and followed by Support Vector Machine (SVM) classification as the second step. Flow concept is an essential idea in OpenFlow protocol which represents a common interface between an SDN switch and an SDN controller. Therefore, our system calculates the packet rate of each flow based on flow statistics obtained by SDN controller. Once the packet rate exceeds a predefined threshold, the system will activate the packet inspection unit which, in turn, will use the (SVM) algorithm to classify the previously collected packets. The experimental results showed that our system was able to detect DoS flooding attacks with 96.25% accuracy and 0.26% false alarm rate.
      PubDate: 2018-04-01
      DOI: 10.26555/ijain.v4i1.138
      Issue No: Vol. 4, No. 1 (2018)
  • Biased support vector machine and weighted-smote in handling class
           imbalance problem

    • Authors: Hartono Hartono, Opim Salim Sitompul, Tulus Tulus, Erna Budhiarti Nababan
      Pages: 21 - 27
      Abstract: Class imbalance occurs when instances in a class are much higher than in other classes. This machine learning major problem can affect the predicted accuracy. Support Vector Machine (SVM) is robust and precise method in handling class imbalance problem but weak in the bias data distribution. Biased Support Vector Machine (BSVM) became popular choice to solve the problem. BSVM provide better control sensitivity and accuracy compared to general SVM. This study proposes the integration of BSVM and SMOTEBoost to handle class imbalance problem. Non Support Vector (NSV) sets from negative samples and Support Vector (SV) sets from positive samples will undergo a Weighted-SMOTE process. The results indicate that implementation of Biased Support Vector Machine and Weighted-SMOTE achieve better accuracy and sensitivity.
      PubDate: 2018-04-01
      DOI: 10.26555/ijain.v4i1.146
      Issue No: Vol. 4, No. 1 (2018)
  • Integrated AHP, Profile Matching, and TOPSIS for selecting type of goats
           based on environmental and financial criteria

    • Authors: Clara Hetty Primasari, Retantyo Wardoyo, Anny Kartika Sari
      Pages: 28 - 39
      Abstract: Goat farm businessman should considered environmental and financial criteria in breeding their commodities. The environmental factors are temperature, humidity, rain intensity, and altitude. For financial criteria, used several subcriteria i.e NPV (Net Present Value), ROI (Return On Investment), BCR (Benefit Cost Ratio), PBP (Payback Period), and BEP (Break Event Point) to determine financial feasibility. This research aims to build a Decision Support System for selecting type of goat to breed by combining AHP, Profile Matching, and TOPSIS. AHP method was used for calculating the weight, Profile Matching for environment suitability evaluation, and TOPSIS for producing a valid decision that represents the goat expert's decision. The result showed that, Bligon Goat had the highest preference value (0.8835847). This can be concluded that DSS decision was valid and it successfully represented expert’s consideration.
      PubDate: 2018-04-01
      DOI: 10.26555/ijain.v4i1.105
      Issue No: Vol. 4, No. 1 (2018)
  • Bayesian networks plant growth identification based on environmental
           parametric L-system

    • Authors: Suhartono Suhartono, Bahtiar Imran
      Pages: 40 - 50
      Abstract: Environmental factor can affect the plant growth. However the factors are dynamic and contains of uncertain data. This paper discuss the use of the plant growth identification using Bayesian networks.The network is based on parametric L-System, one of mathematical model for plants growth grammatical rules. This study models the growth of Zinia plants. The result is promising since the MAPE value is less than 10%.
      PubDate: 2018-04-01
      DOI: 10.26555/ijain.v4i1.157
      Issue No: Vol. 4, No. 1 (2018)
  • Green turtle and fish identification based on acoustic target strength

    • Authors: Sunardi Sunardi, Azrul Mahfurdz, Shoffan Saifullah
      Pages: 51 - 60
      Abstract: Fisherman accidently caught sea turtles in their fishnet. It could be dangerous for its population. This study measures the turtle target strength (TS) using modified echosounder. The result could be used to improve the efficiency of turtle repellent device. The experiment conducted in a hatchery fiber tank contained saline water. The Green were 1, 3, 12 and 18 years old. The study used three species of fish to ensure there are no overlapped value between fish and sea turtle. TS of the animals were calculated incorporating reference targets (sphere). The echo power of the turtle was compared with the solid steel sphere which is confirmed good agreements with the theoretical values. The echo power reference by applying Fast Fourier Transform (FFT) analysis has been used in calculating TS of the animal. From the echo evaluation in time domain at different angles, it is obviously shown that echo signal structure is different between the parts of turtle body. This study reveals that high echo strength is acquired from the carapace and the plastron parts the finding also showed that there are significant differences between 3, 12, 18 years old turtles and fish in every angle measurement.
      PubDate: 2018-04-01
      DOI: 10.26555/ijain.v4i1.147
      Issue No: Vol. 4, No. 1 (2018)
  • A survey on text similarity measure

    • Authors: Didik Dwi Prasetya, Aji Prasetya Wibawa, Tsukasa Hirashima
      Pages: 61 - 69
      Abstract: Measurement of text similarity is a very important activity to determining the degree of similarity between objects. Finding of similarities between words, sentences, and documents are part of the essence of text similarity. Words can be said similar in two ways, lexically and semantically. There have been many studies of text similarity and resulting in various approaches and algorithms. This paper will summarize the measurements of text similarity categorized into four major groups: String-based, Corpus-based, Knowledge-based, and Hybrid similarities. To complete this study, we also conducted a small investigation to evaluate text similarity using common algorithms that represent categories of text similarity
      PubDate: 2018-03-31
      DOI: 10.26555/ijain.v4i1.152
      Issue No: Vol. 4, No. 1 (2018)
  • Variable Precision Rough set based for selecting attribute on environment
           impact data set

    • Authors: Ani Apriani, Iwan Tri Riyadi Yanto, Septiana Fathurrahmah, Sri Haryatmi, Danardono Danardono
      Pages: 70 - 75
      Abstract: The investigation of environment impact have important role to development of the city. The application of the artificial intelligence in form of computational models can be used to analyze the data . One of them is rough set theory. The utilization of Data Clustering method, which is a part of rough set theory, could provide a meaningful contribution on the decision making process. The application of this method could come in term of selecting the attribute of environment impact. This paper examine the application of variable precision rough set model for selecting attribute of environment impact. This method is based on the mean of minimum error classification by utilizing variable precision of attributes. This paper utilized the data set which was established from the field survey. At this preliminary stage, this paper demonstrates the utilization of variable precision rough set model to select the most important impact of regional development. Based on the experiment, The availability of public open space, social organization and culture, migration and rate of employment are selected as a dominant attributes. It can be contributed on the policy design process, in term of formulating a proper intervention for enhancing the quality of social environment.
      PubDate: 2018-03-31
      DOI: 10.26555/ijain.v4i1.109
      Issue No: Vol. 4, No. 1 (2018)
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