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All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Informatika Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmu Komputer dan Informasi Jurnal Ilmu Komputer Transmisi: Jurnal Ilmiah Teknik Elektro Jurnal INKOM Proceedings of KNASTIK Bulletin of Electrical Engineering and Informatics JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal technoscientia Jurnal Teknologi Prosiding SNATIKA Vol 01 (2011) JUITA : Jurnal Informatika International Journal of Advances in Intelligent Informatics Seminar Nasional Informatika (SEMNASIF) Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Proceeding of the Electrical Engineering Computer Science and Informatics Journal of Information Technology and Computer Science Emerging Science Journal IJID (International Journal on Informatics for Development) CCIT (Creative Communication and Innovative Technology) Journal JISKa (Jurnal Informatika Sunan Kalijaga) JURNAL TEKNOLOGI TECHNOSCIENTIA Journal of Applied Data Sciences Makara Journal of Science Jurnal Informatika dan Multimedia JEECS (Journal of Electrical Engineering and Computer Sciences) Madani: Multidisciplinary Scientific Journal

Retantyo Wardoyo

Universitas Gadjah Mada

Author-ID : 359720

Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Other

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Survey: Models and Prototypes of Schema Matching Edhy Sutanta; Retantyo Wardoyo; Khabib Mustofa; Edi Winarko
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 3: June 2016
Publisher : Institute of Advanced Engineering and Science

Schema matching is critical problem within many applications to integration of data/information, to achieve interoperability, and other cases caused by schematic heterogeneity. Schema matching evolved from manual way on a specific domain, leading to a new models and methods that are semi-automatic and more general, so it is able to effectively direct the user within generate a mapping among elements of two the schema or ontologies better. This paper is a summary of literature review on models and prototypes on schema matching within the last 25 years to describe the progress of and research chalenge and opportunities on a new models, methods, and/or prototypes.

Feature Selection of the Combination of Porous Trabecular with Anthropometric Features for Osteoporosis Screening Enny Itje Sela; Sri Hartati; Agus Harjoko; Retantyo Wardoyo; Munakhir Mudjosemedi
International Journal of Electrical and Computer Engineering (IJECE) Vol 5, No 1: February 2015
Publisher : Institute of Advanced Engineering and Science

This study aims to select the important features from the combination of porous trabecular pattern with anthropometric features for osteoporosis screening. The study sample has their bone mineral density (BMD) measured at the proximal femur/lumbar spine using dual-energy X-ray absorptiometry (DXA). Morphological porous features such as porosity, the size of porous, and the orientation of porous are obtained from each dental radiograph using digital image processing. The anthropometric features considered are age, height, weight, and body mass index (BMI). Decision tree (J.48 method) is used to evaluate the accuracy of morphological porous and anthropometric features for selection data. The study shows that the most important feature is age and the considered features for osteoporosis screening are porosity, vertical pore, and oblique pore. The decision tree has considerably high accuracy, sensitivity, and specificity.

Decision-Making Model for Student Assessment by Unifying Numerical and Linguistic Data Sri Andayani; Sri Hartati; Retantyo Wardoyo; Djemari Mardapi
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 1: February 2017
Publisher : Institute of Advanced Engineering and Science

Learning assessment deals with the process of making a decision on the quality or performance of student achievement in a number of competency standards. In the process, teacher’s preferences are provided through both test and non-test, generally in a numeric value, from which the final results are then converted into letters or linguistic value. In the proposed model, linguistic variables are exploited as a form of teacher’s preferences in non-test techniques. Consequently, the assessment data set will consist of numerical and linguistic information, so it requires a method to unify them to obtain the final value. A model that uses the 2-tuple linguistic approach and based on matrix operations is proposed to solve the problem. This study proposed a new procedure that consists of four stages: preprocessing, transformation, aggregation and exploitation. The final result is presented in 2-tuple linguistic representation and its equivalent number, accompanied by a description of the achievement of each competency. The α value of 2-tuple linguistic in the final result and in the description of each competency becomes meaningful information that can be interpreted as a comparative ability one student has related to other students, and shows how much potential is achieved to reach higher ranks. The proposed model contributes to enrich the learning assessment techniques, since the exploitation of linguistic variable as representation preferences provides flexible space for teachers in their assessments. Moreover, using the result with respect to students’ levels of each competency, students’ mastery of each attribute can be diagnosed and their progress of learning can be estimated.

The challenges of emotion recognition methods based on electroencephalogram signals: a literature review I Made Agus Wirawan; Retantyo Wardoyo; Danang Lelono
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp1508-1519

Electroencephalogram (EEG) signals in recognizing emotions have several advantages. Still, the success of this study, however, is strongly influenced by: i) the distribution of the data used, ii) consider of differences in participant characteristics, and iii) consider the characteristics of the EEG signals. In response to these issues, this study will examine three important points that affect the success of emotion recognition packaged in several research questions: i) What factors need to be considered to generate and distribute EEG data?, ii) How can EEG signals be generated with consideration of differences in participant characteristics?, and iii) How do EEG signals with characteristics exist among its features for emotion recognition? The results, therefore, indicate some important challenges to be studied further in EEG signals-based emotion recognition research. These include i) determine robust methods for imbalanced EEG signals data, ii) determine the appropriate smoothing method to eliminate disturbances on the baseline signals, iii) determine the best baseline reduction methods to reduce the differences in the characteristics of the participants on the EEG signals, iv) determine the robust architecture of the capsule network method to overcome the loss of knowledge information and apply it in more diverse data set.

University Website Quality Ranking using Logarithmic Fuzzy Preference Programming Retantyo Wardoyo; Tenia Wahyuningrum
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

The current tight competition in developing University websites forces developers to create better products that meet users needs and convinient. There are at least two factors representing university websites; accessibility and usability. We test three criteria of accessibility and usability that are called stickiness, backlink, and web page loading time. Usability and accessibility are closely related to subjective user judgments. Human judgment cannot be valid. Thus the use of fuzzy numbers are expected to provide solutions in calculating the results. In this research, the question of usability is a multi criteria decision-making problem that is caused by its complex structure. We use the Logarithmic Fuzzy Preference Programming (LFPP) method, which is a refinement of the Fuzzy Analytical Hierarchy Process method, to solve this problem. This research aims to re- assess the rank of five Indonesian university websites. Based on LFPP method, we obtain that the equation of model gets high consistency of the set priority matching to fuzzy pairwise comparison matrix of three selection criteria. The calculation results show that stickiness is the most significant factor that affects the quality of the websites.

A Hybrid Model Schema Matching Using Constraint-Based and Instance-Based Edhy Sutanta; Retantyo Wardoyo; Khabib Mustofa; Edi Winarko
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 3: June 2016
Publisher : Institute of Advanced Engineering and Science

Schema matching is an important process in the Enterprise Information Integration (EII) which is at the level of the back end to solve the problems due to the schematic heterogeneity. This paper is a summary of preliminary result work of the model development stage as part of research on the development of models and prototype of hybrid schema matching that combines two methods, namely constraint-based and instance-based. The discussion includes a general description of the proposed models and the development of models, start from requirement analysis, data type conversion, matching mechanism, database support, constraints and instance extraction, matching and compute the similarity, preliminary result, user verification, verified result, dataset for testing, as well as the performance measurement. Based on result experiment on 36 datasets of heterogeneous RDBMS, it obtained the highest P value is 100.00% while the lowest is 71.43%; The highest R value is 100.00% while the lowest is 75.00%; and F-Measure highest value is 100.00% while the lowest is 81.48%. Unsuccessful matching on the model still happens, including use of an id attribute with data type as autoincrement; using codes that are defined in the same way but different meanings; and if encountered in common instance with the same definition but different meaning.

Classification of plasmodium falciparum based on textural and morphological features Doni Setyawan; Retantyo Wardoyo; Moh Edi Wibowo; E. Elsa Herdiana Murhandarwati
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5036-5048

Malaria is a disease caused by plasmodium parasites transmitted through the bites of female anopheles-mosquito that infect the human red blood cell (RBC). The standard malaria diagnosis is based on manual examination of a thick and thin blood smear, which heavily depends on the microscopist experience. This study proposed a system that can identify the life stages of plasmodium falciparum in human RBC. The image preprocessing process was done by illumination correction using gray world assumption, contrast enhancement using shadow correction, extraction of saturation component, and noise filtering. The segmentation process was applied using Otsuthresholding and morphological operation. The test results showed that the use of artificial neural network (ANN) using a combination of texture and morphological features gives better results when compared to the use of only texture or morphology features. The results showed that the proposed feature achieved an accuracy of 82.67%, a sensitivity of 82.18%, and a specificity of 94.17%, thus improving decision-making for malaria diagnosis.

Face recognition for occluded face with mask region convolutional neural network and fully convolutional network: a literature review Rahmat Budiarsa; Retantyo Wardoyo; Aina Musdholifah
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i5.pp5662-5673

Face recognition technology has been used in many ways, such as in the authentication and identification process. The object raised is a piece of face image that does not have complete facial information (occluded face), it can be due to acquisition from a different point of view or shooting a face from a different angle. This object was raised because the object can affect the detection and identification performance of the face image as a whole. Deep leaning method can be used to solve face recognition problems. In previous research, more focused on face detection and recognition based on resolution, and detection of face. Mask region convolutional neural network (mask R-CNN) method still has deficiency in the segmentation section which results in a decrease in the accuracy of face identification with incomplete face information objects. The segmentation used in mask R-CNN is fully convolutional network (FCN). In this research, exploration and modification of many FCN parameters will be carried out using the CNN backbone pooling layer, and modification of mask R-CNN for face identification, besides that, modifications will be made to the bounding box regressor. it is expected that the modification results can provide the best recommendations based on accuracy.

Fine tuning attribute weighted naïve Bayes model for detecting anxiety disorder levels of online gamers Latubessy, Anastasya; Wardoyo, Retantyo; Musdholifah, Aina; Kusrohmaniah, Sri
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp3277-3286

This research applies the fine tuning attribute weighted naïve Bayes (FTAWNB) model using ordinal data. It is known that in previous research, the FTAWNB model outperformed its competitors on the dataset used. However, the FTAWNB model has not been applied in the mental health domain that uses ordinal data. Therefore, this research used the anxiety gamers dataset to test the fine-tuning attribute weighted Naïve Bayes (FTAWNB) model. Anxiety disorders are mental health disorders that can indicate the emergence of a gaming disorder. Gamers can experience anxiety disorders classified into four classes, namely minimal, mild, moderate, and severe anxiety. Then compare the results by FTAWNB obtained with three other naïve Bayes algorithms, namely Gaussian naïve Bayes, multinomial naïve Bayes, and categorical naïve Bayes, using the same dataset. Model performance is measured based on accuracy, precision, recall, and processing time. The test results show that the FTAWNB outperforms the other three models' accuracy, precision, and recall, with an accuracy value of 99.22%. While the accuracy of Gaussian NB is 91.132%, Categorical is 91.592%, and multinomial naïve Bayes is 61.104%. However, the FTAWNB takes slightly longer than the other three models' processing time. The FTAWNB takes 0.07 seconds to build the model and 0.05 seconds to test the model on training data.

Face recognition with occluded face using improve intersection over union of region proposal network on Mask region convolutional neural network Budiarsa, Rahmat; Wardoyo, Retantyo; Musdholifah, Aina
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp3256-3265

Face recognition entails detecting and identifying facial attributes. Mask region convolutional neural network (R-CNN) method is a prominent approach, while prior research predominantly delved into refining loss functions and perfecting object and face detection, recognizing, and identifying faces using imperfect data remained relatively unexplored. This study focuses on an occluded dataset comprising Indonesian faces, wherein 'occluded' denotes facial data that lacks complete visibility-encompassing instances where objects obscure faces or are partially cropped. This investigation involves a deliberate experiment that tailors the intersection over union (IoU) of the region proposal network (RPN) to suit the nuances of occluded Indonesian faces, thereby augmenting accuracy in recognition and segmentation tasks. The innovation IoU in the strategic utilization of Anchors, which involves the exclusion of anchors falling beyond the image borders to optimize computational efficiency. The outcomes of this research are striking; it showcases a remarkable 14.75%, 10.9%, and 12.97% surge based on mean average precision (mAP), mean average recall (mAR), and F1-Scores compared to the conventional Mask R-CNN approach. Notably, our proposed model elevates the average accuracy by 10% to 15% and decreases running time by 21%, a noteworthy enhancement compared to the preceding model. This progress is substantiated by validation utilizing 300 instances dataset, reinforcing the robustness of our approach.

Co-Authors Abdul Wahid Adiananda Adiananda Agus Harjoko Ahmad Ashari Ahmad Asharit Aina Musdholifah Aina Musdholifah Albert Dian Sano Anastasya Latubessy Andeka Rocky Tanaamah Andika Kurnia Adi Pradana Andriyani, Widyastuti Anny Kartika Sari Arief Kelik Nugroho, Arief Kelik Azhari Azhari Azhari Azhari Azhari Subanar Bambang Sugiantoro Bambang Sugiantoro Bangun Wijayanto Bernard Renaldy Suteja Budiarsa, Rahmat Christian Dwi Suhendra Clara Hetty Primasari Danang Lelono Decky Hendarsyah Desyandri Desyandri Djemari Mardapi Doni Setyawan E. Elsa Herdiana Murhandarwati Edhy Sutanta (Jurusan Teknik Informatika IST AKPRIND Yogyakarta) Edi Winarko Edi Winarko Enny Itje Sela Gede Angga Pradipta, Gede Angga Hananto, Andhika Rafi Hardyanto Soebono Herri Setiawan Herri Setiawan I Made Agus Wirawan I Made Agus Wirawan Ida Ayu Putu Sri Widnyani Istiyanto, Jazi Eko Jazi Eko Istiyanto Jazi Eko Istiyanto Jazi Eko Istiyanto Joan Angelina Widians, Joan Angelina Khabib Mustofa Khairunnisa Khairunnisa Kusrini Kusrini Lausu, Suwandi Lilik Sumaryanti M Mustakim M.Cs S.Kom I Made Agus Wirawan . Moh Edi Wibowo Muhamad Munawar Yusro Muhammad Fakhrurrifqi Muhammad Mukharir Munakhir Mudjosemedi Mustakim, M Nola Ritha NUR HASANAH Peggi Sri Astuti Pratama, Kharis Suryandaru Purba, Susi Eva Maria Purwo Santoso Putri Elfa Mas`udia Rahman Erama Rahmat Budiarsa Ramos Somya Rika Rosnelly Rosa Delima Rosihan Rosihan, Rosihan Santoso, Purwo Silmina, Esi Putri Sri Andayani Sri Hartati Sri Hartati Sri Hartati Sri Hartati Sri Kusrohmaniah, Sri Sri Kusumadewi Sri Mulyana Subahar, Subahar subanar subanar Suryo Guritno Suryo Guritno Suryo Guritno Tempola, Firman Tenia Wahyuningrum Wenty Dwi Yuniarti, Wenty Dwi Wibowo, Moh Edi Winarko, Edi Wiwiet Herulambang Yayi Suryo Prabandari

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