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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Journal of the Medical Sciences (Berkala Ilmu Kedokteran) Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Eksplora Informatika Communications in Science and Technology Jurnal Otomasi Kontrol dan Instrumentasi Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) IJITEE (International Journal of Information Technology and Electrical Engineering) Indonesian Journal of Electrical Engineering and Computer Science Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) JAREE (Journal on Advanced Research in Electrical Engineering) Communications in Humanities and Social Sciences Jurnal Nasional Teknik Elektro dan Teknologi Informasi Journal FORTEI-JEERI Prosiding SNPBS (Seminar Nasional Pendidikan Biologi dan Saintek) Pancaran Pendidikan Teknik: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Teknomatika: Jurnal Informatika dan Komputer

Noor Akhmad Setiawan

Department Of Electrical Engineering And Information Technology, Faculty Of Engineering, Universitas Gadjah Mada, Yogyakarta

Author-ID : 2459804

Religion Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Neuroscience Physics Social Sciences

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Analisis Implementasi Paperless Office (PLO) di Lingkungan Universitas Gadjah Mada Yogyakarta (Studi Kasus di Tiga Fakultas) Haried Novriando; Lukito Edi Nugroho; Noor Akhmad Setiawan
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 1 No 2: Mei 2012
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (220.405 KB)

One important aspect that is needed to determine the successful implementation of a system is the evaluation. Evaluation is one important aspect that is needed to figure out the successful implementation of an information system. This study aims: (1) to evaluate the use of System Paperless Office in University Gadjah Mada by using Delone and Mclean, (2) to proceed the survey data by using Partial Least Square (PLS) software for measuring user perceptions of the PLO. The data which have been collected are primary data by using questionnaires that has to be fulfilled by Gadjah Mada University employees of three faculties. Moreover, they have to be PLO users who actively use this system. The variables used are the system quality, information quality, service quality, user satisfaction, individual impact and organizational impact. The results of the survey indicate that PLO as a system has not been fully used by all PLO users. Some factors that hinder the utilization of PLO are the lack of information and system quality, so the users cannot maximize the advantage of the PLO. It also affects to the value of utility PLO.

A Improving Feature Selection on Heart Disease Dataset With Boruta Approach Muhammad Arzanul Manhar; Indah Soesanti; Noor Akhmad Setiawan
Journal FORTEI-JEERI Vol. 1 No. 1 (2020): FORTEI-JEERI
Publisher : Forum Pendidikan Tinggi Teknik Elektro Indonesia (FORTEI)

Coronary artery disease (CAD) is one of the deadliest diseases in the entire world, including in Indonesia. CAD occurs due to narrowing or blockage of coronary arteries which is usually caused by atherosclerosis. Various studies have been conducted with the aim to predict the nature and characteristics of this disease. Some researches uses the Z-Alizadeh Sani dataset which consists of 54 attributes with two results of classification, CAD and Normal to classify its data. Feature selection is one way to reduce the number of attributes that exist by leaving the attributes that have a high effect on the dataset. In this study, the Boruta method is used as a feature selection to minimize the attributes and leave the attributes with high relative with the dataset. By reducing the attributes in the dataset through the feature selection process, sets of 17 and 18 attributes are selected as attributes with high relative with the dataset. These attributes then used to calculate the accuracy value of the dataset using the several classification methods and 90,3% accuracy is obtained from this study.

Relational into Non-Relational Database Migration with Multiple-Nested Schema Methods on Academic Data Teguh Bharata Adji; Dwi Retno Puspita Sari; Noor Akhmad Setiawan
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 3, No 1 (2019): March 2019
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

The rapid development of internet technology has increased the need of data storage and processing technology application. One application is to manage academic data records at educational institutions. Along with massive growth of information, decrement in the traditional database performance is inevitable. Hence, there are many companies choose to migrate to NoSQL, a technology that is able to overcome the traditional database shortcomings. However, the existing SQL to NoSQL migration tools have not been able to represent SQL data relations in NoSQL without limiting query performance. In this paper, a relational database transformation system transforming MySQL into non-relational database MongoDB was developed, using the Multiple Nested Schema method for academic databases. The development began with a transformation scheme design. The transformation scheme was then implemented in the migration process, using PDI/Kettle. The testing was carried out on three aspects, namely query response time, data integrity, and storage requirements. The test results showed that the developed system successfully represented the relationship of SQL data in NoSQL, provided complex query performance 13.32 times faster in the migration database, basic query performance involving SQL transaction tables 28.6 times faster on migration results, and basic performance Queries without involving SQL transaction tables were 3.91 times faster in the migration source. This shows that the theory of the Multiple Nested Schema method, aiming to overcome the poor performance of queries involving many JOIN operations, is proved. In addition, the system is also proven to be able to maintain data integrity in all tested queries. The space performance test results indicated that the migrated database transformed using the Multiple Nested Schema method showed a storage requirement of 10.53 times larger than the migration source database. This is due to the large amount of data redundancy resulting from the transformation process. However, at present, storage performance is not a top priority in data processing technology, so large storage requirements are a consequence of obtaining efficient query performance, which is still considered as the first priority in data processing technology.

Remote Sensing Technology for Land Farm Mapping Based on NDMI, NDVI, and LST Feature Ahmad Fauzi Mabrur; Noor Akhmad Setiawan; Igi Ardiyanto
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 3, No 3 (2019): September 2019
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Remote Sensing is a reliable and efficient data acquisition techniques. This technique is widely used for land image processing. This technique has many advantages, especially in terms of cost and time. In this study, the classification between dry and irrigated land from irrigation canals is presented. Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), and Land Surface Temperature (LST) values obtained from satellite imagery data are used in this process. It is expected that through this method, the distribution and control of irrigation water can optimize existing agricultural potential. Ground Check (GC) is used for validation process. The results showed that the error rate based on the moon was not so large, i.e., 18%. The highest errors occur in February and March. This happens because those months are the rainy season, so the measured temperature is mostly the temperature above the cloud layer. On the other hand, the lowest error occurs in November. Also, it can be seen that this method can function optimally when detecting residential areas or highways.

Deep Learning Methods for EEG Signals Classification of Motor Imagery in BCI Muhammad Fawaz Saputra; Noor Akhmad Setiawan; Igi Ardiyanto
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 3, No 3 (2019): September 2019
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

EEG signals are obtained from an EEG device after recording the user's brain signals. EEG signals can be generated by the user after performing motor movements or imagery tasks. Motor Imagery (MI) is the task of imagining motor movements that resemble the original motor movements. Brain Computer Interface (BCI) bridges interactions between users and applications in performing tasks. Brain Computer Interface (BCI) Competition IV 2a was used in this study. A fully automated correction method of EOG artifacts in EEG recordings was applied in order to remove artifacts and Common Spatial Pattern (CSP) to get features that can distinguish motor imagery tasks. In this study, a comparative studies between two deep learning methods was explored, namely Deep Belief Network (DBN) and Long Short Term Memory (LSTM). Usability of both deep learning methods was evaluated using the BCI Competition IV-2a dataset. The experimental results of these two deep learning methods show average accuracy of 50.35% for DBN and 49.65% for LSTM.

Serendipity Identification Using Distance-Based Approach Widhi Hartanto; Noor Akhmad Setiawan; Teguh Bharata Adji
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 5, No 1 (2021): March 2021
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.62344

The recommendation system is a method for helping consumers to find products that fit their preferences. However, recommendations that are merely based on user preference are no longer satisfactory. Consumers expect recommendations that are novel, unexpected, and relevant. It requires the development of a serendipity recommendation system that matches the serendipity data character. However, there are still debates among researchers about the available common definition of serendipity. Therefore, our study proposes a work to identify serendipity data's character by directly using serendipity data ground truth from the famous Movielens dataset. The serendipity data identification is based on a distance-based approach using collaborative filtering and k-means clustering algorithms. Collaborative filtering is used to calculate the similarity value between data, while k-means is used to cluster the collaborative filtering data. The resulting clusters are used to determine the position of the serendipity cluster. The result of this study shows that the average distance between the recommended movie cluster and the serendipity movie cluster is 0.85 units, which is neither the closest cluster nor the farthest cluster from the recommended movie cluster.

Eye Blink Classification for Assisting Disability to Communicate Using Bagging and Boosting Luthfi Ardi; Noor Akhmad Setiawan; Sunu Wibirama
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 5, No 4 (2021): December 2021
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.63515

Disability is a physical or mental impairment. People with disability have more barriers to do certain activity than those without disability. Moreover, several conditions make them having difficulty to communicate with other people. Currently, researchers have helped people with disabilities by developing brain-computer interface (BCI) technology, which uses artifact on electroencephalograph (EEG) as a communication tool using blinks. Research on eye blinks has only focused on the threshold and peak amplitude, while the difference in how many blinks can be detected using peak amplitude has not been the focus yet. This study used primary data taken using a Muse headband on 15 subjects. This data was used as a dataset classified using bagging (random forest) and boosting (XGBoost) methods with python; 80% of the data was allocated for learning and 20% was for testing. The classified data was divided into ten times of testing, which were then averaged. The number of eye blinks’ classification results showed that the accuracy value using random forest was 77.55%, and the accuracy result with the XGBoost method was 90.39%. The result suggests that the experimental model is successful and can be used as a reference for making applications that help people to communicate by differentiating the number of eye blinks. This research focused on developing the number of eye blinks. However, in this study, only three blinking were used so that further research could increase these number.

Feature analysis for stage identification of Plasmodium vivax based on digital microscopic image Hanung Adi Nugroho; I Md. Dendi Maysanjaya; Noor Akhmad Setiawan; E. Elsa Herdiana Murhandarwati; Widhia K.Z Oktoeberza
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 2: February 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i2.pp721-728

Plasmodium parasite is identified to confirm malaria disease. Paramedics need to observe the presence of this parasite prepared on thick and thin blood films under microscope. However, false identification still occurs which is caused by human factor during the examination. Thus, malaria identification based on digital image processing has been widely developed to overcome the error possibility. This paper proposes a scheme to identify and classify the stages of Plasmodium vivax parasite on digital microscopic image of thin blood films based on feature analysis. Shape and texture features are extracted from segmented parasite objects. Feature selection based on wrapper method is then conducted to obtain relevant features which may contribute in improving the classification result. The classification process is conducted based on Naïve Bayes classifier. The performance of proposed method is evaluated using 73 digital microscopic images of P.vivax parasite on thin blood films comprising of 29 trophozoites, 10 schizonts and 34 gametocytes stages. By using six selected features including perimeter, dispersion, mean of intensity, ASM, contrast GLCM and entropy GLCM, the proposed scheme achieves the best classification rate with the accuracy, sensitivity and specificity of 97.29%, 97.30% and 97.30%, respectively. This indicates that the proposed scheme has a potential to be implemented in the development of a computerised aided malaria diagnosis system for assisting the paramedics.

Identification of plasmodium falciparum and plasmodium vivax on digital image of thin blood films gf Hanung Adi Nugroho; Made Satria Wibawa; Noor Akhmad Setiawan; E. Elsa Herdiana Murhandarwati; Ratna Lestari Budiani Buana
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 3: March 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i3.pp933-944

Observing presence of Plasmodium parasite of stained thick or thin blood films through microscopic examination is a gold standard for malaria diagnosis. Although the microscopic examination has been extensively used, misidentification might occur caused by human factors. In order to overcome misidentification problem, several studies have been conducted to develop a computer-aided malaria diagnosis (CADx) to assist paramedics in decision-making. This study proposes an approach to identify species and stage of Plasmodium falciparum and Plasmodium vivax on thin blood films collected from the Laboratory of Parasitology, Faculty of Medicine, Universitas Gadjah Mada. Adaptive k-means clustering is applied to segment Plasmodium parasites. A total of 39 features consisting of shape and texture features are extracted and then selected by using wrapper-based forward and backward directions. Classification is evaluated in two schemes. The first scheme is to classify the species of parasite into two classes. The second scheme is to classify the species and stage of parasite into six classes. Three classifiers applied are k-nearest neighbour (KNN), support vector machine (SVM) and multi-layer perceptron (MLP). Furthermore, to facilitate the multiclass classification, one-versus-one (OVO) and one-versus-all (OVA) methods are implemented. The first scheme achieves the accuracy of 88.70% based on MLP classifier using three selected features. While the accuracy gained by the second scheme is 95.16% based on OVO and MLP classifier using 29 selected features. These results indicate that the proposed approach successfully identifies the species and stage of parasite on thin blood films and has potential to be implemented in the CADx system for assisting paramedics in diagnosing malaria.

Increases Activity and The Results of The Learner’s Study by Implementing Cooperative Learning Method Type TAI Galuh Indah Zatadini; Erna Adhistya P; Noor Akhmad Setiawan
Pancaran Pendidikan Vol 6, No 4 (2017)
Publisher : The Faculty of Teacher Training and Education The University of Jember Jember, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25037/pancaran.v6i4.87

Cooperative Learning is a model of learning taken by learners in the group, therefore, it will create many more learners to learn and collaborate. This research include in a class action model research aims to know the increase in activity and the results of the learner’s study on ICT subjects by using the method of Individualization Assisted Team (TAI). This research has three cycles with stages planning, implement1ation, observation and reflection which is done immediately when the learning activity. The outcomes learning research data is taken when the process of reflection after a posttest to all students when the study is completed. While the data retrieval process is done when the implementation of the activity when learners attend teaching and learning activities. From the results of research, the application of the cooperative learning model type TAI can increase the activity of the learners on a standard competency "Using Numeric Process Software to Produce the Information" and the basic competence “Makes the Document Processing Numbers with Variations of Text, Tables, Charts, Pictures and Diagrams". It can be seen from the increase in the percentage of the learner’s activity in the cycle I, II, and III. On the learners’ activity cycle I total percentage are 39.8% and still low. Later in the cycle II, their percentage was 78% and cycle III the total percentage was 55.7%. In addition to this type of cooperative learning, TAI can also enhance the learning outcome of students in all realm of affective, cognitive or psychomotor. This learning model can be one alternative that applied in the activity of learning but also must comply with the material or type of learning activities that will be done because of this learning model is only suitable for competence/problem can be resolved individually or groups.

Co-Authors Adhistya Erna Permanasari Adi Nugroho Adi Wijaya Adi Wijaya Agastya, I Made Artha Ahmad Fauzi Mabrur Aji, Marcus Nurtiantara Anggrahini, Dyah Wulan Anugrah Galang Persada Anugrah Galang Persada, Anugrah Galang Aras, Rezty Amalia Auliya, Syafira Baehaqi Bagus Kurniawan Bambang Sugiyantoro Berbudi Bowo Laksono Brahmantya Aji Pramudita Daru Hagni Setyadi Desyandri Desyandri Dewi, Sri Kusuma Dwi Retno Puspita Sari E. Elsa Herdiana Murhandarwati Eko Nugroho Eko Nugroho Fery Antony Fityah, Farhatul Galuh Indah Zatadini Gilang Adityasakti Hairani Hairani Hanung Adi Nugroho Haried Novriando Heilbert Armando Mapaly I Made Yulistya Negara I Md. Dendi Maysanjaya Igi Ardiyanto Indah Soesanti Ipin Prasojo Ipin Prasojo, Ipin Irma Yuliana Julianto Lemantara Kadek Dwi Pradnyani Novianti Kadek Dwi Pradnyani Novianti, Kadek Dwi Pradnyani Kharisma Adi Utama Lina Choridah Lukito Edi Nugroho Luthfi Ardi Made Satria Wibawa Maghfirah Maghfirah Maghfirah Maghfirah Maghfirah Marcus Nurtiantara Aji Mochammad Wahyudi Muhammad Arzanul Manhar Muhammad Fawaz Saputra Murnani, Suatmi Ni Wayan Priscila Yuni Praditya Nugraha, Anggit Ferdita Nugroho, Adi Nugroho, Anan Oyas Wahyunggoro Paulus Insap Santosa Persada, Anugrah Galang Prasojo, Ipin Putra, M. Azka Rahmadi, Ridho Ratna Lestari Budiani Buana Ridho Rahmadi Ridho Rahmadi Rifkie Primartha Rochim, Febry Putra Rudy Hartanto Sajiah, Adha Mashur Sekar Sari Siti Helmyati Sri Kusuma Dewi Sri Kusuma Dewi, Sri Kusuma SRI RAHAYU Sri Suning Kusumawardani Subhan Afifi Sunu Wibirama Surjono Surjono Teguh Bharata Adji Tito Yuwono, Tito Tole Sutikno Utama, Kharisma Adi Widhi Hartanto Widhia K.Z Oktoeberza Wijaya, Adi Zatadini, Galuh Indah

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