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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Informatika Jurnal Teknik Elektro Seminar Nasional Aplikasi Teknologi Informasi (SNATI) TELKOMNIKA (Telecommunication Computing Electronics and Control) CommIT (Communication & Information Technology) Jurnal Infra Agrokreatif Jurnal Ilmiah Pengabdian kepada Masyarakat Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) International Journal of Industrial Research and Applied Engineering Society : Jurnal Pengabdian dan Pemberdayaan Masyarakat Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) Jurnal Teknik Elektro: Ilmu dan Teknologi
Indar Sugiarto
Petra Christian University
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Other

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STATIC CODE ANALYSIS FOR SOFTWARE QUALITY IMPROVEMENT: A CASE STUDY IN BCI FRAMEWORK DEVELOPMENT Sugiarto, Indar
Jurnal Informatika Vol 9, No 2 (2008): NOVEMBER 2008
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/informatika.9.2.166-172

Abstract

This paper shows how the systematic approach in software testing using static code analysis method can be used for improving the software quality of a BCI framework. The method is best performed during the development phase of framework programs. In the proposed approach, we evaluate several software metrics which are based on the principles of object oriented design. Since such method is depending on the underlying programming language, we describe the method in term of C++ language programming whereas the Qt platform is also currently being used. One of the most important metric is so called software complexity. Applying the software complexity calculation using both McCabe and Halstead method for the BCI framework which consists of two important types of BCI, those are SSVEP and P300, we found that there are two classes in the framework which have very complex and prone to violation of cohesion principle in OOP. The other metrics are fit the criteria of the proposed framework aspects, such as: MPC is less than 20; average complexity is around value of 5; and the maximum depth is below 10 blocks. Such variables are considered very important when further developing the BCI framework in the future.
Forward feature selection for toxic speech classification using support vector machine and random forest Agustinus Bimo Gumelar; Astri Yogatama; Derry Pramono Adi; Frismanda Frismanda; Indar Sugiarto
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i2.pp717-726

Abstract

This study describes the methods for eliminating irrelevant features in speech data to enhance toxic speech classification accuracy and reduce the complexity of the learning process. Therefore, the wrapper method is introduced to estimate the forward selection technique based on support vector machine (SVM) and random forest (RF) classifier algorithms. Eight main speech features were then extracted with derivatives consisting of 9 statistical sub-features from 72 features in the extraction process. Furthermore, Python is used to implement the classifier algorithm of 2,000 toxic data collected through the world's largest video sharing media, known as YouTube. Conclusively, this experiment shows that after the feature selection process, the classification performance using SVM and RF algorithms increases to an excellent extent. We were able to select 10 speech features out of 72 original feature sets using the forward feature selection method, with 99.5% classification accuracy using RF and 99.2% using SVM.
A NOVEL APPROACH FOR CONFIGURING THE STIMULATOR OF A BCI FRAMEWORK USING XML Indar Sugiarto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 7, No 2: August 2009
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v7i2.579

Abstract

In a working BCI framework, all aspects must be considered as an integral part that contributes to the successful operation of a BCI system. This also includes the development of robust but flexible stimulator, especially the one that closely related to the feedback of a BCI system. This paper describes a novel approach in providing flexible visual stimulator using XML which has been applied for a BCI (brain-computer interface) framework. Using XML file format for configuring the visual stimulator of a BCI system, we can develop BCI applications which can accommodate many experiment strategies in BCI research. The BCI framework and its configuration platform is developed using C++ programming language which incorporate Qt’s most powerful XML parser named QXmlStream. The implementation and experiment shows that the XML configuration file can be well executed within the proposed BCI framework. Beside its capability in presenting flexible flickering frequencies and text formatting for SSVEP-based BCI, the configuration platform also provides 3 shapes, 16 colors, and 5 distinct feedback bars. It is not necessary to increase the number of shapes nor colors since those parameters are less important for the BCI stimulator. The proposed method can then be extended to enhance the usability of currently existed BCI framework such as BF++ Toys and BCI 2000.
Fine-grained or coarse-grained? Strategies for implementing parallel genetic algorithms in a programmable neuromorphic platform Indar Sugiarto; Steve Furber
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i1.15026

Abstract

Genetic Algorithm (GA) is one of popular heuristic-based optimization methods that attracts engineers and scientists for many years. With the advancement of multi- and many-core technologies, GAs are transformed into more powerful tools by parallelising their core processes. This paper describes a feasibility study of implementing parallel GAs (pGAs) on a SpiNNaker. As a many-core neuromorphic platform, SpiNNaker offers a possibility to scale-up a parallelised algorithm, such as a pGA, whilst offering low power consumption on its processing and communication overhead. However, due to its small packets distribution mechanism and constrained processing resources, parallelising processes of a GA in SpiNNaker is challenging. In this paper we show how a pGA can be implemented on SpiNNaker and analyse its performance. Due to inherently numerous parameter and classification of pGAs, we evaluate only the most common aspects of a pGA and use some artificial benchmarking test functions. The experiments produced some promising results that may lead to further developments of massively parallel GAs on SpiNNaker.
Aplikasi Tcp-Ip untuk Mengendalikan Gerak WEBCAM Indar Sugiarto; Petrus Santoso; Andy Susanto
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2009
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

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Abstract

Dalam paper ini dipaparkan sistem keamanan memanfaatkan teknologi kamera (dalam hal ini berupa webcam),dua buah motor sebagai penggerak kamera beserta rangkaian driver-nya, sebuah komputer server, danbeberapa komputer client. Webcam dihubungkan dengan komputer server dan kemudian mengirimkan datavideo tersebut ke komputer client melalui protokol TCP/IP. Salah satu komputer client terpilih (pemantau) dapatjuga memerintahkan komputer server untuk menggerakkan kamera, sehingga hampir semua sudut ruangandapat dipantau. Sistem ini, diimplementasikan dengan bahasa pemrograman C++, dan memanfaatkan libraryAPI bawaan Windows untuk mengakses webcam maupun Winsock untuk komunikasi lewat protokol TCP/IP.Sistem telah diuji untuk keadaan jaringan terisolasi maupun lewat koneksi global (internet). Dari hasilpengujian lokal di dapatkan bahwa komputer client dapat menangkap gambar bergerak yang dipancarkan olehserver melalui mekanisme video streaming dengan framerate hingga 30 fps dan hanya memanfaatkan sekitar ¼dari kapasitas maksimum bandwidth jaringan. Jika sistem dioperasikan secara online dan terhubung denganinternet, kualitas video streaming sangat tergantung infrastruktur jaringan yang ada. Namun penempatankomputer server dilokasi yang strategis seperti pada backbone jaringan utama akan dapat meningkatkanaksesibilitas dari sistem dan menurunkan penggunaan bandwidth jaringan hingga hanya 4% saja. Dari hasilpengujian pengendalian motor juga didapatkan bahwa motor dapat dikendalikan sempurna dengan tingkatkesalahan hanya 0,5°.Kata Kunci: TCP-IP, winsock, client-server, webcam, security
Aplikasi Deteksi Jumlah Orang pada Area Indoor Untuk Mendukung Pelaksanaan PPKM dengan Metode YOLO Yoken Adinata; Kartika Gunadi; Indar Sugiarto
Jurnal Infra Vol 10, No 1 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Lately, the world is being hit by the Covid-19 outbreak which has caused several activities and sectors to be hampered, one of which is the buying and selling sector, both inside shopping centers and outside. Finally a solution emerged where each store was given a limit on the number of visitors to minimize the spread of the Covid-19 virus. However, there is a problem, namely monitoring the number of visitors is done manually so it is less effective and efficient.Because of the need for an application that can monitor the number of visitors when it has reached a certain limit the application will send a notification to the user. The method that used in this application to detecting the number of people is You Only Look Once (YOLO) The application has a feature so that the user can configure the parameters that will be used.Overall, the detection system used still has ambiguity in detecting small objects so that sometimes they are not detected as people. The rest, the system runs without problems from large to medium sized objects. On the other hand, overall survey respondents are satisfied with this system, this can be seen in the results of a survey taken from 15 respondents regarding the assessment of how this application helps the implementation of PPKM, and getting an average score of 8.53 out of 10, while the assessment of the ease of use of the application and user interface is 8.6 out of 10 and 8.4 out of 10.
Klasifikasi Motif Batik menggunakan metode Deep Convolutional Neural Network dengan Data Augmentation Samuel Febrian Tumewu; Djoni Haryadi Setiabudi; Indar Sugiarto
Jurnal Infra Vol 8, No 2 (2020)
Publisher : Jurnal Infra

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Abstract

Related researches before used Convolutional Neural Network (CNN) VGG to classify batik motif which limited only on geometrical pattern and implemented 2 augmentation consist of scale and rotation. Therefore, this research uses CNN Residual Network (Resnet) with 4 augmentation technique on both geometrical and non geometrical batik pattern.This research use (Resnet) as a main architecture of CNN to identify batik pattern. Batik motives for this research are from geometric category which is ceplok, kawung, lereng, nitik, and parang. And from nongeometri category are semen and lunglungan. Furthermore, the dataset will be applied scale, random erase, rotation, and flip augmentation to increase the quantity and variation of batik dataset.The results show that CNN Resnet with data augmentation on training dataset gives accuracy up to 84,52% on Resnet-18 and 81,90% on Resnet-50. furthermore, rotation augmentation adds 4,06%, random erase augmentation adds 9,38%, scale augmentation adds 6,52%, and flip augmentation adds 8,58% on accuracy
Sistem Presensi Mahasiswa Berbasis Animated QR Code Menggunakan Raspberry Pi Michael Anggreawan Alexander; Justinus Andjarwirawan; Indar Sugiarto
Jurnal Infra Vol 8, No 2 (2020)
Publisher : Jurnal Infra

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Abstract

Now the use of technology in the field of information systems technology has expanded more widely in all fields, including in educational institutions. The current presence system that is currently running on the teaching and learning system in several educational institutions still uses conventional methods. This causes need more time in the presence process. Previous research has implemented a QR Code added to the Mobile System application. Presence features using the QR Code can be found on the Schedule and Absentee menus. The presence will automatically follow the number of meetings that have been conducted.So with this description will be done designing and creating a presence system workflow with optimizing QR Code that is equipped with Animated, so that it can run using the Android application and using the Raspberry Pi 4 system which is equipped with a camera to read the Animated QR Code, where the student data will be sent to the database using Internet connectivity.Based on the results of tests that have been done, students managed to get an Animated QR Code as presence data by logging in to the application that is incorporated in the Internet network and storing the presence data in the Database. Raspberry Pi Camera is able to read Animated QR Codes from the Android application by taking a few seconds using Raspberry Pi 4. Facilitates students in making presence using an Android-based application.
Penerapan Metode YOLO dan Tesseract-OCR untuk Pendataan Plat Nomor Kendaraan Bermotor Umum di Indonesia Menggunakan Raspberry Pi Eric Tirtana; Kartika Gunadi; Indar Sugiarto
Jurnal Infra Vol 9, No 2 (2021)
Publisher : Jurnal Infra

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Abstract

Parking system is a common thing to find in public places. Parking system usually comes with a program that enables to detect and read license plates. With the advancement of technology, there are many systems / programs that are able to automatically detect and read license plates, but they come with a costly price. In this research, Raspberry Pi 4 will be used as the main platform. With the usage of Raspberry Pi, it is expected to reduce the cost needed to achieve the same output. However, by using Raspberry Pi, the hardware specifications are not as good as computer in general. In this research YOLO will be used to detect the license plate and Tesseract-OCR is used to read the characters on the license plate. From this research, it can be concluded that program can implement YOLO and Tesseract-OCR to detect and read public transportation license plates while being run on Raspberry Pi 4. To get the optimal results, the input image needs to be taken at daytime, using high quality camera, and implement only the necessary pre-processing methods.
Implementasi Sistem Pakar Deteksi Dini Resiko Penyakit Jantung Koroner Menggunakan Metode Backward Chaining dan Certainty Factor pada Android Andreas Prasetyo; Rudy Adipranata; Indar Sugiarto
Jurnal Infra Vol 9, No 2 (2021)
Publisher : Jurnal Infra

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Abstract

Lifestyle in the modern era today can have a harmful impact on ourlives, one of which is coronary heart disease. Coronary heartdisease is the chronic and acute heart's inability to pumpoxygenated blood due to a lack of blood supply in the heart's musclecells.This research, using the backward chaining method, serves to tracethe facts and combine them with hypotheses that can strengthenthose facts. Certainty factor is the method used to measure thecertainty of the facts that have been made and provide results in theform of scoring to determine the level of accuracy of the facts thathave been given by experts.This research will produce an expert-system application that isuseful for early detection of coronary heart disease. Output will bein the form of grouped results, which is the results of a person'spotential risk of coronary heart disease, along with a percentagebased risk potential of developing said disease. It is hoped that thecreation of this system will make it easier for a person to detect thedisease based on daily habits, so it can later be used as the initialdiagnosis whether or not a person has said disease.
Co-Authors Agustinus Bimo Gumelar Alexander Setiawan Andreas Prasetyo Andrew Wijaya Andy Susanto Astri Yogatama Astri Yogatama Candra, Ranggastika Prahlada Cristian Axenie Derry Pramono Adi Djoni Haryadi Setiabudi Edward Tanujaya Eric Tirtana Evert Oneil Felix Pasila Frismanda Frismanda Gondowardoyo, Sean Gregorio Diovani Wahanie Hafizah Kamarudin, Nazhatul Halim, Jason Handry Khoswanto Handy Wicaksono Handy Wicaksono Handy Wicaksono Iwan Halim Sahputra Jehezkiel Hardwin Tandijaya Joni Dewanto Jörg Conradt Justinus Andjarwirawan Kartika Gunadi Kartika Gunadi Kevin Koesoemo Lauw Lim Un Tung Liliana Liliana Michael Anggreawan Alexander Mohammad Ismail Rahman Mulia Rudy Petrus Santoso Petrus Santoso Pratomo, Hariyo Priambudi Setyo Resmana Lim Rudy Adipranata Samuel Febrian Tumewu Saravanakumar Natarajan Setyono Yudo Tyasmoro Siti Halimah Baki Soesanto, Agnes Steve Furber Sugiarto Wibowo Suryadi Thiang Thiang Tience Debora Valentina Timothy Joy Siswanto Tumbelaka, Hanny Hosiana Victor Christian Yohanes TDS Yoken Adinata