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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electronics and Instrumentation Systems IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Teknologi Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Teknologi Pertanian Jurnal Edukasi dan Penelitian Informatika (JEPIN) Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika JTET (Jurnal Teknik Elektro Terapan) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Creative Information Technology Journal JIKO (Jurnal Informatika dan Komputer) Compiler Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Sains Komputer dan Teknologi Informasi Journal of Soft Computing Exploration Jurnal Nasional Teknik Elektro dan Teknologi Informasi Journal of Information Systems for Public Health

Agus Harjoko

Universitas Gadjah Mada

Author-ID : 439660

Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering Medicine & Pharmacology Public Health

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Articles

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Face Recognition Based on Symmetrical Half-Join Method using Stereo Vision Camera Edy Winarno; Agus Harjoko; Aniati Murni Arymurthy; Edi Winarko
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 6: December 2016
Publisher : Institute of Advanced Engineering and Science

The main problem in face recognition system based on half-face pattern is how to anticipate poses and illuminance variations to improve recognition rate. To solve this problem, we can use two lenses on stereo vision camera in face recognition system. Stereo vision camera has left and right lenses that can be used to produce a 2D image of each lens. Stereo vision camera in face recognition has capability to produce two of 2D face images with a different angle. Both angle of the face image will produce a detailed image of the face and better lighting levels on each of the left and right lenses. In this study, we proposed a face recognition technique, using 2 lens on a stereo vision camera namely symmetrical half-join. Symmetrical half-join is a method of normalizing the image of the face detection on each of the left and right lenses in stereo vision camera, then cropping and merging at each image. Tests on face recognition rate based on the variety of poses and variations in illumination shows that the symmetrical half-join method is able to provide a high accuracy of face recognition and can anticipate variations in given pose and illumination variations. The proposed model is able to produce 86% -97% recognition rate on a variety of poses and variations in angles between 0 °- 22.5 °. The variation of illuminance measured using a lux meter can result in 90% -100% recognition rate for the category of at least dim lighting levels (above 10 lux).

The Digital Microscope and Its Image Processing Utility Sri Hartati; Agus Harjoko; Tri Wahyu Supardi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 9, No 3: December 2011
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v9i3.749

Many institutions, including high schools, own a large number of analog or ordinary microscopes. These microscopes are used to observe small objects. Unfortunately, object observations on the ordinary microscope require precision and visual acuity of the user. This paper discusses the development of a high-resolution digital microscope from an analog microscope, including the image processing utility, which allows the digital microscope users to capture, store and process the digital images of the object being observed. The proposed microscope is constructed from hardware components that can be easily found in Indonesia. The image processing software is capable of performing brightness adjustment, contrast enhancement, histogram equalization, scaling and cropping. The proposed digital microscope has a maximum magnification of 1600x, and image resolution can be varied from 320x240 pixels up to 2592x1944 pixels. The microscope was tested with various objects with a variety of magnification, and image processing was carried out on the image of the object. The results showed that the digital microscope and its image processing system were capable of enhancing the observed object and other operations in accordance with the user need. The digital microscope has eliminated the need for direct observation by human eye as with the traditional microscope.

Increasing the Detail and Realism in Web3D Distributed World Mursid Wahyu Hananto; Ahmad Ashari; Khabib Mustofa; Agus Harjoko
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 5: October 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i5.10113

A complex and detailed Web3D world which represented the physical form of an institution is very difficult to be built. To simplify the work, raster images taken from the real structure were heavily utilized. However, this method has resulted in Web3D sites which were low on detail and having minimum level of realism. To overcome this deficiency, it is proposed to maximize the use of polygons. Experiment was done by re-developing the sample world with minimum use of raster images and applying polygons to 92% parts of the site. Site elements were also distributed to three servers to cope with bottleneck problem often occured when using only one server. The result was evaluated in a series of tests to see its viewing capabilities when displayed inside the web browser against various conditions, and it also evaluated in an acceptance test carried out by site users. The majority of testers felt immensely familiar with the details shown by the model as they were able to grab a more close-to-realistic experience like a real-world walk around inside the actual building complex. Problems that often occur whe using only one server ca also be reduced by using distributed world method.

Intelligent Traffic Monitoring Systems: Vehicle Type Classification Using Support Vector Machine Ika Candradewi; Agus Harjoko; Bakhtiar Alldino Ardi Sumbodo
International Journal of Artificial Intelligence Research Vol 5, No 1 (2021): June 2021
Publisher : STMIK Dharma Wacana

In the automation of vehicle traffic monitoring system, information about the type of vehicle, it is essential because used in the process of further analysis as management of traffic control lights. Currently, calculation of the number of vehicles is still done manually. Computer vision applied to traffic monitoring systems could present data more complete and update.In this study consists of three main stages, namely Classification, Feature Extraction, and Detection. At stage vehicle classification used multi-class SVM method to evaluate characteristics of the object into eight classes (LV-TK, LV-Mobil, LV-Mikrobis, MHV-TS, MHV-BS, HV-LB, HV- LT, MC). Features are obtained from the detection object, processed on the feature extraction stage to get features of geometry, HOG, and LBP in the detection stage of the vehicle used MOG method combined with HOG-SVM to get an object in the form of a moving vehicle and does not move. SVM had the advantage of detail and based statistical computing. Geometry, HOG, and LBP characterize complex and represents an object in the form of the gradient and local histogram.The test results demonstrate the accuracy of the calculation of the number of vehicles at the stage of vehicle detection is 92%, with the parameters HOG cellSize 4x4, 2x2 block size, the son of vehicle classification 9. The test results give the overall mean recognition rate 91,31 %, mean precision rate 77,32 %, and mean recall rate 75,66 %.

Pengenalan Simbol Jarimatika Menggunakan Orientasi Histogram dan Multi-layer Perceptron Andi Sunyoto; Agus Harjoko
Creative Information Technology Journal Vol 1, No 4 (2014): Agustus - Oktober
Publisher : UNIVERSITAS AMIKOM YOGYAKARTA

Makalah ini membahas tentang pengenalan simbol-simbol Jarimatika menggunakan Jaringan Syaraf Tiruan (JST). Hasil penelitian ini dapat digunakan untuk pengembangan aplikasi perhitungan Jarimatika dan interaksi antara manusia dan komputer yang lebih natural. Segmentasi yang digunakan adalah orientasi histogram, algoritma JST yang digunakan adalah back propagation multi-layer perceptron. Layer-layer JST tersebut adalah satu layer input, satu hidden layer dan satu output layer. Penelitian ini betujuan untuk implementasi pengenalan pola simbol Jarimatika menggunakan JST multi-layer perceptron, implementasi harus mampu menghasilkan klasifikasi dengan benar, sistem harus mampu melakukan klasifikasi dari gambar statis, sehingga dapat menganalisa pengenalan gestur tangan dari simbol-simbol Jarimatika.Penelitian ini menggunakan 18 simbol dasar Jarimatika. Total citra yang digunakan adalah 360 yang terbagi atas 270 citra untuk training dan 90 citra untuk testing. Hasil penelitian ini menunjukkan bahwa JST multi-perceptron dapat digunakan untuk pengenalan simbol Jarimatika dengan akurasi 93.33%. Jumlah neuron yang optimal pada hidden layer adalah 725. Implementasi penelitian ini menggunakan Matlab versi 7 (R2010a).This paper focuses on the recognition of Jarimatika symbols using Artificial Neural Network (ANN). The results of this research can be used to develop applications for the Jarimatika and to make interaction between humans and computers more natural. The Segmentation used is orientation histograms, the ANN algorithm used is back propagation multi-layer perceptron. Th layers of the ANN are one input layer with 19 data, one hidden layer and one output layer. This research aims to implement Jarimatika symbols with pattern recognition and multi-layer perceptron algoritm, the implementation must be able to produce the correct classification, the system must be able to perform the classification of static images, so can analyze the recognition of hand gestures from Jarimatika symbols. This research uses 18 basic Jarimatika symbols. Total image used were 360, consisting of 270 images for training and 90 images for testing. The results of this study indicate that the multi-layer perceptron ANN can be used for recognition of Jarimatika symbols with accuracy 93.33%. The optimal number of neurons in the hidden layer is 725. Implementation of this research using Matlab version 7 (R2010a).

User Interface Design for e-Learning System Bernard Renaldy Suteja; Agus Harjoko
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2008
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

With the demand for e-Learning steadily growing and the ongoing struggle to convince the skeptics of thepotential of e-Learning and online virtual classrooms, quality design is the foundation for a successful DEprogram. The design of the instruction and the design of the user interface are critical elements in providingquality education with a virtual, e-Learning model. This White Paper will focus on the design of the e-Learninguser interface (UI). This paper provide examples of user interface design from e-Learning prototype.Keywords: e-Learning, user interface design.

Sistem Informasi Perpustakaan dengan Arsitektur Lima Simpul dan Basisdata Terdistribusi Agus Harjoko; Helna Wardhanat
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2005
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

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Telah diimplementasikan dan dikaji sistem informasi perpustakaan dengan arsitektur lima simpul danbasisdata terdistribusi. Pengkajian dilakukan dengan studi kasus pada STMIK Bumigora dan ABA Bumigora diMataram. Pendistribusian basisdata system ini dilakukan dengan mengikuti lokasi fisik koleksi perpustakaanyaitu satu basisdata di STMIK Bumigora dan satu basisdata lagi di ABA Bumigora. Sistem informasiperpustakaan yang dibuat dirancang untuk dapat menangani kebutuhan perpustakaan yang meliputipengelolaan anggota perpustakaan (pendaftaran, perpanjangan dan penghentian), sirkulasi koleksiperpustakaan (pencarian, peminjaman, pengembalian, pemesanan, penarikan, penggantian denda) danpelaporan yang disesuaikan dengan kebutuhan pengelola perpustakaan. Dari hasil percobaan dan evaluasididapatkan bahwa system ini telah memenuhi kebutuhan perpustakaan STMIK Bumigora dan ABA Bumigora diMataram.Key words: library information system, three-tier architecture, distributed database

Penerapan Jaringan Syaraf Tiruan untuk Mendeteksi Posisi Wajah Manusia pada Citra Digital Setyo Nugroho; Agus Harjoko
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2005
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

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Salah satu bagian penting dalam proses pengenalan wajah adalah mendeteksi posisi wajah. Dalammakalah ini kami merancang dan mengimplementasikan sistem pendeteksi posisi wajah dengan menggunakanjaringan syaraf tiruan. Sistem ini dilatih dengan menggunakan contoh-contoh wajah yang diberikan. AlgoritmaQuickprop dan metode active learning digunakan untuk mempercepat proses pelatihan sistem. Dari hasileksperimen dengan menggunakan 23 file citra berisi 149 wajah, sistem pendeteksi wajah ini memberikan hasildetection rate 71,14% dan false positive 62.Kata kunci: deteksi wajah, jaringan syaraf tiruan, quickprop, active learning

Penggunaan Operator Quantifier Guided Dominance Degree (QGDD) sebagai Certainty Factor pada Clinical Group Decision Support System (CGDSS) Sri Kusumadewi; Sri Hartati; Retantyo Wardoyo; Agus Harjoko
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2006
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

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Salah satu permasalahan dalam Clinical Group Decision Support System (CDSS) adalah masalah dianosis. Apabila pada proses pengambilan keputusan, suatu CDSS membutuhkan dukungan dari beberapa orang pakar, maka perlu dibentuk suatu Clinical Group Decision Support System (CGDSS). Pada penelitian ini, akan dibangun suatu model basis pengetahuan berbasis aturan pada CGDSS dengan format preferensi yang diberikan oleh setiap pengambil keputusan berbentuk ordered vectors. Operator Ordered Weighted Averaging (OWA) digunakan untuk melakukan agregasi preferensi yang diberikan oleh setiap pengambil keputusan, dengan menggunakan quantifier fuzzy, ”most”. Konsistensi informasi pada matriks agregasi dilakukan sesuai dengan batasan-batasan yang diberikan pada relasi preferensi fuzzy. Proses perankingan untuk menentukan nilai kinerja setiap alternatif dilakukan dengan menggunakan operator Quantifier Guided Dominance Degree (QGDD). Hasil perankingan sebagai nilai kinerja alternatif akan digunakan sebagai certainty factor (CF) untuk setiap aturan pada basis pengetahuan.Kata kunci: Clinical Group Decision Support System, Ordered Weighted Averaging, Quantifier Guided Dominance Degree

Sistem Pengenalan Iris Mata Manusia dengan Menggunakan Transformasi Wavelet Maimunah Maimunah; Agus Harjoko
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2007
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

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Sistem biometri memberikan identifikasi secara otomatis dari individu berdasarkan ciri atau karakteristikunik yang dimiliki setiap individu. Pada saat ini pengenalan iris merupakan teknologi biometri yang relatif barudengan beberapa keuntungan yang dimilikinya seperti kestabilan dan keamanan .Sistem pengenalan iris terdiri dari proses segmentasi dan ekstraksi ciri menggunakan transformasiwavelet haar dan disimpan sebagai iris template. Proses pengenalan iris dilakukan dengan menggunakan jarakhamming pada iris template.Dalam penelitian ini digunakan data citra mata keabuan yang diambil dari basis data CASIA. Hasilpenelitian menunjukkan bahwa dari mata yang sama, sistem pengenalan iris mampu mengenali citra matadengan tingkat keberhasilan 100% untuk citra query sama dengan citra basis data dan 35.29% untuk citra queryberbeda dengan citra basis data. Adanya bulu mata, kelopak mata, pemantulan cahaya, jarak dan posisipengambilan citra mempengaruhi proses pengenalan iris.Kata kunci: pengenalan iris, segmentasi, transformasi wavelet haar.

Co-Authors Agus Wahyu Widodo Agus Wahyu Widodo, Agus Wahyu Ahmad Ashari Alabid, Noralhuda N. Anak Agung Istri Ngurah Eka Karyawati Andi Sunyoto Aniati Murni Arymurthy Anny Kartika Sari Ashar Punto Nurwendo Azhari, Azhari Bakhtiar Alldino Ardi Sumbodo Bernard Renaldy Suteja Budi Rahardjo Budi Rahmani Dyah Aruming Tyas Edy Winarno Elizabeth Nurmiyati Tamatjita Enny Itje Sela Feri Wibowo Gamma Kosala Hadi Santoso Helna Wardhana Hermawan Syahputra I Gede Aris Gunadi I Putu Adi Pratama Ika Arfiani Ika Candradewi Ika Sudirahayu Ikhwan Ruslianto Iwan Budi Nugroho Jumanto Jumanto, Jumanto Khabib Mustofa Kusrini Kusrini La Ode Hasnuddin S. Sagala Latifah, Husnul Lilik Sutiarso Lukman Awaludin Mahmuddin Yunus Maimunah Maimunah Maura Widyaningsih Much Aziz Muslim Muhammad Anis Al Hilmi Muhammad Shahid Ardi Munakhir Mudjosemedi Murinto Murinto Mursid Wahyu Hananto Nicodemus Mardanus Setiohardjo Nora Idiawati Norman Yazid Novrido Charibaldi Nugraha, Faizal Widya Pujiastuti, Asih Raden Sumiharto Rahmi Hidayati Retantyo Wardoyo Rocky Yefrenes Dillak Rudiati Evi Masithoh Sajid, Syahmi Salman Aliaji Septia Rani Setyo Nugroho Slamet Santosa Slamet Santoso Sri Hartati Sri Hartati Sri Hartati Sri Kusumadewi Sri Suwarno Tia Widiana Tri Kuntoro Priyambodo Tri Wahyu Supardi Wawan Kurniawan Winarko, Edi Yustina Retno Zaenal Abidin

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