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All Journal ComEngApp : Computer Engineering and Applications Journal Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) CommIT (Communication & Information Technology) International Journal of Advances in Intelligent Informatics Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Communications in Science and Technology IJITEE (International Journal of Information Technology and Electrical Engineering) Indonesian Journal of Electrical Engineering and Computer Science Narra J Jurnal Nasional Teknik Elektro dan Teknologi Informasi Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi)
Igi Ardiyanto
Universitas Gadjah Mada
Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Transportation

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User Curiosity Factor in Determining Serendipity of Recommender System Arseto Satriyo Nugroho; Igi Ardiyanto; Teguh Bharata Adji
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 5, No 3 (2021): September 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.67553

Abstract

Recommender rystem (RS) is created to solve the problem by recommending some items among a huge selection of items that will be useful for the e-commerce users. RS prevents the users from being flooded by information that is irrelevant for them.Unlike information retrieval (IR) systems, the RS system's goal is to present information to the users that is accurate and preferably useful to them. Too much focus on accuracy in RS may lead to an overspecialization problem, which will decrease its effectiveness. Therefore, the trend in RS research is focusing beyond accuracy methods, such as serendipity. Serendipity can be described as an unexpected discovery that is useful. Since the concept of a recommendation system is still evolving today, formalizing the definition of serendipity in a recommendation system is very challenging.One known subjective factor of serendipity is curiosity. While some researchers already addressed curiosity factor, it is found that the relationships between various serendipity component as perceived by the users and their curiosity levels is still yet to be researched. In this paper, the method to determine user curiosity model by considering the variation of rated items was presented, then relation to serendipity components using existing user feedback data was validated. The finding showed that the curiosity model was related to some user-perceived values of serendipity, but not all. Moreover, it also had positive effect on broadening the user preference. 
Content-based image retrieval for fabric images: A survey Silvester Tena; Rudy Hartanto; Igi Ardiyanto
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1861-1872

Abstract

In recent years, a great deal of research has been conducted in the area of fabric image retrieval, especially the identification and classification of visual features. One of the challenges associated with the domain of content-based image retrieval (CBIR) is the semantic gap between low-level visual features and high-level human perceptions. Generally, CBIR includes two main components, namely feature extraction and similarity measurement. Therefore, this research aims to determine the content-based image retrieval for fabric using feature extraction techniques grouped into traditional methods and convolutional neural networks (CNN). Traditional descriptors deal with low-level features, while CNN addresses the high-level, called semantic features. Traditional descriptors have the advantage of shorter computation time and reduced system requirements. Meanwhile, CNN descriptors, which handle high-level features tailored to human perceptions, deal with large amounts of data and require a great deal of computation time. In general, the features of a CNN's fully connected layers are used for matching query and database images. In several studies, the extracted features of the CNN's convolutional layer were used for image retrieval. At the end of the CNN layer, hash codes are added to reduce  search time.
PENGEMBANGAN DATA WAREHOUSE UNTUK MENDUKUNG REPORT PENGADAAN DI INSTANSI PEMERINTAHAN Luky Hidayat; Adhistya Erna Permanasari; Igi Ardiyanto
Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Vol. 1 No. 1 (2017): PROSIDING SEMNAS INOTEK Ke-I Tahun 2017
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/inotek.v1i1.359

Abstract

Pengadaan barang/jasa pemerintah adalah kegiatan untuk memperoleh barang/jasa yang prosesnya dimulai dari perencanaan kebutuhan sampai diselesaikannya seluruh kegiatan. Proses pengadaan di pemerintahan saat ini memasuki sebuah babak baru, yaitu dengan mulai diterapkannya pengadaan berbasis elektronik (e-procurement). Untuk melakukan kegiatan monitoring, audit dan memenuhi kebutuhan akses informasi yang real time diperlukan laporan (report) secara berkala terkait pengadaan dengan cepat dan akurat. Karenanya, diperlukan teknologi data warehouse yang dapat mengintegrasikan database serta dapat mempercepat proses pengumpulan data untuk penyajian infomasi yang multidimensi (dapat dilihat dari berbagai sudut pandang) dan ringkas, namun memiliki daya guna yang tinggi sehingga dapat membantu stakeholder dalam proses pengambilan keputusan. Data warehouse merupakan data yang bersifat subject oriented, integrated, non-volatile atau tidak mengalami perubahan dan time variant (data diambil dalam periode waktu tertentu secara periodik). Pada penelitian ini dilakukan pengembangan data warehouse untuk mendukung web report pengadaan dengan memanfaatkan data pengadaan secara e-tendering dan e-purchasing di Pemerintah Kabupaten Purbalingga. Dengan adanya dukungan dan peran teknologi informasi diharapkan dapat mewujudkan clean and good government dalam pengadaan barang/jasa pemerintah.
Analisis Pengaruh Kompresi Citra Fundus terhadap Kinerja Sistem Automated Microanerysm Detections Anugerah Galang Persada; Ahmad Nasikun; Igi Ardiyanto; Hanung Adi Nugroho
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 1: Februari 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1011.955 KB)

Abstract

Diabetes is one of the most serious diseases that commonly suffered by people around the world, including Indonesia. Early symptoms of diabetes could be observed from various indicators, one of which is through the retina. Retina conditions is affected by diabetics and when remain unproperly threated could lead to blindness. This retinal disorders due to diabetes is normally called Diabetic Retinopathy (DR). One method that able to distinguish and detect DR is microaneurysm detection. This method requires good quality of retinal images. However, in certain areas such as rural areas, this requirement may difficult to meet due to lack of adequate infrastructure. One solution that may overcome this problem is to compress the images. In this paper, image compression algorithms were applied to the retinal image, and then used to detect microaneuryms through Deep Learning-based systems. The result shows that the most stable and appropriate algorithm is PNG, which is able to correctly classify around 83% in accuracy with 5,5% variance.
Systematic literature review of dermoscopic pigmented skin lesions classification using convolutional neural network (CNN) Erwin Setyo Nugroho; Igi Ardiyanto; Hanung Adi Nugroho
International Journal of Advances in Intelligent Informatics Vol 9, No 3 (2023): November 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v9i3.961

Abstract

The occurrence of pigmented skin lesions (PSL), including melanoma, are rising, and early detection is crucial for reducing mortality. To assist Pigmented skin lesions, including melanoma, are rising, and early detection is crucial in reducing mortality. To aid dermatologists in early detection, computational techniques have been developed. This research conducted a systematic literature review (SLR) to identify research goals, datasets, methodologies, and performance evaluation methods used in categorizing dermoscopic lesions. This review focuses on using convolutional neural networks (CNNs) in analyzing PSL. Based on specific inclusion and exclusion criteria, the review included 54 primary studies published on Scopus and PubMed between 2018 and 2022. The results showed that ResNet and self-developed CNN were used in 22% of the studies, followed by Ensemble at 20% and DenseNet at 9%. Public datasets such as ISIC 2019 were predominantly used, and 85% of the classifiers used were softmax. The findings suggest that the input, architecture, and output/feature modifications can enhance the model's performance, although improving sensitivity in multiclass classification remains a challenge. While there is no specific model approach to solve the problem in this area, we recommend simultaneously modifying the three clusters to improve the model's performance.
Point of Interest (POI) Recommendation System using Implicit Feedback Based on K-Means+ Clustering and User-Based Collaborative Filtering Sulis Setiowati; Teguh Bharata Adji; Igi Ardiyanto
Computer Engineering and Applications Journal Vol 13 No 1 (2024)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/comengapp.v13i1.388

Abstract

Recommendation system always involves huge volumes of data, therefore it causes the scalability issues that do not only increase the processing time but also reduce the accuracy. In addition, the type of data used also greatly affects the result of the recommendations. In the recommendation system, there are two common types of data namely implicit (binary) rating and explicit (scalar) rating. Binary rating produces lower accuracy when it is not handled with the properly. Thus, optimized K-Means+ clustering and user-based collaborative filtering are proposed in this research. The K-Means clustering is optimized by selecting the K value using the Davies-Bouldin Index (DBI) method. The experimental result shows that the optimization of the K values produces better clustering than Elbow Method. The K-Means+ and User-Based Collaborative Filtering (UBCF) produce precision of 8.6% and f-measure of 7.2%, respectively. The proposed method was compared to DBSCAN algorithm with UBCF, and had better accuracy of 1% increase in precision value. This result proves that K-Means+ with UBCF can handle implicit feedback datasets and improve precision.
Segmentation of retinal blood vessels for detection of diabetic retinopathy: A review Aras, Rezty Amalia; Lestari, Tri; Nugroho, Hanung Adi; Ardiyanto, Igi
Communications in Science and Technology Vol 1 No 1 (2016)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.1.1.2016.13

Abstract

Diabetic detinopathy (DR) is effect of diabetes mellitus to the human vision that is the major cause of blindness. Early diagnosis of DR is an important requirement in diabetes treatment. Retinal fundus image is commonly used to observe the diabetic retinopathy symptoms. It can present retinal features such as blood vessel and also capture the pathologies which may lead to DR. Blood vessel is one of retinal features which can show the retina pathologies. It can be extracted from retinal image by image processing with following stages: pre-processing, segmentation, and post-processing. This paper contains a review of public retinal image dataset and several methods from various conducted researches. All discussed methods are applicable to each researcher cases. There is no further analysis to conclude the best method which can be used for general cases. However, we suggest morphological and multiscale method that gives the best accuracy in segmentation.
Dark lesion elimination based on area, eccentricity and extent features for supporting haemorrhages detection Yulyanti, Vesi; Adi Nugroho, Hanung; Ardiyanto, Igi; Oktoeberza, Widhia KZ
Communications in Science and Technology Vol 4 No 1 (2019)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (410.365 KB) | DOI: 10.21924/cst.4.1.2019.110

Abstract

One of the complications due to the long-term of diabetes is retinal vessels damaging called diabetic retinopathy. It is characterised by appearing the bleeding spots in the large size (haemorrhages) on the surface of retina. Early detection of haemorrhages is needed for preventing the worst effect which leads to vision loss. This study aims to detect haemorrhages by eliminating other dark lesion objects that have similar characteristics with haemorrhages based on three features, i.e. area, eccentricity and extent features. This study uses 43 retinal fundus images taken from DIARETDB1 database. Based on the validation process, the average level of sensitivity gained is 80.5%. These results indicate that the proposed method is quite capable of detecting haemorrhages which appear in the retinal surface.
Comparison of text-image fusion models for high school diploma certificate classification Atmaja Perdana, Chandra Ramadhan; Adi Nugroho, Hanung; Ardiyanto, Igi
Communications in Science and Technology Vol 5 No 1 (2020)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (901.175 KB) | DOI: 10.21924/cst.5.1.2020.172

Abstract

File scanned documents are commonly used in this digital era. Text and image extraction of scanned documents play an important role in acquiring information. A document may contain both texts and images. A combination of text-image classification has been previously investigated. The dataset used for those research works the text were digitally provided. In this research, we used a dataset of high school diploma certificate, which the text must be acquired using optical character recognition (OCR) method. There were two categories for this high school diploma certificate, each category has three classes. We used convolutional neural network for both text and image classifications. We then combined those two models by using adaptive fusion model and weight fusion model to find the best fusion model. We come into conclusion that the performance of weight fusion model which is 0.927 is better than that of adaptive fusion model with 0.892.
Navigasi Objek Virtual Bergerak Bebas untuk Augmented Reality menggunakan Kamera 3D Intel Realsense Nuryono, Aninditya Anggari; Ardiyanto, Igi; Wibirama, Sunu
Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya 2018: Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2025.731 KB)

Abstract

Augmented Reality adalah sebuah teknik untuk menggabungkan konten digital dengan dunia nyata secara real time. Kamera 3D Intel RealSense digunakan untuk menghasilkan konten digital pada Augmented Reality berbasis markerless. Kamera ini merekonstruksi lingkungan nyata secara tiga dimensi. Scene perception merupakan metode untuk merekonstruksi ulang lingkungan nyata secara tiga dimensi. Pemanfaatan kamera ini pada Augmented Reality berupa autonomous agent. Autonomous agent memiliki fungsi navigasi agar sampai ke titik tujuan dengan mencari jalur yang disebut pathfinding. Autonomous agent miliki tiga perilaku yaitu seek, arrive, dan action selection. Perilaku-perilaku ini digunakan autonomous agent agar sampai ke titik tujuan dengan menghindari halangan virtual dan nyata yang ada di dunia nyata. Metode scene perception digunakan untuk membuat sebuah mesh. Mesh ini merupakan grid virtual di dunia nyata yang digunakan sebagai area Augmented Reality. Hasil navigasi dari autonomous agent menggunakan metode scene perception pada Augmented Reality dapat bekerja dengan baik. Autonomous agent dapat menuju ke titik tujuan dengan menghindari halangan virtual dan nyata.
Co-Authors Adhistya Erna Permanasari Ahmad Fauzi Mabrur Ahmad Nasikun Aras, Rezty Amalia Atmaja Perdana, Chandra Ramadhan Dian Nova Kusuma Hardani Elfrida Ratnawati Erwin Setyo Nugroho Hanung Adi Nugroho Luky Hidayat Made Rahmawaty, Made Muhammad Fawaz Saputra Nasikun, Ahmad Noor Akhmad Setiawan Nugroho, Arseto Satriyo Nugroho, Erwin S. Nugroho, Hanung A. Nurcahyani Wulandari Nuryono, Aninditya Anggari Oktoeberza, Widhia KZ Persada, Anugerah Galang Rizky Naufal Perdana Rudy Hartanto Setialana, Pradana Silvester Tena Siti Helmyati Sulis Setiowati Sulis Setiowati Sunu Wibirama Teguh Bharata Adji Tri Lestari Woraratpanya, Kuntpong Yenny Rahmawati Yuli Triyani Yulyanti, Vesi