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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Teknik ITS IPTEK Journal of Proceedings Series IPTEK The Journal for Technology and Science TELKOMNIKA (Telecommunication Computing Electronics and Control) Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Ilmiah Kursor Prosiding SNATIF Jurnal Teknologi Informasi dan Ilmu Komputer International Journal of Advances in Intelligent Informatics Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Elektronika dan Telekomunikasi CYCLOTRON Jurnal Informatika dan Sistem Informasi Aiti: Jurnal Teknologi Informasi JAREE (Journal on Advanced Research in Electrical Engineering) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Bulletin of Social Informatics Theory and Application
Surya Sumpeno
Departemen Teknik Elektro, Fakultas Teknologi Elektro, Institut Teknologi Sepuluh Nopember Jl. Raya ITS, Sukolilo, Surabaya, Jawa Timur, 60111
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Social Sciences

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Klasifikasi Interaksi Kampanye di Media Sosial Menggunakan Naïve Bayes Kernel Estimator Aryo Nugroho; Rumaisah Hidayatillah; Surya Sumpeno; Mauridhi Hery Purnomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 8 No 2: Mei 2019
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

The development of technology also influences changes in campaign patterns. Campaign activities are part of the process of Election of Regional Heads. The aim of the campaign is to mobilize public participation, which is carried out directly or through social media. Social media becomes a channel for interaction between candidates and their supporters. Interactions that occur during the campaign period can be one indicator of the success of the closeness between voters and candidates. This study aims to get the pattern of campaign interactions that occur on Twitter social media channels. This interaction pattern is classified as a model in measuring the success of campaigns on social media. The research begins with obtaining data through the data retrieval process using the API feature provided by Twitter. Furthermore, pre-processing is carried out before data can be processed in an algorithmic method. This stage is done to improve data quality so as to improve accuracy. Naive Bayes Classifier was chosen because of a simple procedure, then Kernel Estimator (KE) was used to improve performance. The use of naive Bayes Kernel Estimator can improve model performance from 76.74% to 80.14%. Testing models with split percentage methods on several combinations get satisfactory results.
Analisis Kinerja LSTM dan GRU sebagai Model Generatif untuk Tari Remo Lukman Zaman; Surya Sumpeno; Mochamad Hariadi
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 8 No 2: Mei 2019
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Creating dance animations can be done manually or using a motion capture system. An intelligent system that able to generate a variety of dance movements should be helpful for this task. The recurrent neural network such as Long Short-Term Memory (LSTM) or Gated Recurrent Unit (GRU) could be trained as a generative model. This model is able to memorize the training data set and reiterate its memory as the output with arbitrary length. This ability makes the model feasible for generating dance animation. Remo is a dance that comprises several repeating basic moves. A generative model with Remo moves as training data set should make the animation creating process for this dance simpler. Because the generative model for this kind of problem involves a probabilistic function in form of Mixture Density Models (MDN), the random effects of that function also affect the model performance. This paper uses LSTM and GRU as generative models for Remo dance moves and tests their performance. SGD, Adagrad, and Adam are also used as optimization algorithms and drop-out is used as the regulator to find out how these algorithms affect the training process. The experiment results show that LSTM outperforms GRU in term of the number of successful training. The trained models are able to create unlimited dance moves animation. The quality of the animations is assessed by using visual and dynamic time warping (DTW) method. The DTW method shows that on average, GRU results have 116% greater variance than LSTM’s.
Deteksi Gestur Lengan Dinamis pada Lingkungan Virtual Tiga Dimensi Koleksi Warisan Budaya Adri Gabriel Sooai; Atyanta. N. Rumaksari; Khamid Khamid; Nurul Zainal Fanani; Surya Sumpeno; Mauridhi Hery Purnomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 4: November 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Virtual reality technology can be used to support museum exhibitions. Implementation could be in various platforms. There are many implementation options, for example in smartphones, tablet, and desktop computers. Most objects of museum collections are very fragile. Minimizing the direct touch on a collection object is one of the benefits of this technology. This study aims to prepare gestures suitable for the exploration of virtual objects of cultural heritage collection. Five sets of gestures have been prepared, namely lifting, picking, holding, sweeping from both directions, left and right. Dynamic arm gestures are recorded using the forearm sensor. The recorded data contains coordinates of gestures in form of x, y, z, raw, pitch, and yaw. Gaussian mixture models are used in selecting features to produce good accuracy in the classification process.Two functions are used, namely probability density function and cumulative distribution function for the feature selection process. In this study, two experiments were used to train the gesture model. The accuracy of the two experiments is shown in the form of a confusion matrix. Each of the confusion matrices show excellent results of 99.8% for SVM and k-NN. Furthermore, modeling results are tested using new data. The testing shows 89.25% result for SVM classifier and 90.09% for k-NN. Four other dynamic arm gestures have a very satisfactory rate of 100% for the two classifiers. The five gestures can be used in the development of virtual reality applications.
Ekstraksi Ciri Produktivitas Dinamis untuk Prediksi Topik Pakar dengan Model Discrete Choice Diana Purwitasari; Chastine Fatichah; Surya Sumpeno; Mauridhi Hery Purnomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 4: November 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Recommendation of active or productive experts is indispensable in supporting collaborations. Activities of publication and citation indicate expert productivity. An expert can be inferred to have an interest in a subject through productivity in that particular topic. Since an expert can change interests over time, the contribution of this paper is a Discrete Choice Model (DCM) based on topic productivities to predict the primary interests of the experts. DCM uses features extracted from bibliographic data of citation relation and title-abstract texts. Before extracting productivity features and dynamicity features to represent interest changes, title clustering with KMeans++ is used to identify research topics. There are six productivity features and five dynamicity values for each productivity feature to demonstrate the expert behavior. Therefore, a clustered topic as a research interest is represented as an expert choice with 30 extracted features in the proposed method. The experiments used multinomial logistic regression for DCM and a log-likelihood indicator for the fitted models of the features. The resulted DCM models showed that productive behavior of the experts by doing many publications and receiving many citations effected to the precision of topic prediction by 80%. Some features were better for predicting primary interests of the expert. It was demonstrated with a lower precision value of 60% by using features that represent the expert behavior of only doing publication or only getting citation.
Menuju Pengenalan Ekspresi Mikro: Pendeteksian Komponen Wajah Menggunakan Discriminative Response Map Fitting Ulla Delfana Rosiani; Priska Choirina; Surya Sumpeno; Mauridhi Hery Purnomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 2: Mei 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

The observations made in the study of micro-expression are to recognize and track the very subtle movements of certain facial areas and in a short time. In this study, the observation of movement is held in some areas of the face component. The facial and facial components detection is the pre-process stage on micro-expression recognition system. The goal at this stage is to get face and face components accurately and quickly on every movement of the video sequence or image sequence. The face landmark point of the Discriminative Response Map Fitting (DRMF) method can be used to get face components area accurately and quickly. This can be done because the facial landmark points used in this model-based method do not change when objects are moved, rotated, or scaled. The results obtained by using this method are accurate with a 100% accuracy value compared to the Haar Cascade Classifier method with an average accuracy of 44%. In addition, the average time required in the formation of facial component boxes for each frame is 0.08 seconds, faster than the Haar Cascade Classifier method of 0.32 seconds. With the results obtained, then the detection of facial components can be obtained accurately and quickly. Furthermore, the boxes of face components obtained are expected to display the appropriate data to be processed correctly and accurately in the next stage, feature extraction and the classification of micro-expression motion stage.
Application level interoperability on IaaS cloud migration Zahara, Soffa; Sumpeno, Surya; Pratomo, Istas
Bulletin of Social Informatics Theory and Application Vol. 1 No. 2 (2017)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v1i2.30

Abstract

The increasing awareness of people about several benefits using cloud computing technology caused a lot of organizations, companies, and agencies are switching from utilizing physical infrastructure to cloud infrastructure, especially IaaS. Considering the strong market enthusiastic about cloud computing, cloud companies were racing competitions offer the best products with various advantages. In the process of utilizing cloud computing technology there are circumstances in which the company wants to move its infrastructure to other cloud providers caused by various aspects in order to meet better expectations of to the new provider. However, there are many obstacles in practice in the process of transfer system between two different environment or can be called migration. One of them is a vendor lock-in that caused system cannot be function properly especially application functionality after migration. This paper introduces improvement method of testing interoperability between systems that were migrated between different cloud providers which use different hypervisor technology. We also conduct interoperability application testing between several cloud providers.
Clustering Titik Fitur Model Wajah 3D Menggunakan K-Nearest Neighbour Nendya, Matahari Bhakti; Yuniarno, Eko Mulyanto; Sumpeno, Surya
Jurnal Informatika dan Sistem Informasi Vol. 7 No. 1 (2021): Jurnal Informatika dan Sistem Informasi
Publisher : Universitas Ciputra Surabaya

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Abstract

The first step in the process of transferring animation using motion capture data to a 3D face model is to determine the facial feature points and the relationship between these points to form a 3D facial model motion system. This study focuses on grouping facial feature points where 33 centroids have been determined and looking for their association with other feature points. The 3D face model used is a humanoid character face model which is similar to a human 3D face model. The results obtained are the distribution of facial feature points that will be used as a reference in the mesh deformation process using linear blend skinning. Langkah awal dalam proses transfer animasi menggunakan data motion capture kepada model wajah 3D adalah menentukan titik fitur wajah dan keterkaitan antar titik tersebut supaya membentuk sistem gerak model wajah 3D. Penelitian ini berfokus pada pengelompokan titik fitur wajah dimana sudah ditentukan 33 titik pusat (centroid) dan mencari keterkaitannya dengan titik fitur lainya. Model wajah 3D yang digunakan berupa model wajah karakter humanoid yang mana mempunyai kemiripan dengan model wajah 3D manusia. Hasil yang didapatkan berupa sebaran titik fitur wajah yang akan digunakan sebagai acuan dalam proses mesh deformation menggunakan linear blend skinning
ANALYSIS OF MATURITY LEVELS OF ICT UTILIZATION ON EAST JAVA’S MICRO, SMALL, MEDIUM ENTERPRISES (MSMEs) IN THE NEW HABITS ADAPTATION ERA Amalia, Siska; Affandi, Achmad; Sumpeno, Surya
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 6, No 1 (2022): April
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v6i1.267

Abstract

The use of information and communication technology has increased along with the Covid-19 pandemic in early 2020 which made the whole world turn into digitalization. This study focuses on analyzing the maturity level of ICT utilization on East Java’s MSMEs using the Business Model Canvas (BMC) approach and the Capability Maturity Model ISAC FOUNDATION (2007) and evaluating gaps. The results of the analysis shows the maturity average of ICT utilization in East Java’s MSMEs is 0.86, which is at Level 1 (Initial), the gap average is 2,13 and the gap maturity value in ICT utilization in East Java’s MSMEs is Large, that is 1,5.Keywords—ICT, Maturity Level, MSMEs
Improving Government Helpdesk Service With an AI-Powered Chatbot Built on the Rasa Framework Sasmita, Wirat Moko Hadi; Sumpeno, Surya; Rachmadi, Reza Fuad
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 2 (2025): April 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i2.6293

Abstract

Helpdesk services are an important component in supporting Information Technology (IT) services. The helpdesk operates as the initial interface for managing and resolving concerns. Helpdesk helps user to get solutions when facing problems while using an IT service. This research focuses on the impact of artificial intelligence (AI)-powered chatbots on the performance of the initial response of government helpdesk services. The chatbot is designed to improve service performance by quickly identifying and classifying reported issues and automatically responding to messages, enabling faster responses. The research proposed a new System Design of a helpdesk system with an AI-based chatbot. The data used comes from Telegram group chat logs, exported in JSON format. We find that the Rasa NLU model with DIET Classifier successfully achieved an accuracy rate of 0.825 in classifying intents, with the precision value of 0.838, recall of 0.829, and F1 score of 0.821 using a Rasa model with cross-validation, where folds is 5 in evaluation. And initial response time was highly improved after using chatbot artificial intelligence from more than 3 hours on the telegram group helpdesk based to an average of 2.15 seconds. These research results suggest AI-Chatbot-based ability to assist the helpdesk team in handling user queries and reports, and improving initial time response.
PROTOTIPE SISTEM PENDUKUNG KEPUTUSAN TERINTEGRASI MODEL NER UNTUK VALIDASI DAN PENETAPAN PEMUKTAHIRAN DATA ASN Holik, Nur Muhamad; Sumpeno, Surya; Fuad Rachmadi, Reza
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 12 No 3: Juni 2025
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2025129175

Abstract

Untuk mendukung dan memperlancar penyelenggaraan manajemen aparatur sipil negara serta pengambilan keputusan yang efisien, efektif, dan akurat, diperlukan data pegawai ASN. Data tersebut harus dimutakhirkan dan divalidasi secara berkala sebelum disebarluaskan dan diakses oleh instansi pemerintah sesuai kewenangannya masing-masing serta dapat diakses oleh masyarakat melalui portal data sesuai dengan ketentuan peraturan perundang-undangan. Pada paper ini ditampilkan prototipe berbasis web untuk menunjukkan bahwa model NER yang dikembangkan dapat diintegrasikan sebagai subsistem dari sistem pendukung keputusan dalam melakukan validasi dan penetapan persetujuan pemutakhiran data ASN. Prototipe menunjukkan tingkat kemiripan hasil prediksi model dengan data yang diusulkan, tertinggi sebesar 100% dan terendah sebesar 41,34%. Pengukuran kinerja model menggunakan spacy menunjukkan bahwa model terbaik memperoleh nilai F1-score rata-rata sebesar 99,01 menggunakan dataset training, 98,20 menggunakan dataset testing, dan 94,26 menggunakan dataset other.
Co-Authors Achmad Affandi Adri Gabriel Sooai Adriel Ferdianto Agung Mega Iswara Ahmad Fathur Muhtadin Amalia, Siska Arda Surya Editya Arifin Arifin Arifin Arifin Arry Maulana Syarif Aryo Nugroho Aryo Nugroho Atyanta Nika Rumaksari Atyanta. N. Rumaksari Chandra Achmad Fauzi Chandra Eko Wahyudi Utomo Chastine Fatichah Choirina, Priska Choirina, Priska Christyowidiasmoro Christyowidiasmoro Diana Purwitasari Eko Mulyanto Yuniarno Endang Setyati Esther Irawati Setiawan Faiz Fathur Rahman Fanani, Nurul Zainal Fuad Rachmadi, Reza Gary Almas Samaita Grace Elva Averina Gunawan Herti Miawarni Herti Miawarni Herti Miawarni Herti Miawarni, Herti Hidayatillah, Rumaisah Holik, Nur Muhamad Hosyi’ah Rusdiana Iskandar Dzulkarnain Istas Pratomo, Istas Joan Santoso Khamid Khamid Khamid Khamid Lukman Hakim Lukman Zaman M Mahaputra Hidayat Matahari Bhakti Nendya, Matahari Bhakti Mauridhi Hery Mauridhi Hery Purnomo Mauridhi Hery Purnomo Maydlinne Liudyvia Mochamad Hariadi Muhammad Rifqi Mukhtar Muhtadin Muhtadin Nova Rijati Nurul Fadillah Nurul Zainal Fanani P., Mauridhy Hery Putra Wisnu AS Rachmadi, Reza Fuad Restuadi Studiawan Rosiani, Ulla Delfana Rumaisah Hidayatillah Sasmita, Wirat Moko Hadi Setijadi, Eko Supeno Mardi Susiki Nugroho, Supeno Mardi Tanisha Amalia Putri Ulla Delfana Rosiani Yosi Kristian Zahara, Soffa Zaini, Ahmad Zaman, Lukman