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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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Chatbot untuk Website Utama UK Petra dengan Hidden Markov Model dan k-Nearest Neighbor untuk Generate Jawaban Kevin Koesoemo; Alexander Setiawan; Indar Sugiarto
Jurnal Infra Vol 9, No 2 (2021)
Publisher : Jurnal Infra

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Abstract

Petra Christian University has various services for general information about university majors and student admissions, such as social media and WhatsApp. However, these services still limited by number and working time of operators as human. Therefore, with this chatbot, information about PCU can be found anytime. Chatbot Study by S. C. P & Afrianto needs method to match chatbot question with the dataset. This thesis uses two methods, namely kNN (k-Nearest Neighbor) and HMM (Hidden Markov Model) to solve these problem. In this chatbot, it will try to combine and compare these two methods, and see if it can produces answers that can be understood and in accordance with various difficulty questions given. The kNN is used as a classification for questions given to chatbot which approximately match with questions on the chatbot’s knowledge base. HMM is used to assemble answer words from the selected knowledge base. Chatbot’s answers will be tested in terms of validity of the answers by two respondents (Public Relation and Admission staff) also the length of time it takes to produce answers. The results of the chatbot with kNN has an accuracy of 64.44% (45 questions), with average system runtime of 0.08 seconds. While the results of chatbot with kNN-HMM produces random and irregular answers, with average system runtime of 0.12 seconds, cause by HMM which is a probability based method.
Klasifikasi dalam Pembuatan Portal Berita Online dengan Menggunakan Metode BERT Jehezkiel Hardwin Tandijaya; Liliana Liliana; Indar Sugiarto
Jurnal Infra Vol 9, No 2 (2021)
Publisher : Jurnal Infra

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Abstract

Internet helps human by making various information from many online news platform accessible. But nowadays, there are a lot of news that can be accessed in different online news platform and needs to be categorized. The news that can be accessed in some of the sources don’t have high credibility about an event, because the publishers use false and misleading information to push their agendas. So in order to check the credibility of an event, it is needed to also read from other sources and not only from 1 source. However, this is not effective because the reader has to look for another news source with different URL address. In this research scraping will be done to retrieve the news that are available in a news platform. After the scraping process is done, the news will be classified to determine the category of the news. The method that will be used is Bidirectional Encoder Representations from Transformers. From the testing of this research, the news can be retrieved and classified. The testing with a pre-trained model indobenchmark /indobert-base-p1 get a very good result where the accuracy reaches 87.548%.
Skill Upgrading untuk Meningkatkan Kompetensi Siswa dan Guru Di SMK Kristen Petra Handy Wicaksono; Indar Sugiarto; Tience Debora Valentina
Society : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol. 2 No. 2 (2022): Vol.2 No.2, April 2022
Publisher : Universitas Dinamika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37802/society.v2i2.216

Abstract

Kompetensi siswa dan guru SMK Kristen Petra perlu ditingkatkan untuk dapat menghadapi tantangan di masa mendatang. Setelah melakukan persiapan, pelatihan soft skill (dengan tema: pentingnya tanggung jawab dan berani menghadapi tantangan) dan hard skill (terkait pemrograman Programmable Logic Controller – PLC) dilakukan secara online, diikuti dengan penyerahan training kit PLC serta pendampingan untuk peserta (guru) yang akan mengikuti sertifikasi kompetensi bidang PLC. Para peserta menilai pelatihan – pelatihan tadi bermanfaat dan tepat sasaran untuk meningkatkan tanggungjawab dan keberanian menerima tantangan (53.3 % sangat setuju, dan 46.7 % setuju) serta untuk meningkatkan pengetahuan dan skill dalam pemrograman PLC (46.7 % sangat setuju, 46.7 % setuju). Sebuah training kit PLC juga telah dihibahkan ke SMK Kristen Petra untuk media eksperimen di sekolah. Pelatihan dan pendampingan terbukti efektif karena dua orang guru yang telah mengikuti pelatihan berhasil mendapatkan sertifikat dari BNSP setelah melalui uji kompetensi.
From Adaptive Reasoning to Cognitive Factory: Bringing Cognitive Intelligence to Manufacturing Technology Indar Sugiarto; Cristian Axenie; Jörg Conradt
International Journal of Industrial Research and Applied Engineering Vol 1, No 1 (2016)
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1186.697 KB) | DOI: 10.9744/JIRAE.1.1.1-10

Abstract

There are two important aspects that will play important roles in future manufacturing systems: changeability and human-machine collaboration. The first aspect, changeability, concerns with the ability of production tools to reconfigure themselves to the new manufacturing settings, possibly with unknown prior information, while maintaining their reliability at lowest cost. The second aspect, human-machine collaboration, emphasizes the ability of production tools to put themselves on the position as humans’ co-workers. The interplay between these two aspects will not only determine the economical accomplishment of a manufacturing process, but it will also shape the future of the technology itself. To address this future challenge of manufacturing systems, the concept of Cognitive Factory was proposed. Along this line, machines and processes are equipped with cognitive capabilities in order to allow them to assess and increase their scope of operation autonomously. However, the technical implementation of such a concept is still widely open for research, since there are several stumbling blocks that limit practicality of the proposed methods. In this paper, we introduce our method to achieve the goal of the Cognitive Factory. Our method is inspired by the working mechanisms of a human’s brain; it works by harnessing the reasoning capabilities of cognitive architecture. By utilizing such an adaptive reasoning mechanism, we envision the future manufacturing systems with cognitive intelligence. We provide illustrative examples from our current research work to demonstrate that our proposed method is notable to address the primary issues of the Cognitive Factory: changeability and human-machine collaboration.
Omni-Directional Mobile Robot Control using Raspberry Pi and Jetson Nano Evert Oneil; Indar Sugiarto
International Journal of Industrial Research and Applied Engineering Vol 4, No 2: OCTOBER 2019
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jirae.4.2.57-62

Abstract

The use of robots continues to increase in various fields in society today. Current developments require robots that are more effective and efficient in its application, especially in terms of its movement. This research is intended to design robots that move omni-directionally, making it easier to move in all directions by using the omniwheels, and the robots can detect simple object around them. The robot using 3 DC motors with encoder as feedback. System movement is controlled using Raspberry Pi 4, to move the robot to destination postition from user’s input. For robot to be able to detect certain object, the robot is equipped with infrared sensor for measure the distance and a camera for image processing purpose with jetson nano as a controller. By using inverse kinematics and odometry calculations for robot movement, it has an error of 9.51% on the x-axis and 8.12% on the y-axis at the robot's final position. The robot can detect objects using infrared sensors with error rate 0.87% and measure object sizes using a camera and image processing with error rate of 30.02% for object’s width readings and 41.8% for object’s height readings.
Analisis Sentimen Dari Keywords Yang Dimasukan Pengguna Di Twitter Indonesia Untuk Penunjang Pembelajaran Strategi Komunikasi Di Program Studi Ilmu Komunikasi Universitas Kristen Petra Dengan Metode Cnn-Bidirectional Lstm Andrianto Saputra Linardi Lie; Djoni Haryadi Setiabudi; Indar Sugiarto
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

To increase online media traffic, the first effort made by online media is to examine the trending phenomenon with the right marketing strategy. One of the methods that online media is used is a communication strategy that utilizes the sentiment analysis method. In reality, students of Communication Science Major at Petra Christian University are not optimally using sentiment analyst system because the sentiment analysis system for the Communication Studies Study Program (Netray) cannot be run by more than one student or is not used simultaneously and the price of the application is still not affordable if the students want to subscribe Netray. So a sentiment analysis system is needed to support the learning of the Communication Science Major at Petra Christian University. In previous related research, there was research that discussed the analysis of the #crowdfunding campaign on Twitter but there was not include sentiment analysis, there are only topological analysis, spatial analysis and others analysis. In addition, there are studies that use various deep learning methods of sentiment analysis, by researching CNN, DNN, RNN, Bi-Lstm, but none of them combine these methods. So it can be concluded that research will be made that analyzes sentiment analysis and combines deep learning methods. Sentiment analysis is the process of using text analytics to obtain various data sources from the internet and various social media platforms. Sentiment analysis can be utilized with artificial intelligence or with computing, because it is more efficient . Sentiment analysis can be complemented by methods from artificial intelligence systems, namely deep learning CNN-BILSTM. CNN-BILSTM is a combination of the two methods of CNN and bidirectional LSTM where CNN is the input layer and bidirectional LSTM is the layer that extracts features from the input. The dataset used in this application is retrieved from github by adopting the CC BY-NC (Common Creative Non Commercial) License. Data used in the deep learning model which contains a collection of Indonesian tweets containing neutral, positive, negative sentiments.From two testing this thesis using twitter as the online media. From the first test, 20 tweets were searched, the tweet contain "Shin tae yong” and yielded an accuracy of 30%. The second test was tested by 45 students of the Petra Christian University Communication Science Program at Petra Christian University Surabaya in the Q2.505 building where this application was tried and applied, after that the application was assessed with a satisfaction questionnaire which resulted in an average score of 4.01, so this application can meet the needs of the Petra Christian University Communication Science Program with the initial target of a satisfaction questionnaire of 3.75.
Aplikasi Sistem Pengontrolan Turtle Tub Untuk Pemeliharaan Kura-Kura Red Belly Nelsoni Dengan Arduino Kevin Pramana Pongmasak; Silvia Rostianingsih; Indar Sugiarto
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Having turtles, especially Red Belly Nelsoni turtle is very common, but usually the owner don’t really know how to properly taking care of their turtles, according to the parameters needed in turtle maintenance. The problem that the author wants to solve is by utilizing Blynk application and Internet of Things tools that has a function to control, monitor and maintain all parameters that needed in turtle maintenance, so that the owner of the turtle can more easily taking care of the turtle in the turtle tub. The test was carried out by giving 2 turtle tubs containing Red Belly Nelsoni turtles to 2 volunteers who carried out the turtle care and maintenance in different ways. From the result of the test carried out, the application has been able to help the volunteers in taking care of the turtles according to the parameter aspects that needed in turtle maintenance.
Hand Symbol Classification for Human-Computer Interaction Using the Fifth Version of YOLO Object Detection Sugiarto Wibowo; Indar Sugiarto
CommIT (Communication and Information Technology) Journal Vol. 17 No. 1 (2023): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v17i1.8520

Abstract

Human-Computer Interaction (HCI) nowadays mostly uses physical contact, such as people using the mouse to choose something in an application. However, there are certain problems that people face in using conventional HCI. The research tries to overcome some problems when people use conventional HCI using the computer vision method. The research focuses on creating and evaluating the object detection model for classifying hand symbols. The research applies the fifth version of YOLO with the architecture of YOLOv5m to classify hand symbols in real time. The methods are divided into three steps. Those steps are dataset creation consisting of 100 images in each class, training phase, and performance evaluation of the model. The hand gesture classes made in the research are ‘ok’, ‘cancel’, ‘previous’, ‘next’, and ‘confirm’, the dataset is made by the researchers custom. After the training phase, the validation results show 93% for accuracy, 99% for precision, 100% for recall, and 99% for F1 score. Meanwhile, in real-time detection, the performance of the model for classifying hand symbols is 80% for accuracy, 95% for precision, 84% for recall, and 89% for F1 score. Although there are differences, it still acceptable for the research and can be improved in future research.
RANCANG BANGUN SISTEM METER LISTRIK PRABAYAR DENGAN PEMBAYARAN MENGGUNAKAN QRIS DI RUMAH KOST Gregorio Diovani Wahanie; Resmana Lim; Indar Sugiarto
Jurnal Teknik Elektro Vol. 16 No. 1 (2023): Maret 2023
Publisher : Institute of Research and Community Outreach

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jte.16.1.5-10

Abstract

Pada penelitian ini dikembangkan suatu sistem yang dapat memantau konsumsi listrik dengan metode memasang meter listrik digital berbasis mikrokontroler. Tidak seperti kWh Meter Prabayar PLN yang Offline, namun meter prabayar ini terhubung dengan internet/Online sehingga tidak memerlukan motode token, dan dapat dimonitor dan top-up pulsa listrik dapat dilakukan langsung secara online. Sistem ini nantinya akan terintergasi secara online melalui aplikasi payment gateway untuk keperluan transaksi secara non-tunai. Sistem ini terdiri dari mikrokontroler ESP32, bagian output terdiri dari LCD 16x2, buzzer, SSR dan LED, dan bagian input terdapat sensor PZEM untuk mengukur energi listrik yang digunakan. Sistem ini juga dapat dimonitor secara internet berbasis web. Hasil Pengujian akurasi pengukuran energi PZEM dengan modul pembanding sejenis SDM120 secara pembacaan dan Analisa matematis menujukan parameter yang mendekati sama. Pengujian pengisian pulsa berhasil melakukan pengisian ulang pulsa listrik sebesar 1 kWh dengan tarif yang dipasang sebesar Rp 1500,- per kWh. Web dashboard yang dikembangkan telah menunjukan hasil fungsi monitoring dan report dari sistem meteran yang dibuat.
Transformasi kebun hidroponik konvensional menjadi energy-efficient smart urban farming berbasis IoT Sugiarto, Indar; Yogatama, Astri; Tyasmoro, Setyono Yudo
Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) Vol 7 No 3 (2024)
Publisher : University of Islam Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33474/jipemas.v7i3.21135

Abstract

Urban Farming adalah teknik bercocok tanam di lingkungan perkotaan dengan memanfaatkan area, seperti halaman rumah, taman, atau bahkan atap bangunan. Untuk mengoptimalkan manfaat dari urban farming, perlu tata kelola yang baik dan terkontrol mulai dari proses awal persiapan, penanaman, perawatan sampai panen dan pasca panen. Di Surabaya ditemukan urban farming berupa kebun hidroponik yang dimiliki oleh KRPL Tambakrejo Surabaya yang tidak berfungsi dengan baik. Melalui kegiatan pengabdian masyarakat dengan metode ABCD (Asset Based Community Development), dilakukan upaya pemberdayaan dan perbaikan dengan mentransformasi kebun hidroponik konvensional mereka menjadi kebun hidroponik cerdas. Metode tersebut diimplementasi mulai dari identifikasi permasalahan yang dihadapi KRPL Tambakrejo, yaitu kesulitan pasokan air bersih, serangan hama tikus, sumber listrik yang terbatas dan cara pemasaran produk yang kurang optimal. Proses transformasi dilakukan melalui revitalisasi kebun hidroponik konvensional menjadi kebun hidroponik cerdas berbasis IoT dan bertenaga surya. Dari hasil analisa setelah dilakukan transformasi tersebut, kebun hidroponik milik KRPL Tambakrejo bisa menghasilkan keuntungan minimal Rp 4.032.000 pertahun. Selain sangat hemat energi listrik dan dapat dipantau secara langsung lewat internet, kebun hidroponik tersebut saat ini juga sudah bebas dari hama tikus.
Co-Authors Agustinus Bimo Gumelar Alexander Setiawan Andreas Prasetyo Andrew Wijaya Andrianto Saputra Linardi Lie Andy Susanto Astri Yogatama Astri Yogatama Candra, Ranggastika Prahlada Cristian Axenie Derry Pramono Adi Djoni Haryadi Setiabudi 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 Kevin Pramana Pongmasak 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 Silvia Rostianingsih 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