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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmu dan Teknologi Kelautan Tropis IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Informatika JURNAL SISTEM INFORMASI BISNIS Proceedings of KNASTIK Jurnal Simetris Elkom: Jurnal Elektronika dan Komputer Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Scientific Journal of Informatics Proceeding SENDI_U Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization International Journal of Artificial Intelligence Research INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA Faktor Exacta INOVTEK Polbeng - Seri Informatika MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Aptisi Transactions on Management Aptisi Transactions on Technopreneurship (ATT) Magisma: Jurnal Ilmiah Ekonomi dan Bisnis JUKANTI (Jurnal Pendidikan Teknologi Informasi) JATI (Jurnal Mahasiswa Teknik Informatika) Journal Sensi: Strategic of Education in Information System Abdimasku : Jurnal Pengabdian Masyarakat INFOKUM Aiti: Jurnal Teknologi Informasi Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknik Informatika (JUTIF) Jurnal Kependidikan: Jurnal Hasil Penelitian dan Kajian Kepustakaan di Bidang Pendidikan, Pengajaran dan Pembelajaran Jurnal Dimensi DKV Seni Rupa dan Desain Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat Eduvest - Journal of Universal Studies CENDEKIA PENDIDIKAN Jurnal Rekayasa elektrika Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Jurnal Informatika: Jurnal Pengembangan IT Jurnal Pendidikan Teknologi Informasi (JUKANTI) INTERNAL (Information System Journal) Pendekar: Jurnal Pendidikan Berkarakter Blockchain Frontier Technology (BFRONT) Scientific Journal of Informatics BACA: Jurnal Dokumentasi dan Informasi International Journal of Information Technology and Business JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Danny Manongga
Universitas Kristen Satya Wacana
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Neuroscience Social Sciences Transportation Other

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Evaluation of Critical Thinking Disposition in Learning using E-Learning Tukino Paryono; Gunawan Gunawan; Sutarto Sutarto; Danny Manongga
INTERNAL (Information System Journal) Vol. 5 No. 2 (2022)
Publisher : Masoem University

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

Abstract

Critical thinking disposition includes seven habits as a motivation in analyzing problems to make decisions in the online learning system applied at the University. E-Learning application as online learning media which is equipped with various facilities to support Lecturer activities.  The purpose of this study was to determine the differences in critical thinking disposition based on the gender of the lecturer and the level of the Lecturer's Academic Position.  The results of the analysis of the calculation of the average score on the evaluation of critical thinking dispositions based on the gender of women (M=3.02) and men (M=3.23) means that there are differences in critical thinking although relatively little. The difference is found in statements related to reading habits, digging and uploading material, easy to receive input, studying material, reviewing assignments and being open.  Meanwhile, the f-count value is 0.903 which is smaller than the f-table is 3.24 at p <0.50, this indicates that there is no significant difference in the Lecturer's Academic Position level in applying critical thinking dispositions in using E-Learning applications for the learning process. Two indicators, gender and Lecturer's Academic Position evaluated with 14 statements for 7 aspects have not shown significant differences, this provides an opportunity to be studied more deeply in compiling statement indicators and can be related to the development of Lecturer's critical thinking disposition with taxono bloom.
Sentiment Analysis of e-Government Service Using the Naive Bayes Algorithm Winny purbaratri; Hindriyanto Dwi Purnomo; Danny Manongga; Iwan Setyawan; Hendry Hendry
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 23 No 2 (2024)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i2.3272

Abstract

E-Government which involves the use of communication and information technology to provide Public services have three obstacles. One of these obstacles is the implementation of e-Government by autonomous regional governments is still carried out individually. Apart from that, implementing the website regions are also not supported by efficient management systems and work processes, this is partly the case This is largely due to the lack of preparation of regulations, procedures and limited resources man. Apart from that, many local governments consider implementing e-Government only involves developing local government websites. More precisely, the implementation of e-Government It is only limited to the maturity stage and ignores the three other important stages that need to be completed. The aim of this research is to determine the level of public approval for government application services. This research uses the Naive Bayes Classifier approach as the methodology. The data sources used in this research consist of user reviews and comments obtained from Google Play Store. The results of this investigation produce a level of precision The highest is achieving a score of 83%. Additionally it shows an accuracy rate of 83%,levelcompleteness is 100%, and F-measure is 90.7%.
Toddler Stunting Consulting Chatbot using Rasa Framework Wiwien Hadikurniawati; Sutarto Wijono; Danny Manongga; Irwan Sembiring; Kristoko Dwi Hartomo
Jurnal Rekayasa Elektrika Vol 19, No 4 (2023)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v19i4.33014

Abstract

Chatbots are artificial intelligence software that can communicate with users to assist them in certain tasks or provide information. They can reduce the need for human interaction and make processes more efficient. However, when it comes to more specific tasks related to handling the problem of stunting in toddlers these services are usually unable to provide an appropriate response. Chatbots were created with the help of the Rasa framework, which was designed to adapt the various components of natural language understanding (NLU). This adjustment allows him to understand more complex questions from respondents such as those related to healthy feeding of toddlers. This research explained the use of the Rasa framework to enhance their capabilities, describe the testing and evaluation process, and present the performance results of the chatbot model in addressing the issue of stunting in toddlers. The model is then tested using a confusion matrix, precision, accuracy, and F1 score, which measures how accurate the chatbot's responses are to the user's input. The model had a precision, accuracy, and F1 score of 0.928, 0.932 and 0.930, respectively.
EVALUASI KETERGUNAAN WEBSITE PERPUSTAKAAN UNIVERSITAS KRISTEN SATYA WACANA DENGAN MENGGUNAKAN METODE SYSTEM USABILITY SCALE Madawara, Herdin Yohnes; Manongga, Danny; Hendry, Hendry
Jurnal Pendidikan Teknologi Informasi (JUKANTI) Vol 6 No 2 (2023): JURNAL PENDIDIKAN TEKNOLOGI INFORMASI (JUKANTI) EDISI NOPEMBER 2023
Publisher : Program Studi Pendidikan Informatika, Universitas Citra Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37792/jukanti.v6i2.933

Abstract

This research was conducted with the aim of evaluating the usability of the Satya Wacana Christian University (UKSW) Library website using the System Usability Scale (SUS) method. This research also aims to identify areas that need to be improved in the UKSW Library website. Respondents in this study were UKSW students who had used the library website. This study used the SUS questionnaire consisting of 10 questions with a 5-point Likert scale. The results of the SUS calculation show that the average value of the usability of the UKSW Library website is 59.514, which is in the medium or "OK" category. Further analysis shows that areas that need to be improved are clarity of information, ease of navigation, and visual appearance. This research is expected to provide input for the UKSW Library in developing the website in order to increase usability and meet the needs of its users. The conclusion of this research is that the UKSW Library website still has some areas that need to be improved to increase usability.
The Adoption of Blockchain Technology the Business Using Structural Equation Modelling Aini, Qurotul; Manongga, Danny; Sediyono, Eko; Joko Prasetyo, Sri Yulianto; Rahardja, Untung; Santoso, Nuke Puji Lestari
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 18, No 1 (2024): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.82107

Abstract

There are many aspects of readiness that must be considered when implementing technological breakthroughs, the business sector is still relatively slow in adopting blockchain technology. However, considering that blockchain technology is still in its early stages of development and has many potential applications, it is necessary to conduct empirical studies on the factors influencing its application in the industry. The problem of this study is to develop an appropriate framework based on how well its features match the needs of the business sector. This research method uses data collection using online questionnaires to obtain information from 86 respondents. The current study also utilizes the Smart PLS 4 model to produce a structural hypothetical model. The results of this study find a significant influence on Revolutionary Innovation by enriching the literature on the relationship between Blockchain, Big Data and the Business Sector, which is expanded by adding new variables. The novelty of this research identifies potential utilization, analyzes internal and external factors, and identifies how blockchain disrupts the business sector. The purpose of this study is to assess how blockchain technology is currently used in the business sector for data provision as a theoretical information technology innovation
Analisis konten budaya kolaboratif berbasis Grounded Theory menggunakan Text Mining Julians, Adhe Ronny; Manongga, Daniel Herman Fredy; Hendry, Hendry
AITI Vol 21 No 2 (2024)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v21i2.230-250

Abstract

Creating a collaborative culture of innovation in an organization is very important today. A collaborative culture of innovation is not just about physically working together but also about creating an environment that supports open communication, appreciation for new ideas, and acceptance of risk. Organizations that embrace this culture can create significant added value and thrive in an ever-changing environment. This research aims to conduct a content analysis of several Grounded Theory-based reputable scientific articles using Text Mining, which involves using coding techniques to classify information and identify certain categories or codes representing certain text elements. The analysis results are a conceptual network model that connects elements that influence collaborative culture on innovation, such as Openness, Diversity, Shared Goals, Trust, Teamwork, Support, and Use of Technology. Organizations use this model to create a collaborative culture of innovation in their environment, and it can be used in further research to test the model using statistical tests.
Comparing logistic regression and extreme gradient boosting on student arguments Wahyuningsih, Tri; Manongga, Danny; Sembiring, Irwan
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp3119-3128

Abstract

Identifying the effectiveness level and quality of students' arguments poses a challenge for teachers. This is due to the lack of techniques that can accurately assist in identifying the effectiveness and quality of students' arguments. This research aims to develop a model that can identify effectiveness categories in students' arguments. The method employed involves the logistic regression+XGBoost algorithm combined with separate implementations of term frequency-inverse document frequency (TF-IDF) and CountVectorizer. Student argument data were collected and processed using natural language processing techniques. The research results indicate that TF-IDF outperforms in identifying effectiveness classes in student arguments with an accuracy of 66.20%. The multi-output classification yielded an accuracy of 89.32% in the initial testing, which further improved to 92.34% after implementing one-hot encoding. A novel finding in this research is the superiority of TF-IDF as a technique for identifying effectiveness classes in student arguments compared to CountVectorizer. The implications of this research include the development of a model that can assist teachers in identifying the effectiveness level of students' arguments, thereby improving the quality of learning and enhancing students' argumentative competence.
Membaca Sinyal Electroencephalogram (EEG) Dalam Menangkap Tingkat Emosi (Berdasarkan Ontologi) Devianto, Yudo; Sediyono, Eko; Prasetyo, Sri Yulianto Joko; Manongga, Danny
Faktor Exacta Vol 17, No 2 (2024)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v17i2.20878

Abstract

Philosophically based EEG (electroencephalography) signal data processing is an engaging interdisciplinary approach and opens up new perspectives in understanding brain function. In this context, it is necessary to examine data from a technical or biological point of view and consider its metaphysical, epistemological and even ontological aspects. Ontology is a branch of metaphysics that deals with objects and the types of objects that exist according to one's metaphysical (or even physical) theory, their properties, and their relationship. This article attempts to provide a philosophical view of science based on ontology for processing EEG signal data, the data source of which is taken from brain waves. With the results of trials using the Artificial Neural Network (ANN) classification, an accuracy value of 46.73 was obtained. The Convolutional Neural Network (CNN) algorithm can also be used to process EEG signal data to determine a person's emotional level; this is proven in research results; although the overall accuracy of emotion recognition has increased significantly, several problems cause low accuracy in the DEAP and DREAMER data sets. There are also results of other experiments carried out using CNN, and the experimental results show that the weight of channels related to emotions is greater than that of different channels. The Continuous Capsule Network (CCN) algorithm and Deep Neural Network (DNN) algorithm can also be used to process EEG signal data to determine the level of emotion.
Systematic Literature Review: The Role of Artificial Intelligence in Digital Marketing Yusup, Muhamad; Wijono, Sutarto; Manongga, Danny; Sembiring, Irwan; Prasetyo, Sri Yulianto Joko; Wellem, Theophilus
Journal Sensi: Strategic of Education in Information System Vol 10 No 1 (2024): Journal Sensi
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sensi.v10i1.3117

Abstract

Artificial Intelligence has given a competitive advantage and can increment competition and benefit or Return on Venture in Computerized Showcasing. This article points to recognize diary sources related to the part of Fake Insights, explanatory strategies, applicabilities, and execution measurements on the part of AI in Computerized Promoting from 2015 to 2022. Based on the incorporation and prohibition criteria outlined, it was established that 8 things related to the article were distributed in 2015 and 2022. This article is organized utilizing the SLR strategy which is characterized as a preparation for recognizing, evaluating and evaluating the all accessible investigation to supply answers to four Research Questions. With Suggestions, and add up to of eleven investigation strategies, seventeen usage and nine execution measurements have been distinguished that can be utilized by analysts for future inquire about the part of Manufactured Insights in Computerized Promoting.
Enhancing Machine Learning with Low-Cost P M2.5 Air Quality Sensor Calibration using Image Processing Rahardja, Untung; Aini, Qurotul; Manongga, Danny; Sembiring, Irwan; Ayu Sanjaya, Yulia Putri; Rahardja.,M.T.I.,MM, Dr. Ir. Untung
APTISI Transactions on Management (ATM) Vol 7 No 3 (2023): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v7i3.2062

Abstract

Low-cost particulate matter sensors, due to their increased mobility compared to reference monitors, are transforming air quality monitoring. Calibrating these sensors requires training data from reference monitors, which is traditionally done through conventional procedures or by using machine learning techniques. The latter outperforms traditional methods, but still requires deployment of a reference monitor and significant amounts of training data from the target sensor. In this study, we present a cutting-edge machine learning-based transfer learning technique for rapid sensor calibration with Co-deployment with reference monitors is kept to a minimum. This approach integrates data from a small number of sensors, including the target sensor, reducing the dependence on a reference monitor. Our studies reveal that In recent research, a transfer learning method using a meta-agnostic model has been proposed, and the results proved to be much more effective than the previous method. In trials, calibration errors were successfully reduced by up to 32\% and 15\% compared to the best raw and baseline observations. This shows the great potential of transfer learning methods to increase the effectiveness of learning in the long term. These results highlight the potential of this innovative transfer learning technique for rapidly and accurately calibrating low-cost particulate matter sensors using machine learning.
Co-Authors Abas Sunarya, Po Abdi Samuel Mango Ade Iriani Agni Isador Harsapranata Agung Wibowo Albert Kriestian Novi Adhi Nugraha Antonius Mbay Ndapamuri Anumi, Maria Grassella April Lia Hananto Apriliasari, Dwi Astriyer J. Nahumury Ayu Sanjaya, Yulia Putri Baihaqi, Kiki Ahmad Bani, Benediktus Budhi Kristianto Budi Santoso Cahyaningtyas, Christian Daniawan, Benny Dendy Kurniawan Destiyani, Gati Devianto, Yudo Dwi Hosanna Bangkalang Efendy, Rifan Eko Nur Hermansyah Eko Sediyono Elfira Umar Elmanda, Vonda Erwianta Gustial Radjah Evangs Mailoa Evi Maria Faturahman, Adam Fauzi Ahmad Muda Filimdity, Elsa K. Frederik Samuel Papilaya Girinzio, Iqbal Desam Gunawan Gunawan Henderi Hendry Hendry, - Henry Adhi Sulistyo Herdin Yohnes Madawara Hindriyanto Dwi Purnomo Huda, Baenil I Ketut Suada Irwan Sembiring Iwan Setiawan Iwan Setyawan Johan Jimmy Carter Tambotoh Joko Siswanto Julianingsih, Dwi Julians, Adhe Ronny Krismiyati Kristoko Dwi Hartomo Lorna Yertas Baisa Lukman Santoso Madawara, Herdin Yohnes Mango, Abdi Samuel Mangoki, Willson Martza Merry Swastikasari Muhamad Yusup Muhammad Ryza Awwali , Sulartopo, Muhammad Ryza Awwali , Nina Setiyawati Panja, Eben Penidas Fiodinggo Tanaem Penidas Fodinggo Tanaem Perdana, Eric Megah Po Abas Sunarya Priatna , Wowon Pudjajana, Andre Maureen Pukada, Michael Alan Hirdi Purbaratri, Winny Purnomo, Hendryanto Dwi Qurotul Aini Radius Tanone Rahardja.,M.T.I.,MM, Dr. Ir. Untung Ravensca Matatula Ravensca Matatula Reni Veliyanti Rimes Jopmorestho Malioy Rivort Pormes Rivort Pormes Rivort Pormes, Rivort Ronny Julians, Adhe Saian, Septovan Dwi Suputra Santoso, Joseph Teguh Santoso, Nuke Puji Lestari Selfiana Pandie Sri Yulianto Joko Prasetyo Stefanus Christian Relmasira Suharyadi Sulistyo, Henry Adhi Sutarto Sutarto Sutarto Wijono Swastikasari, Martza Merry Theopillus J. H. Wellem Tri Wahyuningsih Tukino Tukino, Tukino Untung Rahardja Victor Peter Lodewyk Duan Winny purbaratri Wiwien Hadikurniawati Yari Dwikurnaningsih Yerik Afrianto Singgalen Yessica Nataliani