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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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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.
Analisis Sentimen E-Learning X Terhadap Antarmuka Pengguna Menggunakan Kombinasi Multinomial Naive Bayes Dan Pendekatan Design Thinking Huda, Baenil; Sembiring, Irwan; Setiawan, Iwan; Manongga, Danny; Purnomo, Hindriyanto Dwi; Hendry, Hendry; Fauzi, Ahmad; Lia Hananto, April; Tukino, Tukino
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 11 No 4: Agustus 2024
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.1147686

Abstract

Penelitian ini bertujuan untuk menganalisis sentimen pengguna terhadap antarmuka e-learning X menggunakan kombinasi Multinomial Naive Bayes dan pendekatan Design Thinking. Permasalahan yang dihadapi adalah banyaknya feedback negatif terkait antarmuka pengguna yang dianggap kurang intuitif. Data sentimen dari ulasan pengguna diklasifikasikan menggunakan algoritma Multinomial Naive Bayes, sementara Design Thinking digunakan untuk merancang solusi antarmuka yang lebih user-friendly. Hasilnya menunjukkan bahwa metode ini efektif meningkatkan sentimen positif pengguna, dengan perbaikan signifikan dalam pengalaman dan kepuasan pengguna terhadap antarmuka e-learning X, Serta rekomendasi untuk pengembangan aplikasi e-learning.   Abstract   This research aims to analyze user sentiment towards the e-learning interface X using a combination of Multinomial Naive Bayes and Design Thinking approaches. The problem faced was the large number of negative feedback regarding the user interface which was considered less intuitive. Sentiment data from user reviews is classified using the Multinomial Naive Bayes algorithm, while Design Thinking is used to design more user-friendly interface solutions. The results show that this method is effective in increasing positive user sentiment, with significant improvements in user experience and satisfaction with the X e-learning interface As well as recommendations for developing e-learning applications.
ANALISIS SISTEM LAYANAN PENDAFTARAN E-KTP MENGGUNAKAN FRAMEWROK FOR THE APPLICATION OF SYSTEM THINKING Ronny Julians, Adhe; Manongga, Danny; Hendry, Hendry
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 7 No. 1 (2023): JATI Vol. 7 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v7i1.6393

Abstract

Pelayanan terkait pembuatan e-KTP pada Dinas Kependudukan dan Pencatatan Sipil Kabupaten Mimika, hingga saat ini masih sering ditemui berbagai permasalahan didalam prosesnya, dimulai dari jauhnya jarak tempuh ke kantor terkait yang memakan waktu serta biaya yang tidak sedikit, proses pendaftaran yang lama karena antrian yang panjang, serta adanya penumpukan data yang mengakibatkan pelayanan menjadi tidak efisien dalam penggunaan waktu. Terkait dengan hal tersebut, maka tujuan dari penelitian ini adalah untuk memberikan solusi mengenai bagaiamana membuat model perancangan sistem layanan pendaftaran e-KTP berbasis web dengan menggunakan Framework For The Application Of System Thinking sebagai pendekatan dalam penyusunan penelitian, yang diharapkan dapat mempermudah didalam proses pendaftaran terkait dengan layanan e-KTP yang cepat, mudah, ramah, gratis dan mudah dijangkau.
PERANCANGAN SISTEM INFORMASI KEUANGAN BERBASIS WEB PADA GKS MAULIRU MENGGUNAKAN METODE RAPID APPLICATION DEVELOPMENT Panja, Eben; Manongga, Danny
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 7 No. 1 (2023): JATI Vol. 7 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v7i1.6401

Abstract

Sistem Informasi saat ini memiliki dampak yang cukup signifikan dalam suatu organisasi, baik swasta maupun sektor pemerintahan. Dengan maksud tersebut, maka perlu menjadi perhatian untuk terus mengembangkan beberapa proses bisnis dengan mengimplementasikan sistem informasi. Gereja Kristen Sumba (GKS) Mauliru adalah objek pada penelitian ini, dimana gereja ini berada di Kabupaten Sumba Timur, Provinsi Nusa Tenggara Timur. Masalah utama yang terjadi pada GKS Mauliru dan cabang gereja, terkhusus pada pengelolaan keuangan, dimana pengelolaan keuangan masih menggunakan excel serta pembuatan laporan yang dilakukan melalui pembukuan. Proses pelaporan keuangan dari tiap cabang banyak mengalami kendala seperti tiap cabang harus menulis pendapatan tiap minggunya dalam pembukuan dan proses pelaporan keuangan mingguan yang harus diantar ke gereja pusat dengan jarak yang cukup jauh. Dari masalah tersebut dikembangkan sistem informasi keuangan berbasis web pada GKS Mauliru. Pengembagan sistem menggunakan metode rapid application development dan pengujian sistem menggunakan blackbox testing. Hasil pengujian dari sistem informasi keuangan yang telah dikembangkan berfungsi dengan baik sesuai dengan kebutuhan operasional yang diharapkan dan dapat membantu pihak GKS mauliru dalam pengelolaan keuangan.
Understanding Data-Driven Analytic Decision Making on Air Quality Monitoring an Empirical Study Sembiring, Irwan; Manongga, Danny; Rahardja, Untung; Aini, Qurotul
Aptisi Transactions On Technopreneurship (ATT) Vol 6 No 3 (2024): November
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v6i3.459

Abstract

Air quality monitoring is increasingly relying on data-driven analytic decision-making tools to provide accurate and timely information, forming the background of this study. The objective is to understand the factors influencing the adoption and usage behavior of these tools using the Unified Theory of Acceptance and Use of Technology (UTAUT2) model. The method involves incorporating UTAUT2 constructs Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), Price Value (PV), Hedonic Motivation (HM), and Habit (H), alongside external variables such as Considered Risk (CR) and Considered Trust (CT). Data from 287 respondents were analyzed to assess their impact on Behavior Intention (BI) and Usage Behavior (UB). The results demonstrate that both trust and risk considerations significantly affect user behavior, underscoring the need to address these factors to enhance the adoption of air quality monitoring systems. In conclusion, this research provides valuable insights for developers and policymakers on improving the implementation and acceptance of data-driven technologies in environmental monitoring, thereby contributing to more effective air quality management.
Co-Authors Abas Sunarya, Po Abdi Samuel Mango Ade Iriani Agni Isador Harsapranata Agung Wibowo Albert Kriestian Novi Adhi Nugraha Andianti, Yohana Antonius Mbay Ndapamuri Anumi, Maria Grassella April Lia Hananto Apriliasari, Dwi Arny Lattu 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 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 Sophia Tri Satyawati 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