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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) JURNAL SISTEM INFORMASI BISNIS Jurnal Peternakan Integratif Elkom: Jurnal Elektronika dan Komputer Journal of Education and Learning (EduLearn) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Prosiding SNATIF Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika JUITA : Jurnal Informatika Scientific Journal of Informatics Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization AdBispreneur Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JIKO (Jurnal Informatika dan Komputer) JURNAL MEDIA INFORMATIKA BUDIDARMA Information System for Educators and Professionals : Journal of Information System SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Informatika Aptisi Transactions on Management JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Aptisi Transactions on Technopreneurship (ATT) EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Jurnal Mnemonic Journal Sensi: Strategic of Education in Information System Indonesian Journal of Electrical Engineering and Computer Science Abdimasku : Jurnal Pengabdian Masyarakat Computer Science and Information Technologies Jurnal Bumigora Information Technology (BITe) Aiti: Jurnal Teknologi Informasi Infotech: Journal of Technology Information Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknik Informatika (JUTIF) Indonesian Journal of Applied Research (IJAR) Journal of Applied Data Sciences JOINTER : Journal of Informatics Engineering Jurnal Indonesia : Manajemen Informatika dan Komunikasi Journal of Information Technology (JIfoTech) Edutik : Jurnal Pendidikan Teknologi Informasi dan Komunikasi Nusantara of Engineering (NOE) Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat Jurnal Rekayasa elektrika Jurnal INFOTEL SmartComp Jurnal Indonesia : Manajemen Informatika dan Komunikasi Blockchain Frontier Technology (BFRONT) Scientific Journal of Informatics JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Irwan Sembiring
Universitas Kristen Satya Wacana
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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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.
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 SERANGAN CYBER MENGGUNAKAN HONEYPOT PADA WEB BERBASIS CLOUD Pamungkas, Bayu Setyanto; Sembiring, Irwan
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 4 No. 3 (2023): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v4i3.325

Abstract

Cloud computing has a fairly high-security system, however as it can be accessed from anywhere via the internet network, it does not rule out the possibility that the system is safe from cyberattacks, such as Port Scanning, Brute Force Attacks, Malware Attacks, and other types of cyberattacks, T-Pot Honeypot is an all in one system from Honeypot which is an additional security system to detect, trap attacks not to be able to enter the main system. Based on the research results, the implementation of this T-Pot Honeypot can detect attacks and successfully trap attackers by providing false information such as a list of open ports that are the target of the attacker's search. The log data of the detected attack results are processed by the Honeypot system and forwarded into graphs and diagrams that can be seen through the Kibana Dashboard, making it easier for administrators to monitor attack anomalies carried out by attackers so that they can be used to improve security further.
Progress in Non-Invasive Cognitive Brain-Computer Interface and Implications for Mind-Uploading Astawa, I Wayan Aswin Dew; Purnomo, Hindriyanto Dwi; Sembiring, Irwan
International Journal of Artificial Intelligence Research Vol 8, No 1 (2024): June 2024
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v8i1.1133

Abstract

Mind-uploading, the vision of transferring human consciousness into a digital realm, relies on a profound comprehension of the brain and cutting-edge technology. Non-invasive cognitive Brain-Computer Interfaces (BCI) offer a promising avenue for delving into neural activity and bridging the brain-machine gap. This research explores the potential of non-invasive cognitive BCI in realizing mind-uploading through a systematic literature review (SLR), analyzing recent research that focuses on its current progress and implications for mind-uploading. The SLR unveils significant strides in non-invasive cognitive BCI, demonstrating increased precision in recording and decoding cognitive processes and fostering a deeper understanding of these processes. This progress is attributed to a diverse range of emerging feature extraction and decoding methods, transforming subtle neural signals into interpretable commands. Notably, advancements in signal processing and neuroimaging techniques enhance communication speed and clarity between the brain and computer. Furthermore, the development of cost-effective methods, frameworks, and hardware holds the promise of broader accessibility to BCI technology. However, significant hurdles remain. The computational demands of current cognitive BCI systems pose a substantial challenge, while the scarcity of high-quality training datasets hampers algorithm development and accuracy. The poor signal quality causes difficulties in recording neural complexity and hampers accuracy. In conclusion, non-invasive cognitive BCI has significant potential to pave the way for mind-uploading. However, its limitations, make their capabilities remain insufficient to fully realize this ambitious vision. This highlights the critical need for sustained research and innovation to bridge the gap between current understanding and the exciting realm of mind-uploading.
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.
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.
DESAIN LFSR SKEMA A5/1 DENGAN SEMBILAN FUNGSI UNTUK PENGAMANAN SERTIFIKAT TANAH DIGITAL Nugroho, Samuel Danny; Sediyono, Eko -; Sembiring, Irwan -
JURNAL INFORMATIKA DAN KOMPUTER Vol 8, No 2 (2024): September 2024
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiko.v8i2.1331

Abstract

Penelitian ini merancang Linear Feedback Shift Register (LFSR) skema A5/1 menggunakan sembilan fungsi umpan balik, dan mengimplementasikan dalam sistem pengamanan sertifikat tanah digital menggunakan hybrid kriptografi dengan menggubungkan algoritma RSA dan Stream Cipher Rabbit. Hasil pengujian diperoleh, rancangan algoritma dapat menghasilkan luaran bit yang lebih acak dan konsisten dibandingkan dengan penggunan blok fungsi yang lebih kecil. Proses enkripsi dan dekripsi menunjukan rancangan Hybrid RSA-Rabbit merupakan algoritma yang optimum, karena memiliki kompleksitas waktu dan memori yang minimum. Pengujian korelasi menunjukkan plainteks dan cipherteks tidak berhubungan secara statistik, bahkan dalam kriteria Guilford  berada dalam kategori “sedikit”. Sehingga rancangan algoritma dapat menyembunyikan informasi penting pada sertifikat. Hasil ini menunjukkan bahwa rancangan Hybrid RSA-Rabbit  dan dapat digunakan dalam mengamankan sertifikat tanah digital dan  dapat diimplementasikan sebagai algoritma sertifikat tanah digital yang berjalan secara real-time.
Strategic Evaluation of Whistleblower Software Security in Government: ISO/IEC 25010 and AHP Method Purbaratri, Winny; Sembiring, Irwan; Setiawan, Adi; Setyawan, Iwan
Jurnal Sistem Informasi Bisnis Vol 14, No 4 (2024): Volume 14 Nomor 4 Tahun 2024
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol14iss4pp321-328

Abstract

To assess the effectiveness of software security measures in government whistleblower systems, we will utilize the ISO/IEC 25010 standard and the Analytic Hierarchy Process (AHP) methodology. Through the integration of various frameworks, our objective is to build a complete evaluation model that effectively identifies and enhances any vulnerabilities in these crucial systems. The strategy we employ combines the qualitative and quantitative evaluation capabilities of ISO/IEC 25010 and AHP, respectively, to offer a comprehensive perspective on software security performance. The results indicate substantial improvements in the security and reliability of whistleblower software, underscoring the effectiveness of our suggested evaluation technique in identifying crucial areas for refinement. Moreover, the utilization of AHP permitted the ranking of security qualities, guaranteeing focused and efficient improvements. Ultimately, the study emphasizes the significance of thorough security assessments for government whistleblower systems and verifies the effectiveness of utilizing ISO/IEC 25010 and AHP as a methodical approach to improve software security. This research enhances the ongoing endeavor to protect confidential data, fostering a more secure and reliable atmosphere for individuals who expose wrongdoing.
Innovation and Key Benefits of Business Models in Blockchain Companies Aini, Qurotul; Manongga, Danny; Rahardja, Untung; Sembiring, Irwan; Efendy, Rifan
Blockchain Frontier Technology Vol. 2 No. 2 (2023): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/bfront.v2i2.161

Abstract

Existing business models are changed and disrupted by blockchain technology, which warrants more research. This study tries to describe the phenomena of blockchain technology in relation to business model innovation in the enterprise ecosystem on the basis of that. Blockchain technology has been shown to increase organizational performance empirically. The value system concept is used in this study to explain this phenomena. This study employs a multiple-case study to respond to research questions using abductive reasoning. Overall, the outcomes According to this study, blockchain technology benefits an organization in four different ways: I value capture through higher profitability; (ii) value creation through private partnerships; (iii) value delivery through smart contracts; and (iv) value proposition that drives value by raising the organization's business value through operational improvements. This report also suggests a blockchain ecosystem with various private and consortium organizations. Private ecosystem focused on internal organizational performance enhancement within one corporate enterprise. The consortium ecosystem, on the other hand, is focused on fostering corporate cooperation.
Co-Authors Abas Sunarya, Po Ade Iriani Adi Setiawan Adriyanto Juliastomo Gundo Agus Sugiarto Agustinus, Ari Alamsyah, Ferry Andriana, Myra April Lia Hananto Apriliasari, Dwi Ardaneswari, Awanda Arthur, Christian Astawa, I Wayan Aswin Dew Ayu Sanjaya, Yulia Putri Bayu Setyanto Pamungkas Budhi Kristianto Budi Santoso Budi, Reza Setya Cahyaningtyas, Christian Daniawan, Benny Danny Manongga Danny Sebastian Dedy Prasetya Kristiadi Dwi Hosanna Bangkalang Dwi Setiawan Edi Suharyadi Efendy, Rifan Eko Sediono Eko Sediyono Eleazer Gottlieb Julio Sumampouw Elmanda, Vonda Erick Alfons Lisangan Esti Zakia Darojat Evangs Mailoa Evi Maria Faturahman, Adam Fauzi Ahmad Muda Fian Yulio Santoso Florentina Tatrin Kurniati Gallen cakra adhi wibowo Gerry Santos Lasatira Ginting, Jusia Amanda Girinzio, Iqbal Desam Gudiato, Candra Hamdan . Hany Makaruku, Yulian Hasnudi . Henderi Henderi . Hendry Hendry, - Henuk, Yusuf Leonard Hindriyanto Dwi Purnomo Huda, Baenil Ignatius Agus Supriyono Ilham Hizbuloh Indrastanti Ratna Widiasari Iwan Setiawan Iwan Setiawan Iwan Setyawan Joko Listiawan Sukowati Joko Siswanto Joko Siswanto Jonas, Dendy Julians, Adhe Ronny Juneth Manuputty Krismiyati Kristoko D Hartomo Kristoko Dwi Hartomo Kusumajaya, Robby Andika Limbong, Josua Josen Alexander Madawara, Herdin Yohnes Manongga, Daniel H.F Manongga, Daniel H.F. Manongga, Daniel HF Marsyel Sampe Asang Marvelino, Matthew Mau, Stevanus Dwi Istiavan Maya Sari Merryana Lestari Migunani Migunani Mira Mira Mira Mohammad Ridwan Muhamad Yusup Nanle, Zeze Nazmun Nahar Khanom Nina Setiyawati Ninda Lutfiani Nining Fitriani Nugroho, Samuel Danny Nurtino, Tio Nuryadi, Didik Nurzainah Ginting Pamungkas, Bayu Setyanto Phillnov Yohanes Pinontoan Pinontoan, Phillnov Yohanes Priatna , Wowon Purbaratri, Winny Purnama Harahap, Eka Purnomo, Hidriyanto Dwi Putra, Yonathan Rahadi Qurotul Aini Qurotul Aini Rahardja.,M.T.I.,MM, Dr. Ir. Untung Raymond Elias Mauboy Rimes Jopmorestho Malioy Roy Rudolf Huizen Saian, Septovan Dwi Suputra Sandry Lanovela Pasaribu Santoso, Nuke Puji Lestari Sediyono, Eko - Setiawan Hakim Sri Ngudi Wahyuni Sri Ngudi Wahyuni, Sri Ngudi Sri Yulianto Joko Prasetyo Suharyadi Sulistio Sulistio Sumampouw, Eleazer Gottlieb Julio Supriadi, Candra Suryantara, I Gusti Ngurah Susanti, Novita Dewi Sutarto Wijono Suwijo Danu Prasetyo Teady Matius Surya Mulyana, Teady Matius Teguh Wahyono Theopillus J. H. Wellem Tintien Koerniawati Tirsa Ninia Lina Tomasoa, Lyonly Tri Wahyuningsih Tri Wahyuningsih Tukino, Tukino Untung Rahardja Untung Rahardja Wibowo, Mars Caroline Wijaya, Angga Zakharia Wiwien Hadikurniawati Yerik Afrianto Singgalen Yessica Nataliani Yohan Maurits Indey Yohnes Madawara, Herdin Yulian Hany Makaruku