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All Journal J@TI (TEKNIK INDUSTRI) Jurnal Ilmiah Teknologi dan Rekayasa Techno.Com: Jurnal Teknologi Informasi MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Forum Ilmu Sosial Jurnal Adabiya Edulib Lentera Pustaka Jurnal Kajian Informasi & Perpustakaan JIPI (Jurnal Ilmu Perpustakaan dan Informasi) Jurnal Tamaddun Populis : Jurnal Sosial dan Humaniora Publication Library and Information Science Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Informatika Jurnal Khatulistiwa Informatika HIGIENE: Jurnal Kesehatan Lingkungan JBMP (Jurnal Bisnis, Manajemen dan Perbankan) Jurnal Pilar Nusa Mandiri Jurnal Penelitian Pendidikan IPA (JPPIPA) JURNAL YAQZHAN: Analisis Filsafat, Agama dan Kemanusiaan Indonesian Journal of Artificial Intelligence and Data Mining JRST (Jurnal Riset Sains dan Teknologi) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Manajemen Kesehatan Yayasan RS.Dr. Soetomo Angkasa: Jurnal Ilmiah Bidang Teknologi Martabe : Jurnal Pengabdian Kepada Masyarakat International Journal of Community Service Learning JURNAL GOVERNANSI Cakrawala: Jurnal Litbang Kebijakan Tibanndaru : Jurnal Ilmu Perpustakaan dan Informasi Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat J-Dinamika: Jurnal Pengabdian Kepada Masyarakat Transparansi Jurnal Ilmiah Ilmu Administrasi Jurnal Kesehatan Medical Technology and Public Health Journal Applied Technology and Computing Science Journal Jurnal Ekonomi Manajemen Sistem Informasi Dinasti International Journal of Education Management and Social Science Journal of Economics, Business, and Government Challenges MUKADIMAH: Jurnal Pendidikan, Sejarah, dan Ilmu-ilmu Sosial Jurnal Informasi dan Teknologi Jatilima : Jurnal Multimedia Dan Teknologi Informasi Responsive: Jurnal Pemikiran dan Penelitian Administrasi, Sosial, Humaniora dan Kebijakan Publik Bubungan Tinggi: Jurnal Pengabdian Masyarakat J-3P (Jurnal Pembangunan Pemberdayaan Pemerintahan) Info Bibliotheca: Jurnal perpustakaan dan ilmu Informasi Teknosains : Jurnal Sains,Teknologi dan Informatika Journal of Computer Networks, Architecture and High Performance Computing Unilib: Jurnal Perpustakaan Jurnal Pemerintahan dan Kebijakan (JPK) BIOLOVA Journal of Technology and Informatics (JoTI) Az-Zahra: Journal of Gender and Family Studies Media Pustakawan Pustaka Karya : Jurnal Ilmiah Ilmu Perpustakaan dan Informasi Bidik : Jurnal Pengabdian kepada Masyarakat Journal of Law, Poliitic and Humanities Jurnal Ilmu Multidisplin Malcom: Indonesian Journal of Machine Learning and Computer Science MIMBAR INTEGRITAS Journal of Governance and Social Policy Eduvest - Journal of Universal Studies SATIN - Sains dan Teknologi Informasi Journal of Economics and Management Scienties Riwayat: Educational Journal of History and Humanities (Journal of Environmental Sustainability Management) Indonesian Governance Journal : Kajian Politik-Pemerintahan Jurnal Wacana Kinerja: Kajian Praktis-Akademis Kinerja dan Administrasi Pelayanan Publik Jurnal Informatika
Imam Yuadi
Departemen Ilmu Informasi Dan Perpustakaan, Fakultas Ilmu Sosial Dan Ilmu Politik, Universitas Airlangga
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Other

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ANALISIS TEXT CLUSTERING MASYARAKAT DI TWITTER TENTANG SEPAK BOLA INDONESIA MENGGUNAKAN ORANGE DATA MINING Baihaqie, Owen; Yuadi, Imam
Jurnal Khatulistiwa Informatika Vol 11, No 2 (2023): Periode Desember 2023
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jki.v11i2.16072

Abstract

Twitter saat ini menjadi sebuah platform media sosial yang sangat menarik untuk diamati. Topik yang sedang trend di Twitter seringkali memunculkan komentar dan opini dari masyarakat Indonesia. Salah satu topik yang menarik untuk dianalisis adalah sepak bola Indonesia yang saat ini banyak disoroti. Penelitian ini bertujuan untuk menganalisis tanggapan masyarakat terhadap topik tersebut melalui komentar di Twitter, menggunakan metode analisis Vader, tweet profiler, dan visualisasi distribution. Proses analisis dilakukan dengan menggunakan aplikasi Orange Data Mining, yang melibatkan tahapan preprocess text, seperti transformation, tokenization, normalization, dan filtering untuk memastikan teks bisa dianalisis. Hasil dari penelitian ini menunjukkan bahwa terdapat enam jenis respon dari masyarakat terhadap sepak bola Indonesia, dengan respon tertinggi adalah rasa terkejut dan takut.
Training Evaluation Analysis Using Text Mining Nainunis, Mas Akhmad; Yuadi, Imam
Indonesian Journal of Artificial Intelligence and Data Mining Vol 7, No 1 (2024): March 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v7i1.27607

Abstract

Training evaluation is an evaluation of the results of training that has been carried out. This evaluation includes technical and non-technical factors which are very important for the company to pay attention to when implementing training in the future. Many companies only implement training evaluations as a formality and only include evaluations that are limited by choice, such as closed questionnaires, training evaluations using open questionnaires can provide the freedom to provide positive or negative input that can be of concern to the company. This research aims to find out the words or topics that appear most frequently in open comments on training evaluation results by using the FP Growth algorithm and association rules to find out the relationship between topics or words from the training evaluation results. They are applied to 516 open-ended comments submitted via the post-training questionnaire. The research results showed that 15 association rules were created using Rapidminer using the FP-Growth algorithm with a minimum support of 0.02 and a minimum confidence of 0.5. All rules have a lift value>1 which indicates that all rules are valid or have a strong association relationship. This research can determine the pattern of comments or suggestions given by workers regarding training evaluation.
Analisis Bibliometrix Publikasi Ilmiah Terkait Prevention Cyberbullying Menggunakan Web Of Scince Pada Biblioshany Wettebossy, Anita Elizabeth; Yuadi, Imam
Angkasa: Jurnal Ilmiah Bidang Teknologi Vol 16, No 1 (2024): Mei
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/angkasa.v16i1.2058

Abstract

Pencegahan Cyberbullying melibatkan sejumlah tindakan yang mengurangi risiko dan dampak perilaku negatif secara daring. Inisiatif ini mencakup pemahaman  tentang etika digital serta edukasi  dari pihak yang berwenang. Dalam hal ini penulis terdorong menganalisis sejauh mana pertumbuhan dan perkembangan publikasi ilmiah terkait prevention cyberbullying menggunakan bibliometrix dengan kata kunci prevention cyberbullying. Tujuan dan manfaat penelitian ini  untuk menilai tingkat pertumbuhan  publikasi ilmiah terkait topik, hal ini diharapkan agar  mengurangi  fakta buruk mengenai  cyberbullying dan mampu  memberikan kontribusi  pada pemahaman  masyarakat  serta menyediakan landasan edukasi yang lebih baik dalam upaya pencegahan cyberbullying. Analisis data menggunakan web of science dengan kata kunci pencegahan cyberbullying memperoleh hasil  sebanyak 882 dokumen tidak dibatasi. Kemudian data diolah pada aplikasi R studio, bahasa R dan bibliometrik. Hasil yang diperoleh dari data utama mencakup periode dari tahun 2007 dan 2023. Tabel tersebut menunjukkan bahwa 882 dokumen berasal dari 425 sumber termasuk jurnal dan buku, telah ditulis oleh 2.313 penulis dengan topik prevention cyberbullying. Tingkat pertumbuhan tahunan 6.26 dengan rata-rata kutipan 26.86 per dokumen dan rata-rata usia dokumen  5.25 kutipan per tahun dengan referensi 0. Dapat disimpulkan bahwa perkembangan publikasi ilmiah terkait topik telah dilakukan sejak lama.
Research Mapping on Personal Data Protection Policy Unas, Frisca Maria; Yuadi, Imam
Journal of Governance and Social Policy Vol 4, No 2 (2023): DECEMBER 2023
Publisher : Department of Government Studies, Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/gaspol.v4i2.32478

Abstract

The need for Personal Data Protection must be supported by policies that are able to guarantee the security of personal information so that it is not misused by irresponsible persons. The development of research on personal data protection policy can be a good reference for the government and stakeholders in formulating policies that can guarantee the security of personal data. This study aims to determine research trends and explain the relationship between keywords and researchers in research articles on personal data protection policies. This study uses the bibliometric analysis method assisted by the VOS Viewer and Biblioshiny Rstudio tools so that it can display interesting network visualization. The findings from this study are the development of research publications on related topics from year to year, mapping of subject areas of research publications on related topics, mapping of countries of origin of research publications on related topics, relationships between authors/researchers, relationships between keywords from a number of research articles on related topics, distribution of journals that publish research articles on related topics, and productivity of researchers/writers of articles on related topics. The results of this study can help researchers find novelty opportunities and use appropriate reference sources in conducting research on related topics
Study Orange Data Mining Model Prediksi Status Gizi Balita Kelurahan X Sari, Tri Kartika; Imam Yuadi
SATIN - Sains dan Teknologi Informasi Vol 9 No 2 (2023): SATIN - Sains dan Teknologi Informasi
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33372/stn.v9i2.994

Abstract

Usia 0-59 bulan merupakan periode emas masa penting dimana semua proses perkembangan organ yang mempengaruhi kemampuan sensorik dan motorik seorang anak berlangsung. Pemantauan dan identifikasi status gizi balita secara dini diharapkan bisa melakukan control serta intervensi yang tepat dan cepat sehingga bisa menghilangkan atau meminimalisir dampak buruk yang ditimbulkan. Tujuan penelitian ini untuk melakukan identifikasi status gizi balita melalui pembuatan model prediksi menggunakan aplikasi orange data mining dan memberikan rekomendasi metode algoritma mana diantara KNN, Decision Tree, Naive Bayesdan Regresi logistic yang paling akurat.ROC Analisys (ROCA),Cross Validation dan Confusion Matrixsebagai model evaluasi. Empat model tersebutkemudian dibandingkan dan disimpulkan bahwa model algoritma KNN yang lebih direkomendasikan untuk prediksi status gizi karena memiliki tingkat akurasi dan presisi lebih baik dibanding 3 metode lainnya dengan nilai akurasi 95,24%, presisi 77,51%.
PEMETAAN BIBLIOMETRIK: PENGGUNAAN TEKNOLOGI ARTIFICIAL INTELLIGENCE (AI) PADA RENTANG WAKTU 2011-2023 DALAM DUNIA PENDIDIKAN Raihanzaki, Raka Gading; Yuadi, Imam
Info Bibliotheca: Jurnal Perpustakaan dan Ilmu Informasi Vol. 5 No. 2 (2024): Info Bibliotheca: Jurnal Perpustakaan dan Ilmu Informasi
Publisher : Program Studi Perpustakaan dan Ilmu Informasi, Fakultas Bahasa dan Seni, Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ib.v5i2.461

Abstract

Artificial Intelligence technology is artificial intelligence which is then associated with the ability of machines or computers to do things that humans do. Artificial Intelligence originally started in 1942 when the American science fiction writer Isaac Asimov then included AI in his book entitled Runaround which then told about robots. Then, in 1956 MarvinMinsky and John McCarthy began conducting research on artificial intelligence. Artificial Intelligence technology has become increasingly popular among the wider community, in all circles, including in the world of education. One of the products from AI which is quite popular at the moment is GPT chat which is often used in the world of education. This is because Artificial Intelligence technology makes it very easy to do work or assignments. This article will then examine using bibliometric analysis the trends in the use of Artificial Intelligence technology in the world of education. This article analyzes using the bibliometric analysis method using a database from Scopus with a research range from 2011 to 2023, with the keywords artificial intelligence, impact, and education, which then produces 1565 articles. These articles were analyzed using bibliometric methods with biblioshiny. The aim of this article is to analyze trends in the use of artificial intelligence technology in the world of education based on bibliometric analysis by observing the number of publications on this topic from year to year. It was found that from year to year research on the use of artificial intelligence in the world of education, the graph continues to increase and shows a percentage of 43.71% for the development of publications from year to year. This article is divided into several parts (1) introduction which explains each research component starting from scopus bibliometrics and biblioshiny as well as the topics studied; (2) research methods carried out using bibliometric analysis; (3) results and discussion of the bibliometric analysis; and (4) conclusions.
DIGITAL LIBRARIES IN EDUCATION: A BIBLIOMETRIC ANALYSIS ON THE WEB OF SCIENCE Suhada, Hofur; Yuadi, Imam
Publication Library and Information Science Vol 8 No 1 (2024)
Publisher : Perpustakaan Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/pls.v8i1.8801

Abstract

This study aims to identify trends and developments in scientific publications related to digital libraries in education. The VOSViewer bibliometric analysis and visualization method was applied using the Web of Science (WOS) database from 2013 to early 2024. The study reveals significant developments in research over the past few years. It details research productivity and identifies the keywords 'higher education' and 'systematic review' as frequently associated with the main keywords. United states of america is identified as the most influential country in publications, with author Khan A and the journal Humanidades & Inovacao as the most  contributors. The study's conclusion confirms that scientific publications on digital libraries in education are experiencing positive growth, in line with the development of information and communication technology (ICT).
ANALYSIS OF LIBRARY VISITOR GROUPING THROUGH MASK USAGE IDENTIFICATION IN XIN ZHONG LIBRARY WITH ORANGE DATA MINING APPLICATION Putra, Dwi Permana; Yuadi, Imam
Publication Library and Information Science Vol 9 No 1 (2025)
Publisher : Perpustakaan Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/pls.v9i1.11508

Abstract

AbstractThe application of data mining in libraries plays a crucial role in supporting data management and monitoring health protocols, especially during the pandemic. A key challenge faced by librarians is effectively monitoring visitors' mask usage compliance. This study aims to analyze visitors' facial images at the library using the Orange Data Mining application, enabling librarians to identify whether visitors are wearing masks. The approach involves collecting random facial images of visitors, preprocessing the data for standardization of size and resolution, extracting features using the Inception V3 model, and conducting hierarchical clustering analysis with the Manhattan metric. The clustering results are visualized in a dendrogram, helping to group the data. The findings show that the dendrogram clearly differentiates between visitors with masks and those without. This visualization provides librarians with an effective tool for monitoring areas of the library that require more strict health protocol supervision. The study concludes that the Orange Data Mining application offers a practical solution for libraries to monitor compliance with health protocols. By utilizing data mining techniques, libraries can enhance visitor safety and comfort. Further research is suggested to expand the dataset and explore other methods to improve analysis accuracy.
Bahasa Inggris Zidny, Irvan; Puspitasari, Ira; Yuadi, Imam
Jurnal Penelitian Pendidikan IPA Vol 9 No 8 (2023): August
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v9i8.4531

Abstract

This study presents a novel approach to assist learning analysts in identifying suitable learning pathways based on historical training data through the utilization of text mining techniques. The dataset utilized in this research comprises training data from the year 2021 and the Course Development Management Program (CDMP) catalogue. The BERT 'bert-base-nli-mean-tokens' model is employed for encoding purposes. By comparing the training data names from 2021 with the CDMP catalogue using cosine similarity and dot score, valuable insights are obtained. The findings indicate that cosine similarity is a more effective measure for interpreting the data, thereby simplifying the process for learning analysts and managers in identifying appropriate learning paths for their employees. This research provides a practical solution that leverages text mining techniques to optimize the analysis and decision-making processes in learning and development domains, enabling organizations to enhance the effectiveness and efficiency of their training programs.
Digital Forensic Approaches for Counterfeit Money Detection: A Compratie of KNN, Logistic Regression, and SVM Classifiers Sabrina Nur Amalia; Imam Yuadi
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 03 (2025): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i03.1764

Abstract

Counterfeit currency presents a substantial risk to economic stability and financial security, necessitating efficient and dependable detection techniques in both forensic and practical contexts. This research examines digital forensic methodologies for the identification of counterfeit banknotes employing three machine learning classifiers: K-Nearest Neighbors (KNN), Logistic Regression, and Support Vector Machine (SVM). A dataset was generated by photographing authentic and counterfeit Indonesian banknotes using a mobile phone camera, thereafter undergoing preprocessing and augmentation to enhance resilience. To improve classification performance, three image preprocessing techniques—grayscale filtering, edge detection, and blurring—were employed. The models were assessed based on accuracy, precision, recall, and F1-score obtained from confusion matrix analysis. The experimental findings demonstrated that SVM and Logistic Regression consistently surpassed KNN in all settings, with SVM attaining the best overall accuracy of 0.997 under gray and blur filtering. Logistic Regression exhibited high reliability, with an accuracy of 0.994–0.997 using gray and blur filters. KNN, although originally less successful, showed significant enhancement when integrated with blur filtering, attaining an accuracy of 0.973. Conversely, edge detection was found to be detrimental to the performance of all tested models.
Co-Authors AA Sudharmawan, AA Achmad Djunawan Albigaeri, Syahruly Nizar Alifka Cellina Velby Anastasya, Diva Berta Andini, Aulia Rizqi Anggraini, Pramudya Galuh Suci Artha Rachma Widiastuti Azmi, Muhammad Izharul Baihaqie, Owen Berliani, Kezia Putri Budiyan Mariyadi Cahyani, Retno Tri Christia, Tifani Dewi Condro Rahino Mustikaning Pawestri Dama Putri, Kania Dewanty, Alifia Kaltsum Dwisusilo, Aditya Endang Gunarti Enny Mar’atus Sholihah Erika Putri Fadilia Rinarwastu, Fadilia Febriano, Rizki Dwi Ferdiansah, Gilang Fitri Mutia, Fitri Fitria Wulandari, Martina Gunarti, Endang Halim, Yunus Abdul Handari Niken Anggraini Hapsari, Ratih Addina Hardevianty, Melissa Yunda Hasna, Dhia Alifia Izdihar Hendrawati, Lucy Dyah Inggrid Nindia Aprila Palupi Ira Puspitasari Ira Puspitasari Ismi Choirunnisa Prihatini Kartika Sari, Della Kezia Rahmawati Santosa Koko Srimulyo Lathifah, Lathifah Lestari, Santi Dwi Desy Lifindra, Stevanie Aurelia M Kafi Maulana M. Fariz Fadillah Mardianto Mahardika, Synthia Amelia Putri Margono, Hendro Mariyadi, Budiyan Marsaa Salsabiila Maulidah, Nofiyah Mayasari, Sentri Indah Melati Purba Bestari, Melati Purba Mochammad Edris Effendi Muhammad Rafi Raihan Nabilla Salsabil Damayanti Zahraa Nainunis, Mas Akhmad Nazikhah, Nisak Ummi Niken Ayu Pratiwi, Bertha Novia, Asradiani Nur Muhammad, Rizqi Nurahman, Yeni Fitria Nurul Firdausy Palupi, Inggrid Nindia Aprila Pradhana, Andrea Thrisiawan Prasetyo Yuwinanto, Helmy Prasyesti Kurniasari, Meinia Prayitna, Thomas Wigung Aji Purba, Trie Dinda Maharani Putra, Dwi Permana Putra, Nawwaf Faruq Adina Putri Kinanti, Novrianti Putri, Selviana Azzira Ragil Tri Atmi, Ragil Tri Rahmadani, Sinta Raihanzaki, Raka Gading Ratih Addina Hapsari Rosiana, Lidya Rosyani, Widha Sabayu, Brian Sabrina Hartianingrum, Hikmah Sabrina Nur Amalia Safina Innaf Mia Ardelia Salsabila, Chyntia Shafa Santoso, Yuniawan Heru Sari, Tri Kartika Setiadi, Yusuf Sheva Alana Brilianty Sinta Rahmadani Soesantari, Tri Sufryanto, Sukma Sugihartati, Rahma Suhada, Hofur Taufik Roni Sahroni Tikamidia, Sonia Tri Hadi Wicaksono Triandari, Ayu Ullin Nihaya Unas, Frisca Maria Vilosa, Bias Vivia Adriyanti, Elvetta Wardani, Hesti Ari Wettebossy, Anita Elizabeth Wildan Habibi Yuwinanto, Helmy Prasetyo Zidny, Irvan