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All Journal Humanika : Kajian Ilmiah Mata Kuliah Umum JIPI (Jurnal Ilmu Perpustakaan dan Informasi) Masyarakat, Kebudayaan dan Politik Journal of Economic, Bussines and Accounting (COSTING) Martabe : Jurnal Pengabdian Kepada Masyarakat Fair Value: Jurnal Ilmiah Akuntansi dan Keuangan JURNAL GOVERNANSI Khazanah: Jurnal Pengembangan Kearsipan Journal of Urban Sociology Building of Informatics, Technology and Science BALANCE: Economic, Business, Management and Accounting Journal JENIUS (Jurnal Ilmiah Manajemen Sumber Daya Manusia) MUKADIMAH: Jurnal Pendidikan, Sejarah, dan Ilmu-ilmu Sosial Bubungan Tinggi: Jurnal Pengabdian Masyarakat Journal of Soft Computing Exploration ABDI PUSTAKA: Jurnal Perpustakaan dan Kearsipan Literatify : Trends in Library Development Bidik : Jurnal Pengabdian kepada Masyarakat Malcom: Indonesian Journal of Machine Learning and Computer Science Pustakaloka: Jurnal Kajian Informasi dan Perpustakaan MILRev: Metro Islamic Law Review Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) The Indonesian Journal of Computer Science Madania: Jurnal Kajian Keislaman
Hendro Margono
Universitas Airlangga
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Social Sciences Other

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Prediksi Sentimen Investor Pasar Modal Di Jejaring Sosial Menggunakan Text Mining Aestikani Mahani; Hendro Margono
BALANCE: Economic, Business, Management and Accounting Journal Vol 18, No 2 (2021): Juli
Publisher : UMSurabaya Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/blc.v18i2.7226

Abstract

The decline in optimism for capital market investors is one of the financial impacts on the business world that arose from the SARS-COVID19 pandemic. This event was reflected in a decrease in trading volume followed by a sharp drop in the JCI on the Indonesia Stock Exchange starting March 2020. Thus, a slowdown in the economic recovery resulting from the pandemic is reflected in investor sentiment in the capital market. On the one hand, the rapid development of the internet in Indonesia has triggered the investor's activities in the information searching prior buy and sell securities, mostly use online platforms, which contribute to influencing investor preferences and sentiment. This study conducted a qualitative examination of the features/terms of stock investment in the capital market and collected them in a compact dictionary (lexicon). Therefore, lexicon-based investor opinion extraction was extracted from Twitter, followed by the text sentiment analysis, and forming a classification model based on Naive Bayes and Decision Tree. This research output shows that the polarity of capital market investor sentiment is optimistic with the sentiment features that often appear, namely "cuan", "bearish," "serok", "copet", "untung", "cut loss", and "nyangkut." Meanwhile, the Decision Tree classification model provides better performance.Keywords                        :  investor, lexicon, social network, stock exchange, text miningCorrespondence to        : aestikani.mahani-2019@feb.unair.ac.id Penurunan optimisme investor pasar modal adalah salah satu dampak keuangan pada dunia usaha yang timbul akibat pandemi SARS-COVID19. Hal ini tercermin dari turunnya volume perdagangan yang diikuti penurunan tajam IHSG di Bursa Efek Indonesia mulai Maret 2020. Sehingga kekhawatiran atas perlambatan pemulihan ekonomi sebagai dampak pandemi, tercermin dari sentimen investor di pasar modal. Di satu sisi, perkembangan internet di Indonesia yang pesat, memicu kecenderungan aktivitas investor dalam pencarian informasi sebelum membeli dan menjual surat berharga  secara online, turut berkontribusi dalam mempengaruhi preferensi dan sentimen investor. Penelitian ini menggali ekspektasi investor yang tercermin pada sentimen investasi, dimana pasar modal sebagai salah satu barometer penting perekonomian suatu negara. Kajian ini mengeksplorasi fitur/terms investasi saham yang kerap muncul di pasar modal dan mengumpulkannya dalam kamus leksikon. Kemudian, dilakukan ekstraksi opini investor berbasis leksikon yang digali dari jejaring sosial Twitter, dilanjutkan dengan tahap text mining yaitu menganalisis sentimen, dan membentuk model klasifikasi berbasis Naive Bayes dan Decision Tree. Keluaran penelitian ini  menunjukkan bahwa polaritas sentimen investor pasar modal adalah positif dengan fitur sentimen yang sering muncul yaitu “cuan”, “bearish”, “serok”, “copet”, “untung”, dan “cut loss”. Sedangkan model klasifikasi Decision Tree memberikan performansi akurasi yang kebih baik.Kata Kunci                  : Analisis sentimen; Investor; Leksikon; Text mining; Twitter
The Urgency of Disability Services in the Library with Literature Review Rifa, Syafira Dila; Rosyani, Widha; Margono, Hendro
Pustakaloka Vol. 16 No. 1 (2024)
Publisher : IAIN Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21154/pustakaloka.v16i1.8524

Abstract

Penyandang disabilitas mengalami keterbatasan yang membuat akses ke berbagai layanan, termasuk di perpustakaan, menjadi sulit. Untuk itu, diperlukan layanan khusus di perpustakaan agar mereka dapat mengakses informasi dengan lebih mudah. Peraturan Pemerintah Nomor 23 Tahun 2014 mengatur pelaksanaan Undang-Undang Nomor 43 Tahun 2007 tentang perpustakaan, yang menekankan pentingnya layanan non-diskriminatif bagi penyandang disabilitas. Penelitian ini bertujuan mengatasi kurangnya artikel jurnal mengenai layanan disabilitas di perpustakaan dengan menggunakan metode literature review, yang melibatkan pencarian jurnal terkait di Google Scholar. Data dari jurnal-jurnal tersebut menunjukkan bahwa beberapa perpustakaan masih memiliki layanan disabilitas yang kurang memadai, sementara yang lain sudah mulai memperhatikan pentingnya keamanan dan kenyamanan bagi penyandang disabilitas. Artikel ini membahas pengenalan kebutuhan pengguna disabilitas, pelatihan petugas perpustakaan, aksesibilitas fasilitas, dan inovasi digital untuk aksesibilitas universal di era digital bagi penyandang disabilitas.
The Role of Teacher-Librarian in Building Lifelong Learning for Students Hendro Margono; Nadya Ananda Tri Anugrah Putri
Literatify: Trends in Library Developments Conference Papers of the Hybrid International Conference on Library and Information Science (HICoLIS
Publisher : UPT Perpustakaan UIN Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/literatify.vi.42724

Abstract

Teacher Librarian is usually a teacher who also acts or is responsible as a librarian in the school library. Teachers who have a minimum education in the field of library science Diploma two (D-II) at an accredited university or complete a minimum Diploma two (D-II) education which is then continued with training and learning in the library field. However, in Indonesia there is often a phenomenon of teacher-librarians who do not have scientific provision in the library field so that in some cases in real life, the management of the library system becomes less than optimal and cannot be utilized by users properly. In contrast to other countries, it is known that many schools in Europe use teacher-librarians as school library staff. This is so that teacher-librarians can collaborate with teachers to improve the quality of learning as well as the literacy skills of their students. School libraries should also have interesting and effective programs because this can affect students' learning achievement. Lifelong Learning is learning that is carried out throughout life without coercion on one's part to improve their abilities and knowledge so that they can create good competitiveness for their environment. Students who act as lifelong learners need proper guidance, namely with the help of Teacher-Librarians and also teaching teachers during the learning process. This article uses a literature review method that critically reviews ideas or findings in academically oriented literature.
Kebutuhan transformasi bank digital Indonesia di era revolusi industri 4.0 Suharbi, Muhammad Akbar; Margono, Hendro
Fair Value: Jurnal Ilmiah Akuntansi dan Keuangan Vol. 4 No. 10 (2022): Fair Value: Jurnal Ilmiah Akuntansi dan Keuangan
Publisher : Departement Of Accounting, Indonesian Cooperative Institute, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (734.756 KB) | DOI: 10.32670/fairvalue.v4i10.1758

Abstract

The occurrence of the Covid-19 pandemic forced humans to adapt to technology, not least in terms of finance, namely transactions in banking. This study aims to analyze the transformation of the banking industry into a digital bank in providing services to customers. This research is a type of qualitative research using secondary data from reliable literacy. The results of this study indicate that the transformation into a digital bank provides many advantages for banks to be able to continue to survive in running their business. Where digital banks are the choice of customers in transacting in the financial sector because it is easy, fast, and efficient. Transforming into a digital bank can also increase more customers and fee base income for banks because they can collaborate with fintech and e-commerce and can be efficient in managing bank assets which in turn can increase bank profits exponentially. However, in transforming into a digital bank, banks must have a strong foundation, especially in terms of infrastructure and security of customer data that is vulnerable to hacking attacks (cyber crime). So that in the Industrial Revolution 4.0 era technology is the main key in winning the competition and remaining sustainable in running a business, for that the banking sector in Indonesia is required to continue to innovate in providing the best service to its customers.
Technology innovation in library: a bibliometric review Margono, Hendro; Rasyid, Rizka Adristi; Setiyarini, Melina Dewi
Humanika: Kajian Ilmiah Mata Kuliah Umum Vol. 24 No. 2 (2024): Humanika: Kajian Ilmiah Mata Kuliah Umum
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/hum.v24i2.70660

Abstract

Technological innovation is changing libraries and how libraries operate. This study presents a bibliometric analysis to identify key patterns and trends in research on technological innovation in libraries, based on the publication of papers indexed in Web of Science from 2019 to 2023. A total of 433 documents from 342 sources were analyzed using Biblioshiny and VOSViewer software. The results show an increasing interest in this research domain, despite a negative annual publication growth rate of -32.33% in recent years. The IEEE Winter Conference on Computer Vision Applications and the IEEE Symposium on Security and Privacy were the most productive sources. "Library" was the most frequent keyword found in 6% of documents, along with terms such as "model", "performance", and "system", highlighting the focus on developing and evaluating technological systems for libraries.  The findings summarize the key topics, trends, and leading countries driving technology innovation research for libraries over the past five years. This bibliometric review provides insights to guide future research efforts in this area.
AUTHENTIC LEADERSHIP AND KNOWLEDGE SHARING IN INDONESIA'S DATA SCIENCE COMMUNITIES: THE MEDIATING ROLE OF ORGANIZATIONAL COMMITMENT Aldo Lovely Arief Suyoso; Muchammad Toyib; Hendro Margono
Journal of Economic, Bussines and Accounting (COSTING) Vol 7 No 5 (2024): Journal of Economic, Bussines and Accounting (COSTING)
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/costing.v7i5.12097

Abstract

This study aims to investigate the relationships between authentic leadership, organizational commitment, trust, and knowledge sharing behavior in the context of the workplace. Data were collected from members of the astronomy community in Indonesia involved in the development of community-based astronomy tourism. Multiple linear regression analysis was used to test the relationships between these variables. The results show that authentic leadership has a significant positive relationship with organizational commitment and knowledge sharing behavior, both tacit and explicit. Organizational commitment also mediates the relationship between authentic leadership and knowledge sharing behavior. However, trust does not strengthen the relationship between organizational commitment and knowledge sharing behavior. Managerial implications include the importance of developing authentic leadership and fostering organizational cultures that support employee commitment. Academic implications include supporting theories of authentic leadership and enriching understanding of the mechanisms of mediation and moderation in the relationships among variables. This study provides a significant contribution to understanding the dynamics of workplace relationships and highlights the importance of psychological factors in the development of sustainable organizations.
Application of Machine Learning for Dementia Classification through MRI Images using Vertex AI on Google Cloud Services Rinanda, Tiara Disti; Arief Suyoso, Aldo Lovely; Margono, Hendro
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6040

Abstract

Alzheimer's dementia remains a serious global health challenge, particularly in resource-limited countries where early and accurate diagnosis is crucial to reducing morbidity and mortality rates. Despite advances in medical imaging and diagnostic tools, early detection of Alzheimer’s remains a complex and resource-intensive task for healthcare systems worldwide. This study leverages the power of machine learning, specifically Convolutional Neural Networks (CNN), to develop a reliable model for detecting the severity of dementia using brain MRI images. The dataset used consists of four main categories: Non-Demented, Very Mild Demented, Mild Demented, and Moderate Demented, with a total of 1,561 images obtained from Kaggle. The model was trained using Vertex AI on Google Cloud, which automatically optimized model parameters through AutoML and Hyperparameter Tuning. Techniques such as image segmentation and feature extraction were applied to enhance model accuracy. The results show that this CNN model achieved a precision rate of 93.5% for the Non-Demented category, with classification accuracy consistently between 92% and 93% for various other levels of dementia severity. These findings underscore the potential of machine learning, particularly CNN, in significantly improving dementia detection accuracy even in resource-constrained settings. By utilizing advanced techniques such as image segmentation, feature extraction, and CNN-based automated classification, this model offers a promising solution for real-time dementia diagnosis. The scalability and adaptability of the model built using Vertex AI allow for broader applications in global clinical scenarios, supporting public health efforts to reduce the burden of Alzheimer's disease. While challenges regarding data sensitivity and computational resources are acknowledged, the model’s potential to improve early diagnosis and patient outcomes is highly significant.
Narrative literature review: Efficiency enhancement - user trust in chatbots as a tool for improving service quality by humans Margono, Hendro; Bastian, Devi; Faiza, Nova Auliatul
Journal of Soft Computing Exploration Vol. 5 No. 2 (2024): June 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i2.286

Abstract

Chatbots have become efficient and reliable tools for instant and real-time information dissemination. Despite their effectiveness, user trust in chatbot systems remains relatively low. A holistic approach is necessary, integrating user emotional experiences, trust-building strategies, and continuous technological refinement to maximize chatbot benefits across various sectors. This research explores the potential for selective information dissemination based on user preferences using chatbots combined with artificial intelligence. Through a narrative approach, the study reviews literature and analyzes eight articles related to chatbots' application in information dissemination. The results indicate that chatbots are efficient in providing information and can be customized for various needs, such as population services, reminder notifications, and book processing. Chatbots have the potential to enhance services and can be integrated into information systems to improve service quality. However, challenges such as reliance on high-quality data and machine learning, difficulties in understanding non-formal language or slang, and limitations in handling complex questions need to be addressed for chatbots to reach their full potential.
Strategi Peningkatan Literasi Masyarakat Melalui Program Taman Bacaan Masyarakat (TBM) 4.0 Yuwinanto, Helmy Prasetyo; Soesantari, Tri; Atmi, Ragil Tri; Sugihartati, Rahma; Srimulyo, Koko; Gunarti, Endang; Yuadi, Imam; Mutia, Fitri; Margono, Hendro; Prasyesti Kurniasari, Meinia; Abdul Halim, Yunus
BIDIK: Jurnal Pengabdian kepada Masyarakat Vol. 5 No. 1 (2024): BIDIK: Jurnal Pengabdian kepada Masyarakat
Publisher : Fakultas Ilmu Budaya Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/bidik.v5i1.25251

Abstract

Dalam rangka mengarahkan agar masyarakat senantiasa memanfaatkan Taman Bacaan Masyarakat (TBM) untuk kegiatan yang produktif dan sekaligus mendukung peningkatan kemampuan literasi mereka. Tujuan dilakukan pendirian taman bacaan untuk memberikan bekal pengetahuan kepada pengelola TBM dan masyarakat tentang pemanfaatan yang positif dan produktif dari perkembangan TBM. Dengan cara memberikan pelatihan dengan peningkatan kemampuan pengelola yang baik dan professional maka akan diharapkan mampu memberikan hasil yang bermanfaat pada peningkatan pengetahuan pengelola dalam mengembangkan yang lebih baik dari sebelumnya. Untuk selanjutnya, dalam memberikan informasi mengenai program literasi dan mengadakan program-program tersebut disarankan TBM tersebut memiliki kegiatan yang terprogram dengan baik untuk penggunanya.
Research trends in gambling tax dynamics: A bibliometric analysis Khithobi, Arya Teges; Margono, Hendro; Hariani, Nurul Jamila; Soegiono, Agie Nugroho
Masyarakat, Kebudayaan dan Politik Vol. 37 No. 3 (2024): Masyarakat, Kebudayaan dan Politik
Publisher : Faculty of Social and Political Science, Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/mkp.V37I32024.270-287

Abstract

Gambling has been around for a long time and continues to evolve as it becomes integrated with video games. In its development, gambling continues to have negative impacts both economically and socially, such as unemployment, tax losses, divorce, and suicide. However, gambling can also have a positive impact, such as an increase in government revenue if taxed appropriately. This study aims to offer a thorough analysis of many publications from the last decade and monitor the progress of scientific research on gambling taxes as found in the Scopus database, utilizing VOSviewer and WordStat. In this study, the method used was bibliometric analysis. Between 2014 and 2023, a total of 132 scientific articles were dedicated to studying gambling taxes. There are a total of seven groups consisting of 111 keywords that are directly connected to gambling taxes. There are three groups of eight authors who are collaborating on a research project about gambling taxes. The study found that the University of Macau has affiliations with the majority of publications that impose gambling taxes. The United States has the biggest number of publications on the topic of gambling taxes. Studies on gambling taxes frequently confront issues of tax evasion and focus on a significant topic, namely the impact on public health and individuals. The study concluded that publications related to gambling taxes are dominated by articles from various multidisciplinary fields. This study recommends a wider range of publications and research from a more varied range of time and sources.
Co-Authors Adriansyah, Muhammad Ali Aestikani Mahani Aldo Lovely Arief Suyoso Aldo Lovely Arief Suyoso Aliffatin, Ety Subekti Anastasya, Diva Berta Anggraini, Handari Niken Arief Suyoso, Aldo Lovely Arum Karisma Nadya Lakshita Bastian, Devi Br Sihaloho, Dwi Paskah Marito Cahyani, Retno Tri Caspari, Andrean Dama Putri, Kania Dian Dwi Nur Rahmah Dwi Permana Putra Faiza, Nova Auliatul Fauziah, Salsa Fenny Nur Aprillia Fitri Mutia, Fitri Gunarti, Endang Halim, Yunus Abdul Hary Supriyatno Imam Yuadi Inriani, Sefania Wenny Eka Julian, Antoni Khithobi, Arya Teges Koko Srimulyo Lestari, Nur Laili Indah Fuji Lestari, Santi Dwi Desy Maulidah, Nofiyah Meilinda Putri, Ulfa Muchammad Toyib Muhammad Mustajib Muhammad Rafi Solakhudin Nadya Ananda Tri Anugrah Putri Nawwaf Faruq Adina Putra Niken Ayu Pratiwi, Bertha Nurul Jamila Hariani Prasetyo Yuwinanto, Helmy Prasyesti Kurniasari, Meinia Putra, Yudistira Ardi Nugraha Setyawan Ragil Tri Atmi, Ragil Tri Rahma, Nadhifia Shabrina Nur Rasyid, Rizka Adristi Rifa, Syafira Dila Rinanda, Tiara Disti Ronal Kamim Rosyani, Widha Seger Handoyo Setiadi, Yusuf Setiyarini, Melina Dewi Sheikh Adnan Ahmed Usmani Soegiono, Agie Nugroho Soesantari, Tri Solly Aryza Sugihartati, Rahma Suharbi, Muhammad Akbar Syaidatul Fiza Ma'arif Tondang, Edoardo Vivia Adriyanti, Elvetta Windrasari, Shella Norma Yuwinanto, Helmy Prasetyo