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Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi)
Published by Ikatan Ahli Informatika Indonesia
ISSN : -     EISSN : 25973584     DOI : -
Core Subject : Science,
Computer Science & IT
Seminar Nasional Sistem Informasi dan Teknologi (SISFOTEK) merupakan ajang pertemuan ilmiah, sarana diskusi dan publikasi hasil penelitian maupun penerapan teknologi terkini dari para praktisi, peneliti, akademisi dan umum di bidang sistem informasi dan teknologi dalam artian luas.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 471 Documents
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Peningkatan Visibilitas Produk pada Rekomendasi Long-Tail dengan Pendekatan Frequent Maximal Itemset Rosyid Muarif; Tubagus Mohammad Akhriza; Eni Farida
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Long-tail products are often overlooked in Collaborative Filtering recommendation systems due to their low purchase frequency and reliance on user interaction history. This study proposes the use of a Frequent Maximal Itemset (FMI) to improve the visibility of long-tail products in an online electronic cigarette (vape) store. Unlike Collaborative Filtering, FMI does not require user data and identifies historical transaction patterns to recommend relevant long-tail products alongside popular ones. Experimental results show that FMI is effective in identifying maximal itemsets that combine popular and long-tail products. Validation with 10 users revealed that 90% found the recommendations relevant to the main products they were searching for, and 90% indicated that they were likely to try the recommended long-tail products. The long-tail products included in the recommendations had logical associations with popular products, such as nicotine liquids with vaping devices. Thus, the FMI approach proves to be more flexible and effective in addressing popularity bias, while also providing long-tail products with greater visibility and increasing their potential for sales.
Prototipe Kelas Pintar Berbasis Android Menggunakan Metode Rapid Application Development Di Universitas Bina Insani Tiar Permana; Rully Pramudita
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The concept of smart classrooms has become a solution to improve the efficiency of the teaching and learning process. However, there are still challenges related to classroom preparation and management, such as forgetting to turn off devices after use or leaving the room without locking the door. The aim of this research is to develop the BiU-Class application to remotely control devices in the classroom. The development method used is Rapid Application Development (RAD) to accelerate the development process. Testing results between the application and the devices show that the system works well, demonstrating that the Smart Classroom concept has the potential to address problems in education. However, its implementation is currently hindered by electrical issues that require further research. The developed application is considered easy to understand by users, thus having the potential for future development and use once technical issues are resolved.
Analisis Kelayakan Peminjaman Uang untuk Pembelian Properti Dipengaruhi oleh Status Perkawinan dan Jumlah Tanggungan Menggunakan Algoritma Naïve Bayes Sri Erina Damayanti; Firli Setiani; Putri Ayu Ningtias; Reihan Aulia Darojat
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

This study aims to analyse the feasibility of loan approval for property purchases influenced by marital status and the number of dependents using the Naïve Bayes algorithm. Data were collected from a bank and analyzed using Orange Data Mining software. The results show that the Naïve Bayes algorithm is effective in predicting loan feasibility with an accuracy rate of 80.4%. Other evaluation metrics such as F1 score, precision, and recall also demonstrate good performance, with values of 78.2%, 81.4%, and 80.4% respectively. Although there are some weaknesses in predicting both positive and negative classes with equal accuracy, overall, the Naïve Bayes method remains reliable for this purpose. The implementation of this algorithm using the Orange Data Mining toolkit facilitates the data analysis and visualisation process, providing a clear understanding of the factors influencing loan feasibility for borrowers.
Analisis Bibliometrik: Pemetaan Penelitian Machine Learning dalam E-commerce Berdasarkan Data dari Scopus (2019-2024) Yudhistira Arie Wijaya; Dadang Sudrajat
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

This study explores the application of machine learning in e-commerce using descriptive and visual bibliometric analysis methods. Data were collected from the Scopus database for the period 2019–2024 through five stages: defining search keywords, initial search results, refinement of the search results, compiling statistics on the initial data, and data analysis. The findings indicate a significant increase in publications from 2020 to 2023, peaking in 2023, followed by a decline in 2024. IEEE Access and the International Journal of Advanced Computer Science and Applications are the main sources of publications, with India and China standing out as the countries with the highest number of publications. International research collaboration shows significant growth, and co-word analysis identifies “machine learning” as a central topic closely linked with “electronic commerce” and “learning systems." Citation trends reveal that highly cited publications have a significant impact. These findings provide comprehensive insights into the development and contributions of research in machine learning for e-commerce, with important implications for researchers and industry practitioners in addressing new challenges and opportunities.
Studi Bibliometrik Implementasi Teknik Machine learning dalam Bidang Customer Relationship Management Khaerul Anam
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Application of machine learning techniques in Customer Relationship Management has proven to have significant potential in enhancing the efficiency and effectiveness of managing customer interactions. This study aims to conduct a comprehensive bibliometric analysis regarding the application of machine learning techniques in CRM. Through this analysis, we seek to identify recent research trends, gaps, and future research opportunities. This study utilizes data from various prestigious international scientific journals indexed by Scopus to explore the application of machine learning techniques for churn prediction models. The method employed in this research is bibliometric analysis on machine learning techniques in the field of CRM. This study reveals a significant trend in the application of machine learning techniques in Customer Relationship Management. The results indicate that the use of machine learning in CRM has increased, particularly since 2021, reflecting a high interest and the relevance of this technology in enhancing the efficiency and effectiveness of CRM. The analysis also shows that the discipline of computer science dominates this research, followed by engineering, business and management, and mathematics. The contribution of this research to existing knowledge is providing a deeper understanding of current research trends and identifying gaps and future research opportunities.
Bibliometric Analysis Impact of Machine Learning on Mental Health in Student Learning Fadhil Muhammad Basysyar; Dadang Sudrajat; Gifthera Dwilestari
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The integration of machine learning in educational settings offers promising avenues for addressing mental health challenges among students [1]. This study conducts a bibliometric analysis to explore the impact of machine learning on mental health within student learning environments. By systematically reviewing peer-reviewed articles, conference papers, and relevant literature from the past decade, this research identifies key trends, challenges, and opportunities in this emerging field. The study focuses on the effectiveness of different machine learning methodologies in detecting, diagnosing, and intervening in mental health issues, highlighting the potential for early identification and personalized support. Furthermore, it addresses critical concerns related to data privacy, ethical considerations, and algorithmic biases, which are paramount for the responsible deployment of these technologies. The findings reveal significant advancements in the application of natural language processing and wearable technology data for mental health monitoring. However, gaps remain in longitudinal studies and the consideration of cultural and contextual factors. This research contributes to the existing body of knowledge by providing a comprehensive overview and identifying directions for future research, ultimately aiming to enhance the well-being and academic performance of students through innovative machine learning solutions.
Bibliometrik Analisis: Teknologi Permainan Bidang Pendidikan Pada Sekolah Menengah Pertama Rudi Kurniawan; Dadang Sudrajat
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

This study explores the use of game technology to enhance learning motivation and engagement among junior high school students in Indonesia. The background of the problem indicates low levels of learning motivation and student engagement in conventional learning processes. The root of this problem is linked to traditional teaching methods that are less engaging for students. This study aims to evaluate the effectiveness of game technology in addressing this issue. The research method employed a mixed methods approach involving a literature review, the development of educational game modules, and case studies in several junior high schools in Indonesia. The data used includes surveys on students' learning motivation, observations of student engagement, and interviews with teachers. The study also collected qualitative data from students' firsthand experiences in using game technology in learning. The results of the study demonstrate that the integration of game technology into the junior high school curriculum significantly increases students' learning motivation and engagement. Students who used educational games showed increased interest in the subject matter, were more active in class participation, and had a better understanding of the concepts taught. This study concludes that game technology is an effective tool for improving the quality of education in junior high schools and recommends a broader adoption of this technology in the Indonesian education system.
Bibliometrik Analysis: Konten Video Untuk Meningkatkan Daya Tarik Pariwisata Arif Rinaldi Dikananda; Dadang Sudrajat; Fatihanursari Dikananda; Rudi Kurniawan; Martanto
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The use of video content as a marketing tool in the tourism industry has seen a significant increase in recent years. This research aims to explore and develop effective video content strategies in increasing tourism appeal and influencing tourists' decisions to visit certain destinations. Research methods include bibliometric analysis of video content used in tourism marketing, as well as experiments to test the effectiveness of various video content strategies. The results of the study show that the characteristics of travel vlogs that include personal narratives, attractive visuals, and relevant information can increase user travel intentions. Additionally, audience engagement through short videos has proven to be a key factor in increasing travel interest. This research makes a new contribution in understanding the role of video content in tourism marketing and developing a video marketing strategy model that can be applied by the tourism industry to increase the attractiveness of tourist destinations. By utilizing the results of this study, the tourism industry can optimize the use of video content to reach a wider audience and increase positive perceptions of tourist destinations.
Analisis Bibliometrik: Media Pembelajaran Interaktif di Bidang Teknologi Pendidikan pada Database Scopus Tahun 2018-2024 Fatihanursari Dikananda; Ahmad Rifai
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

This study aims to analyze the trends in the use of interactive learning media in the field of educational technology through a bibliometric approach. Interactive learning media encourage active engagement of learners and include mobile apps, interactive whiteboards and interactive videos. Studies show that interactive media improve students' motivation, learning outcomes and creative thinking skills. Bibliometric methods were used to explore and visualize research trends and collaborations between researchers and institutions in this field. Data was collected from academic databases that included scientific articles, conference proceedings and dissertations. Tools such as VOSviewer were used to map collaboration networks and keyword trends that revealed several key research themes, including the effectiveness of interactive learning media, the development of technology-based media, and their implementation in various educational contexts. This study provides an in-depth understanding of research developments in interactive learning media and identifies research gaps that could be a focus in the future. The results show a significant increase in the number of publications related to interactive learning media in recent years. The study also identifies key centers of research excellence and collaborations between institutions.
Systematic Bibliometric Research Trend of Text Mining on Product Comments in Business Ecosystem Gifthera Dwilestari; Fadhil Muhammad Basysyar
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The business ecosystem represents a new paradigm that has gained considerable attention among researchers and practitioners. Despite its popularity, systematic literature reviews utilizing bibliometric analysis within this context remain sparse. This study aims to conduct a comprehensive bibliometric and visualization analysis of business ecosystem research, focusing on the impact of text mining on product comments. Employing VOSviewer for visualization, the study evaluates 95 scientific articles indexed in Scopus quartiles Q1 to Q4 from the Scopus database over the last decade (2001-2024). The bibliometric analysis identifies the most productive publishers, the evolution of scientific articles, and citation patterns. Visualization with VOSviewer reveals prevalent terms in titles and abstracts, author collaboration networks, and assists in identifying novel and underexplored topics within the business ecosystem. The findings provide valuable insights for researchers and practitioners, highlighting key trends and potential research gaps, thus contributing to the advancement of knowledge in the field.

Page 35 of 48 | Total Record : 471

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