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All Journal Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Journal of Informatics and Communication Technology (JICT) Buletin Ilmiah Ilmu Komputer dan Multimedia (BIIKMA) Journal of International Multidisciplinary Research Jurnal Pengabdian kepada Masyarakat Journal of Informatics and Communication Technology (JICT) RUBINSTEIN IKRAM: Jurnal Ilmu Komputer Al Muslim ALMUISY: Journal of Al Muslim Information System
Yakub
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Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Public Health Social Sciences Other

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Journal : RUBINSTEIN

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Bibliometric Analysis: IoT Networks and Wireless Communication Protocols Kurnia, Yusuf; Yakub; Rimbawan Oprasto, Raditya; Oktavianus Gunawan, Aldi
RUBINSTEIN Vol. 2 No. 1 (2023): RUBINSTEIN (juRnal mUltidisiplin BIsNis Sains TEknologI & humaNiora)
Publisher : LP3kM Buddhi Dharma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/rubin.v2i1.2295

Abstract

Penelitian ini menggunakan pendekatan metodologi sistematis untuk mengumpulkan, mengevaluasi, dan menganalisis penelitian terkait analisis keamanan protokol komunikasi nirkabel dalam jaringan Internet of Things (IoT). Prosesnya melibatkan pencarian melalui pangkalan data ilmiah utama dan konferensi terkait. Tujuannya adalah memberikan wawasan yang mendalam tentang tren terbaru dalam analisis keamanan protokol komunikasi nirkabel di lingkungan jaringan IoT. Diharapkan, hasil tinjauan literatur ini akan memberikan pemahaman yang lebih baik kepada peneliti. Selain itu, tinjauan ini juga diharapkan mampu mengidentifikasi kesenjangan dalam penelitian yang telah ada serta memberikan arahan untuk penelitian masa depan dalam bidang ini. Evaluasi jurnal ilmiah melalui metrik h-index memberikan pandangan tentang pengaruh, produktivitas, dan kualitas karya ilmiah masing-masing jurnal, serta informasi tentang kontribusinya dalam mengembangkan pengetahuan tentang IoT Networks dan Wireless Communication Protocols. Selama lima tahun terakhir, perkembangan riset ini tercermin dalam peningkatan frekuensi kata-kata kunci seperti "IoT," "Jaringan," "Data," dan "Komunikasi," mencerminkan minat yang semakin berkembang dalam aspek-aspek tersebut. Studi ini juga mengungkap tiga kombinasi kata kunci yang paling umum, seperti "Perangkat IoT," "Jaringan Nirkabel," dan "Konsumsi Energi," yang mencerminkan fokus pada teknologi yang efisien dan berkelanjutan. Selain itu, dalam rangka merangsang penelitian lebih lanjut, teridentifikasi lima kombinasi topik yang menjanjikan, seperti "IoT Security Challenges," "Wireless Network Performance," "Data Management Solutions," "Internet Connectivity Management," dan "Innovative IoT Applications." Harapannya, studi ini akan membantu meningkatkan pemahaman tentang analisis keamanan protokol komunikasi nirkabel dan jaringan IoT.
Web-Based Car Sales Prediction System Using the ARIMA (Autoregressive Integrated Moving Average) Model for Optimizing Automotive Marketing Strategies Kurnia, Yusuf; Yakub; Rudy Arijanto; Winson Layanda; Dwi Putra, Dicky Surya
RUBINSTEIN Vol. 4 No. 1 (2025): RUBINSTEIN (juRnal mUltidisiplin BIsNis Sains TEknologI & humaNiora)
Publisher : LP3kM Buddhi Dharma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/rubin.v4i1.4039

Abstract

This study aims to develop a web-based car sales prediction system using the ARIMA (Autoregressive Integrated Moving Average) model to support the optimization of marketing strategies in the automotive sector. With the rapid growth of the automotive industry in Indonesia, companies, particularly car showrooms, face the challenge of accurately forecasting vehicle demand. Therefore, an ARIMA-based prediction system can assist in estimating future sales based on historical data, thereby improving stock management, distribution, and marketing strategies. The system was developed using five years of historical sales data and implemented the ARIMA model to forecast car sales for upcoming periods. It was built with the Python programming language, employing Flask for the backend and HTML, CSS, and JavaScript for the frontend. The prediction results are presented in the form of interactive graphs, enabling users to make data-driven decisions more effectively. System evaluation was carried out by measuring prediction accuracy using MAPE (Mean Absolute Percentage Error) and RMSE (Root Mean Square Error) metrics. The testing results indicate that the ARIMA model can generate predictions with a high level of accuracy, assisting showrooms in planning stock and promotional activities more efficiently. Furthermore, the system is equipped with a responsive user interface, making it easily accessible via mobile devices. This research contributes to the utilization of technology in sales planning, particularly in the automotive sector, by enabling more precise, efficient, and data-driven decision-making.
Co-Authors Arif Rahman Hakim Basri, Amat Dahlan lama bawa Dahlia Amelia Dwi Putra, Dicky Surya Hendratna, Gempa Jonathan Gunawan Jusmawati Khaerunnas Marini Umi Atmaja, Dewi Oktavianus Gunawan, Aldi Pralantina, Peny Raharjo, Dasa Rakhim, Indra Paripurna Rendy Agustian Hidayat Rimbawan Oprasto, Raditya Rudy Arijanto Saputri, Rena Sayyaf Kholillullah Siti Nurbaiti Siti Nurhayati Suhadarliyah Swastika GKD, Puri Syahruddin, Muhammad Tonggiroh, Mursalim Winson Layanda Yusuf Kurnia, Yusuf