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All Journal Jurnal Nasional Pengabdian Masyarakat Journal of Statistics and Data Science
Beat, Sebastiana Laura
Unknown Affiliation
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Mathematics Other

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Pengembangan Media Sosial Instagram dan TikTok sebagai Sarana Branding dan Edukasi di BSI Kabupaten Tangerang Arinata, Kadek Wika; Savera, Shan; Khasanah, Iftha Nikmatul; Prastowo, Marsya Aqila; Nuraprilia, Dyah; Beat, Sebastiana Laura; Hartono, Kennard Kurniadi; Purba, Delima Ester; Deliberto, Felicio; Nurhayati, Nurhayati
Jurnal Nasional Pengabdian Masyarakat Vol. 6 No. 1 (2025): Jurnal Nasional Pengandian Masyarakat
Publisher : Training & Research Institute - Jeramba Ilmu Sukses

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47747/jnpm.v6i1.2726

Abstract

The development of Instagram and TikTok as branding and educational tools for the Main Waste Bank of Tangerang Regency has shown significant results in increasing visibility and community participation in waste management. Through an integrated content marketing approach, the program successfully expanded the reach and engagement of BSI KabTang's social media accounts, with Instagram followers growing to 7136 and TikTok followers reaching 3935 within three months. Educational content presented in various formats, such as infographics, short videos, and interactive posts, effectively raised public awareness about the 3R principles (Reduce, Reuse, Recycle) and sustainable waste management practices. The main challenges included limited digital infrastructure and the digital literacy of the management team, which were addressed through intensive mentoring and sustainability strategies, including staff training, guidebook development, and building collaborative networks with environmental communities. This program demonstrated that social media can be an effective tool for environmental campaigns. Moving forward, the development of more interactive digital platforms and collaborations with various stakeholders is recommended to enhance the program's impact
Enhancing Operational Efficiency in Domestic Cargo Handling at Tanjung Priok Port Affandi, Karina; Wulandari , Yuhanda Tri; Beat, Sebastiana Laura
Journal of Statistics and Data Science Vol. 5 No. 1 (2026)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jsds.v5i1.37840

Abstract

Maritime transportation plays a crucial role in national development and population mobility in archipelagic countries like Indonesia. It is also key in encouraging Indonesia's economic growth, especially in frontier, outermost, and underdeveloped areas, as well as being a gateway to international trade. One of the important nodal points in sea transportation is the Port of Tanjung Priok in North Jakarta. This port is the largest and busiest, serving as the main gateway for the flow of export-import goods and the distribution of goods between islands. This research aims to analyze the loading and unloading activities of domestic goods at the Port of Tanjung Priok using secondary data from the official website of the Central Bureau of Statistics for the period from January 2007 to December 2023. The models used are Seasonal Autoregressive Integrated Moving Average (SARIMA) and Long Short-Term Memory (LSTM). SARIMA is employed due to the presence of seasonal patterns in the data. Subsequently, the SARIMA model will be compared with the Long Short-Term Memory (LSTM) model, which uses a machine learning approach to evaluate and determine the most accurate model for predicting domestic cargo handling activities at Tanjung Priok Port. Based on the RMSE analysis, the LSTM model has a lower RMSE compared to the SARIMA model, indicating that LSTM provides more accurate predictions for this time series data. However, it is important to note that a lower RMSE does not always mean that one model is generally better. Additional evaluations, such as residual analysis, other statistical tests, or prediction consistency through cross validation, should also be considered to validate the model's superiority comprehensively. This analysis is expected to provide deeper insights into port capacity planning and operational management, enabling more precise and effective decision-making in response to future demand dynamics and operational trends.
Co-Authors Affandi, Karina Arinata, Kadek Wika Deliberto, Felicio Hartono, Kennard Kurniadi Khasanah, Iftha Nikmatul Nuraprilia, Dyah Nurhayati Nurhayati Prastowo, Marsya Aqila Purba, Delima Ester Savera, Shan Wulandari , Yuhanda Tri