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All Journal Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Journal of Artificial Intelligence and Digital Business Proceedings of The International Conference on Computer Science, Engineering, Social Sciences, and Multidisciplinary Studies
Sitepu, Andri Ismail
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Religion Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Social Sciences

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Enhanced Rainfall Forecasting Through Deep Learning Optimization Using Long Short-Term Memory Networks Harefa, Ade May Luky; Antoni, Robin; Sitepu, Andri Ismail; Limbong, Yohannes France; Novelan, Muhammad Syahputra
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 2 (2025): Mei - Juli
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i2.487

Abstract

This study aims to develop a rainfall prediction system using Deep Learning with the Long Short-Term Memory (LSTM) method to improve prediction accuracy and efficiency. The model was built using rainfall data from Gunung Sitoli, covering the period from October 16 to December 14, 2004. The dataset was divided into 90% for training and 10% for testing. The LSTM model was configured with 1 hidden layer and trained for 50 epochs. To evaluate its performance, the Mean Squared Error (MSE) metric was applied. The model achieved an MSE of 0.03 on the test data, indicating a low prediction error and good accuracy. This result shows that LSTM is capable of learning rainfall patterns over time and producing reliable forecasts. Furthermore, the model was integrated into a system to streamline the forecasting and evaluation process. This integration provides an efficient alternative to manual calculations, offering users faster and more accessible predictions. The implementation of this system is especially beneficial for early warning and decision-making processes in regions like Gunung Sitoli, where rainfall patterns can significantly impact on daily activities and disaster preparedness.
PELATIHAN PEMBUATAN DIGITAL LOOKBOOK BERBASIS AI BAGI MASYARAKAT DI LKP AZ ZIKRA Hermawan, Rudi; Wijaya, Rian Farta; Budianto, Eko; Septian, Muhammad; As'ary, Muhammad Hasyim; Sitepu, Andri Ismail
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol 5, No 2 (2025): Desember 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v5i2.5315

Abstract

Abstract: The rapid development of artificial intelligence (AI) technology presents both challenges and opportunities for the general public, particularly in the creative economy sector. This community service activity aims to improve the digital literacy and creative competency of the community at LKP Az Zikra through training on creating digital lookbooks using AI-based platforms. The method employed involves direct training with a "learning by doing" approach, encompassing introduction to generative AI, prompt engineering techniques, and practical creation of digital fashion catalogs. The activity focuses on transferring skills in utilizing tools such as AI image generators to produce professional visual assets without high costs. The results indicate a significant increase in participants' ability to operate AI technology for product visualization purposes. Participants successfully produced digital lookbooks that meet industry standards in terms of aesthetics and resolution. This capability proves that AI technology democratization can be effectively achieved through structured non-formal education, providing economic value added for community business promotion.            Keywords: artificial intelligence; digital lookbook; community empowerment; creative economy; vocational training  Abstrak: Pesatnya perkembangan teknologi kecerdasan buatan (Artificial Intelligence/AI) menghadirkan tantangan sekaligus peluang bagi masyarakat umum, khususnya dalam sektor ekonomi kreatif. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan literasi digital dan kompetensi kreatif masyarakat di LKP Az Zikra melalui pelatihan pembuatan digital lookbook berbasis platform AI. Metode yang digunakan adalah pelatihan langsung dengan pendekatan learning by doing yang mencakup pengenalan generative AI, teknik prompt engineering, dan praktik pembuatan katalog mode digital. Fokus utama kegiatan adalah transfer keterampilan penggunaan perangkat lunak penghasil gambar otomatis untuk menghasilkan aset visual profesional tanpa biaya tinggi. Hasil kegiatan menunjukkan adanya peningkatan signifikan pada kemampuan peserta dalam mengoperasikan teknologi AI untuk keperluan visualisasi produk. Peserta berhasil menghasilkan luaran berupa digital lookbook yang memenuhi standar estetika industri dan resolusi gambar. Kemampuan ini membuktikan bahwa demokratisasi teknologi AI dapat dilakukan efektif melalui pendidikan non-formal yang terstruktur serta memberikan nilai tambah ekonomi bagi promosi usaha masyarakat. Kata kunci: kecerdasan buatan; digital lookbook; pemberdayaan masyarakat; ekonomi kreatif; pelatihan vokasi  
The Optimization of Instagram and TikTok Social Media to Help MSMEs Reach Generation Z Customers Silaban, Indra Marto; Sarif, Muhammad Irfan; Rambe, Rezkinah; Sitepu, Andri Ismail
Proceedings of The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies Vol. 1 (2025)
Publisher : CV Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/cessmuds.v1.108

Abstract

Generation Z represents a strategic market segment for Micro, Small, and Medium Enterprises (MSMEs) due to their high digital engagement and purchasing potential. Instagram and TikTok have emerged as dominant social media platforms among Generation Z, emphasizing visual storytelling, short-form video, and interactive content. This study aims to analyze the optimization of Instagram and TikTok as digital marketing tools to help MSMEs effectively reach Generation Z customers. A qualitative descriptive approach was employed through systematic literature review and observational analysis of MSME social media practices. The findings indicate that content creativity, algorithm-oriented features utilization, posting consistency, and audience interaction significantly influence engagement rates and brand awareness among Generation Z users. Furthermore, authentic storytelling and trend-based content enhance purchase intention and customer trust. This research contributes by providing a structured digital marketing framework tailored for MSMEs targeting Generation Z through social media platforms. The results are expected to support MSME digital transformation and sustainable competitiveness in the digital economy
Co-Authors Antoni, Robin As'ary, Muhammad Hasyim Eko Budianto Harefa, Ade May Luky Limbong, Yohannes France Muhammad Syahputra Novelan Rambe, Rezkinah Rudi Hermawan Sarif, Muhammad Irfan Septian, Muhammad Silaban, Indra Marto Wijaya, Rian Farta