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All Journal Techno.Com: Jurnal Teknologi Informasi Electro Luceat SOSCIED Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Indonesian Journal of Networking and Security - IJNS Jurnal Pengabdian Pada Masyarakat METHABDI JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Adhi Priyanto
STMIK AKI Pati
Religion Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Immunology & microbiology Languange, Linguistic, Communication & Media Medicine & Pharmacology Physics Public Health Social Sciences

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Implementasi Algoritma Deep Learning untuk Analisis Sentimen Pengguna Platform Pendidikan Nugroho, Anjis Sapto; Prasetyo, Eko; Priyanto, Adhi; Puryono, Daniel Alfa
SOSCIED Vol 8 No 2 (2025): SOSCIED - November 2025
Publisher : LPPM Politeknik Saint Paul Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32531/jsoscied.v8i2.999

Abstract

More than 3.5 million Indonesian educators had used the Merdeka Mengajar Platform by 2024. Comparing this figure to the 3.37 million from the previous academic year, there has been an increase of almost 3.85%. However, an investigation is required to determine the reasons why the application's use has not yet achieved the anticipated goal number of users. This study does sentiment analysis on evaluations of the Merdeka Mengajar platform using Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM). The benefits of RNN and LSTM in processing sequential data, especially in text processing for sentiment analysis, led to their selection. The purpose of this study is to solve the difficulties in determining if users' sentiments on the platform are favorable or negative. Important steps in the research technique include preprocessing, data cleaning, and employing FastText embedding to convert text into numerical vectors. Then, using patterns in the text data, RNN and LSTM models are used to forecast sentiment. The study's findings demonstrate that the LSTM model can, with an estimated accuracy of 93.58%, identify long-term associations in sequential data. The RNN model, on the other hand, produces a lesser accuracy of 91.70%. Particularly in text data with intricate temporal circumstances, the LSTM model performs better at accurately classifying sentiment. By better understanding customer opinions and input on the Merdeka Mengajar platform, this study helps platform developers improve the quality of their services.
Strategi Pemberdayaan UMKM Melalui Pelatihan Pembuatan Iklan Digital untuk Optimalisasi Pemasaran Komoditas Lokal di Kecamatan Kayen Eko Prasetyo; Adhi Priyanto; Sthepanus Widjaja
Jurnal Pengabdian Pada Masyarakat METHABDI Vol 5 No 2 (2025): Jurnal Pengabdian Pada Masyarakat METHABDI
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Entrepreneurs are individuals or groups engaged in business activities to produce goods or services. To increase product visibility, they need to implement marketing strategies, including the use of digital media. However, many UMKM actors in Kayen District, Pati Regency, still rely on manual marketing methods or word-of-mouth promotion. To address this issue, Lembaga Penelitian dan Pengabdian kepada Masyarakat (LP2M) of STMIK AKI Pati organized a digital marketing training program for local UMKM. The goal is to enhance their ability to market their products or services effectively through digital platforms. The training is conducted in three stages: first, introducing the basic concepts of digital marketing; second, teaching participants how to use graphic design software such as Canva and Photoshop to create logos and promotional flyers; and third, guiding them on how to register and use e-commerce platforms like Shopee and Tokopedia, as well as how to advertise effectively on social media. This program aims to help UMKM actors in Kayen understand the importance of digital marketing and develop more effective strategies to promote and sell their products online.
Co-Authors - STMIK AKI Pati, Fanji Ulinnuha Anjis Sapto Nugroho Ardiyanto, Yusuf Asih, Yuni Retno Daniel Alfa Puryono Eko Prasetyo Fanji Ulinnuha - STMIK AKI Pati Haryani, Ninik Listiarini Edy Sudiati Moh Rofi Muhammad Ainun Najib Nur Hafid Prastichia, Vistalia Putri Sthepanus Widjaja Sugi Harsono Syahid Nur Salas Uliana, Uliana Yuni Retno Asih Yusril Muna