Claim Missing Document
Check
Articles

Found 2 Documents
Search

Opensid: Memberdayakan Perangakat Desa Tidu Di Kecamatan Pohjentrek, Kabupaten Pasuruan Dengan Sistem Informasi Muhammad Udin; Khoirul Anwar
MENGABDI : Jurnal Hasil Kegiatan Bersama Masyarakat Vol. 1 No. 5 (2023): Oktober : MENGABDI : Jurnal Hasil Kegiatan Bersama Masyarakat
Publisher : Asosiasi Riset Ekonomi dan Akuntansi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/mengabdi.v1i5.392

Abstract

The application of technology in public services has become an indispensable obligation, even for the Village Government of Tidu in Pohjentrek Subdistrict, Pasuruan Regency. Manual approaches in public services are vulnerable to serious problems, such as the risk of losing important documents and the lack of structured recording of documents issued by the Village Government of Tidu. In response to this challenge, a community service effort was undertaken to support the Government and the community of Tidu Village in utilizing the Tidu Village Information Website. The mentoring and training sessions conducted successfully demonstrated that the implementation of the service system by the Village Government of Tidu is much more productive, with time savings and a transition from manual data management to digital format through the village information system.
Evaluasi Sentimen Review Produk Roundup Menggunakan Algoritma Support Vector Machine: Evaluasi Sentimen Review Produk Roundup Menggunakan Algoritma Support Vector Machine Mohamad Khoiron; Dian Ahkam Sani; Mohammad Zoqi Sarwani; Muhammad Mahrus Ali; Khoirul Anwar; Muhammad Udin
J-Innovation Vol. 13 No. 2 (2024): Jurnal J-Innovation
Publisher : Politeknik Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55600/jipa.v13i2.313

Abstract

In today's digital era, more and more internet users are sharing their experiences and opinions about certain products. Sentiment analysis can be used to extract valuable information from the data generated by the shopee application users. This study aims to conduct a sentiment analysis of Roundup product reviews. The method used is the Support Vector Machine (SVM). SVM is an effective machine learning method for classifying text based on positive or negative sentiments. The purpose of this study is the SVM model which can be used to perform sentiment analysis automatically on Roundup product reviews. The results of this analysis can provide important insights for Roundup producers in understanding consumer perceptions of their products. In addition, this research can also be a guide for consumers in choosing and understanding weed killer products that suit their needs and preferences. In this study, the accuracy value was 80%, the precision value was 80%, the recall value was 100% and the value F1 score of 88.89%.