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Journal : Informatika

Penerapan Natural Language Processing dalam Pembuatan Aplikasi Penerjemah Bahasa Melayu Dialek Panai – Bahasa Indonesia Dar, Muhammad Halmi; Hasibuan, Mila Nirmala Sari; Nasution, Fitri Aini
Jurnal Informatika Vol 11, No 3 (2023): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v11i3.5887

Abstract

The Panai dialect of Malay is the mother tongue used by the speaking community in four sub-districts in Labuhanbatu Regency. The reduced number of native speakers who are skilled in the Panai Malay dialect can threaten the sustainability of this language. Efforts to preserve the Panai Malay dialect must be made to avoid extinction. One way that can be done is to document vocabulary in the form of a translator application. This study aims to create an application translator for the Panai-Indonesian dialect of Malay by applying natural language processing. As for the potential users of this application, they are the people of Labuhanbatu in general, especially those in the four sub-districts previously described. The stages of the research method used were: requirement analysis, design, implementation, testing, and maintenance. This research focuses on technology for improving information and communication technology content in the context of local wisdom (culture and language) in Indonesia. The focus of this research is in line with the Strategic Plan (RENSTRA) of Labuhanbatu University, which covers the fields of information and communication technology and cultural arts. From the results of this study, it is hoped that local wisdom in Labuhanbatu Regency will be maintained as social capital for the resilience of the Indonesian nation.
Analisis Sentimen Ulasan Pengguna Aplikasi pada Google Play Store Menggunakan Algoritma Support Vector Machine Lubis, Sanny Khairani; Dar, Muhammad Halmi; Nasution, Fitri Aini
Jurnal Informatika Vol 11, No 2 (2023): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v11i2.5860

Abstract

One of the most popular e-commerce sites in Indonesia is Shopee. As the largest marketplace application in Indonesia, Shopee provides product and service review features to users on the Google Play Store. The review feature is very helpful to find out whether user reviews are positive or negative. Having user reviews will help Shopee improve its services. To identify a very large number of user reviews, it is not possible to do it manually by reading them one by one. This process will take a very long time and is not effective. Therefore, we need a method that is able to identify reviews from users more effectively and efficiently. This research aims to conduct sentiment analysis of user reviews of the Shopee application on the Google Play Store by applying the Support Vector Machine algorithm. The research stages carried out started with dataset collection, dataset labeling, preprocessing, TF-IDF weighting, classification, and evaluation. From the research results, accuracy was 70.88%, precision was 49.49%, recall was 52.55%, and F1-score was 49.84%. From these results, it can be concluded that the performance of the support vector machine algorithm in classifying the sentiment of user reviews of the Shopee application on the Google Play Store is quite good.