Gusti Made Arya Sasmita
Jurusan Teknologi Informasi, Fakultas Teknik, Universitas Udayana

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Performance Analysis of the K-Nearest Neighbors (K-NN) for Sentiment Analysis of Online Loan Application X Gunadarma, I Ketut Agus Leo; Arya Sasmita, Gusti Made; Prayana Trisna, I Nyoman
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 12 No 3 (2024): Vol. 12, No. 3, December 2024
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2024.v12.i03.p07

Abstract

The digital economy in Indonesia is growing rapidly, including in online lending services. Application X is one of the popular online lending applications, offering users convenience in applying for loans online. This research employs sentiment analysis on user reviews of Application X to understand their preferences and needs. The K-Nearest Neighbours (K-NN) method is applied as the primary algorithm for sentiment classification. Data collected through user review scraping undergoes a series of preprocessing stages, such as tokenization, stop word removal, and stemming, aimed at improving data quality. The K-NN model is tested in various scenarios to achieve the best results. The best scenario reveals that the highest accuracy is achieved by the K-NN model when the stop word removal process is not applied during the data preprocessing stage where the accuracy without using the stop word process was 92.9%, compared to 89.9% when using stop words.
Internet of Things Based Water Quality Control System Putra, I Putu Andika; Wibawa, Kadek Suar; Arya Sasmita, Gusti Made
Jurnal Indonesia Sosial Teknologi Vol. 5 No. 9 (2024): Jurnal Indonesia Sosial Teknologi
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jist.v5i9.1195

Abstract

Fish incubation, which involves the hatching of fish eggs, represents the process of embryogenesis until the embryo emerges from its protective shell. This intricate developmental journey is influenced by a combination of internal and external factors. External factors can be influenced by water quality that is not suitable for hatching fish eggs. Water quality, which includes temperature, dissolved oxygen, light intensity, salinity, and pH, is an important and limiting factor for living creatures that live in water, including chemical, biological, and physical factors. Poor water quality can prevent fish eggs from hatching and even cause death. The primary objective here is the creation of an Internet of Things (IoT)-based system designed for controlling water quality during fish incubation. This system is intended to aid fish farmers in effectively control the environmental conditions within their incubation ponds. The method used in designing IoT device is research and development, and it uses the Arduino Mega microcontroller as the main device to run pH sensors, turbidity sensors, oxygen sensors, temperature sensors, and relay modules. Water Quality Control System The fish incubation was successful. The average time needed to change the water temperature from 28.5 to 29 degrees Celsius is 4 minutes and 7 seconds; change the dissolved oxygen level from 11 to 11.5 is 3 minutes and 33 seconds; change the pH value of the water from 6.9 to 7.1; and maintain turbidity below 5 with an average time of 5 minutes and 58 seconds. Controlling water quality can speed up the fish egg incubation process for 8 hours.