Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal JURIKOM (Jurnal Riset Komputer) TIN: TERAPAN INFORMATIKA NUSANTARA
Raditia Vindua
Universitas Pamulang, Tangerang Selatan
Aerospace Engineering Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Analisis Sentimen Pemilu Indonesia Tahun 2024 Dari Media Sosial Twitter Menggunakan Python Raditia Vindua; Achmad Udin Zailani
JURIKOM (Jurnal Riset Komputer) Vol 10, No 2 (2023): April 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i2.5945

Abstract

The general election of Indonesia in the upcoming 2024 will be an interesting topic for social media users, especially Twitter. Currently, Twitter is very influential in building sentiment, preferences, and public politics. So that people's Tweets can be used to see a picture of public opinion. There are various opinions of Twitter users with positive, neutral and negative sentiments. However, classifying the sentiments of Twitter users requires quite a lot of time and effort due to the large number of tweets found. The large number of incoming tweets regarding the election encourages the need for a method that helps to view public opinion effectively. By providing the textblob library, Python, which is a programming language, is able to classify tweet data and can be used to answer these problems. The tweet data is preprocessed first where there are two processes in the initial data, namely the cleaning and stemming processes. After that, a sentiment analysis was carried out to find out how the results of the classification related to public opinion from the 2024 elections and classify them into three classes, namely positive, neutral and negative using Python. The results of this study show that Python performs sentiment analysis with the results of the proportion of positive class sentiments of 40%, 52% neutral and 8% negative about the 2024 elections so that it can be concluded that Python can classify tweets from Twitter so that we can identify public opinion about elections. The general public of Indonesia in 2024 will have neutral opinions tend to be positive
Perancangan Aplikasi Absensi Karyawan Menggunakan Geolocation dan Metode Agile Scrum Berbasis Android Raditia Vindua; Eka Yuni Titik Artaningsih; Adam Muiz
TIN: Terapan Informatika Nusantara Vol 7 No 1 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i1.9739

Abstract

Employee attendance is an important factor in enforcing discipline, which is directly related to improving company productivity. In the digital era, companies are required to have an attendance system that is efficient, accurate, and capable of minimizing potential fraud. The manual attendance method currently used has several weaknesses, such as being vulnerable to data manipulation, difficult to verify due to the absence of accurate attendance evidence, and time-consuming in the recapitulation process. This condition becomes a challenge for construction companies engaged in infrastructure development, particularly in the gas and oil sector, because most employees work in the field. This study aims to develop an Android-based attendance system supported by geolocation technology to assist the process of recording employee attendance in real time and based on location. The system was developed using Java-based Android programming and MySQL as the database, with the Agile Scrum development method carried out gradually through planning, sprint, evaluation, and system refinement stages. The geolocation feature is used to record the latitude and longitude coordinates of employees when performing attendance, allowing attendance data to be verified by management. The testing results show that the system increased the efficiency of the attendance recapitulation process by 75%, from an average of 20 minutes manually to 5 minutes using the system. In addition, the location accuracy testing showed a coordinate suitability level of 92% based on a comparison between the attendance location points and the predetermined work locations. The black-box testing results also showed that all main system functions, including login, clock-in attendance, clock-out attendance, location validation, and data recapitulation, operated with a 100% success rate. Therefore, the Android-based attendance system with geolocation can help improve the efficiency of attendance management, reduce the potential for data manipulation, and support more effective human resource management.
Co-Authors Achmad Udin Zailani Adam Muiz Eka Yuni Titik Artaningsih