Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal Jurnal Riset Informatika QISTINA: Jurnal Multidisiplin Indonesia
Listia, Hijka
Unknown Affiliation
Religion Computer Science & IT Economics, Econometrics & Finance Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Nursing

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

Found 2 Documents
Search

 1 
Analysis of Public Sentiment Regarding the Issue of Cancelling the Revision of the 2024 Regional Election Law with NLP Wardaniah, Sabina; Listia, Hijka; Wulandari, Siti; Ramadhani, Fanny; Dewi, Sri; Hasan, Afrizal
QISTINA: Jurnal Multidisiplin Indonesia Vol 3, No 2 (2024): December 2024
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/qistina.v3i2.4166

Abstract

The latest changes regarding the age requirements for regional head candidates in the 2024 Election by the Supreme Court have given rise to various responses from the public. This decision has become an important issue that is widely discussed on social media and mass media, where this decision has caused various reactions, both positive, negative and neutral. Sentiment analysis is important to determine public opinion on this decision. This study aims to analyze public sentiment on the Issue of Cancellation of the Revision of the 2024 Pilkada Law. This study uses the Natural Language Processing (NLP) method with the Naive Bayes algorithm. The data used is text data in the form of public opinion on the Issue of Cancellation of the Revision of the 2024 Pilkada Law collected via Twitter. This data is then processed using NLP techniques such as cleaning, tokenization, normalization, filtering and stemming. After that, public opinion on the Issue of Cancellation of the Revision of the 2024 Pilkada Law is classified into positive, negative and neutral sentiment categories. The results of the study showed that the results of the model performance evaluation using data testing produced an accuracy of 92%, so it can be concluded that this model is good enough for sentiment analysis. Accuracy shows that the model makes correct predictions on 92% of the total data, which is dominated by the neutral class.
DECISION SUPPORT SYSTEM FOR SELECTION OF OUTSTANDING PROSPECTIVE STUDENTS AT SMKS AL WASHLIYAH 2 MERBAU SCHOOL USING PROFILE MATCHING Wardaniah, Sabina; Listia, Hijka; Wulandari, Siti; Yandra Niska, Debi
Jurnal Riset Informatika Vol. 7 No. 3 (2025): Juni 2025
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v7i3.371

Abstract

The selection of outstanding students in the school environment is an important process that requires objective and structured assessment. However, in practice, this process is still often done manually so that it has the potential to cause subjectivity and inaccuracy in decision making. This study aims to build a Decision Support System (DSS) in the selection of prospective outstanding students at SMKS Al-Washliyah 2 Merbau using the Profile Matching method. This method works by comparing the competencies or criteria possessed by students with the ideal profile that has been determined so that the gap (difference) between the two can be identified. The criteria used in the assessment include academic aspects, organizational activity, personality and discipline. This system is implemented in the form of a computer-based application to facilitate the selection process and improve assessment accuracy. The implementation of Decision Support using the Profile Matching method can be concluded that the system built is able to provide an effective solution in the selection process of prospective outstanding students at SMKS Al-Washliyah 2 Merbau.
Co-Authors Hasan, Afrizal Niska, Debi Yandra Ramadhani, Fanny siti wulandari Sri Dewi Wardaniah, Sabina