Article Per Year (5 Year)
p-Index From 2021 - 2026
1.908
P-Index
This Author published in this journals
All Journal SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Computer Based Information System Journal Jurnal Puan Indonesia Jurnal Pengabdian Barelang Prosiding Seminar Nasional Ilmu Sosial dan Teknologi (SNISTEK)
Anggia Dasa Putri
Universitas Putera Batam
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Nursing Public Health Social Sciences Other

Published : 11 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : computer based information system journal

 1 
PERANCANGAN SISTEM PAKAR DIAGNOSA PENYAKIT TONSILITS MENGGUNAKAN METODE FORWARD CHAINING BERBASIS WEB Vincent Vincent; Anggia Dasa Putri
Computer Based Information System Journal Vol. 13 No. 1 (2025): CBIS Journal
Publisher : Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/cbis.v13i1.9583

Abstract

A common ear, nose, and throat (ENT) condition that typically affects people of all ages is tonsillitis. Tonsillitis related issues can be avoided with a diagnosis procedure. In the medical field, expert systems a technology that can solve issues using expert knowledge are frequently employed to diagnose illnesses. People can determine whether they have tonsillitis or not by simply use the system for early diagnosis. The Forward Chaining technique is applied on the expert system. Because the Forward Chaining approach can trace the rules from user inputs and then derive conclusions, it is usually used. The Rapid Application Development (RAD) approach is implemented during application design and development simply because the method has the benefit of enabling the quick development of applications. The tonsillitis expert system was developed using the PHP programming language and MySQL database, which facilitate the maintenance of facts and knowledge. From the research results, it is shown that the system were able to help diagnose tonsillitis quickly and provide recommendations for treatments. Expert system to diagnose tonsillitis is expected to raise public awareness of the illness's dangers and the need of staying well. The system should also be able to help the general public make well informed judgments regarding treatment of tonsillitis.
IMPLEMENTASI METODE RULE-BASED REASONING PADA EXPERT SYSTEM DALAM MENDETEKSI GANGGUAN PENCERNAAN PADA ANAK Putri Anengsi Manurung Sabar Manurung; Anggia Dasa Putri
Computer Based Information System Journal Vol. 13 No. 2 (2025): CBIS Journal
Publisher : Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/cbis.v13i2.10379

Abstract

Digestive disorders in children are a serios health issue globally, with diarrhea being a leading cause of mortality among toddlers. In Batam City, the hitgh incidence of acute diarrhea and other digestive disorders in children underscores the urgency for better management. Contributing factors include immature immune systems, unhealthy eating patterns, poor sanitation, low parental understanding of Clean and Healthy Living Behavior, and limited access to medical information and facilities. This problem is futher exacerbated by overlapping symptoms of digestive disorders, making early diagnosis difficult. To address these challenges, this research aims to design and build a web-based expert system application capable of detecting digestive disorders in children. The system implements a Rule-Based Reasing method with a Forward Chaining algorithm, which logically matches user-inputted symptoms against rules in tis knowledge base to generate a rapid initial diagnosis. This application focuses on three main indicators of degetive disorders : Diarrhea, Constipation, and GERD, for children aged 5 months to 12 years. Thus, this expert system is expected to be an interactive tool that enhances parental understanding, facititates early diagnosis of digestive disorders in children, and serves ad a reference for healthcare professionals and the development of health information systems.
ANALISIS PERBANDINGAN SVM, KNN DAN NAÏVE BAYES PADA SENTIMENT ANALYSIS TWEET MAKAN BERGIZI GRATIS Ibnu Abdul Ghofur; Anggia Dasa Putri
Computer Based Information System Journal Vol. 14 No. 1 (2026): CBIS Journal
Publisher : Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/cbis.v14i1.10994

Abstract

This study explores the effectiveness of three machine learning classifiers—Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Naïve Bayes—in analyzing public sentiment toward the Free Nutritious Meal Program using data from the X (Twitter) platform. Tweets were collected via Tweet Harvester by applying keyword-based filtering over the August–October 2025 period. Prior to model implementation, the textual dataset underwent comprehensive preprocessing, including data cleaning, case normalization, lexical standardization, tokenization, stopword elimination, and stemming. Sentiment labels were generated using a lexicon-based approach to distinguish between positive and negative opinions. The processed data were divided into training and testing subsets for classification. Model performance was evaluated using accuracy metrics derived from the confusion matrix. The results show that SVM outperformed the other models with an accuracy of 91.7%, followed by Naïve Bayes at 79.6% and KNN at 79.3%, indicating the strong capability of SVM in handling complex textual representations in social media sentiment analysis.
Co-Authors Argo Putra Prima Citra Indah Asmarawati Dian Lestari Siregar Dian Lestari Siregar Dian Lestari Siregar Dian Lestrari Siregar Ellbert Hutabri, Ellbert Evan Rosiska Evan Rosiska Evi Ayu Dina Wati Fauzan Harits Ibnu Abdul Ghofur Indrawan, Mohamad Gita Nanda Jarti Nurma Dhona Handayani Pratiwi, Mariska Putri Putri Anengsi Manurung Sabar Manurung Raymond Raymond Rio rahmat Yusran Robby Satria tukino, tukino Vincent Vincent