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All Journal Jusikom: Jurnal Sistem Informasi Ilmu Komputer RISTEC : Research in Information Systems and Technology
Nugroho, Imam Ma’ruf
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Computer Science & IT Decision Sciences, Operations Research & Management

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NAÏVE BAYES ALGORITHM OPTIMIZATION USING PARTICLE SWARM OPTIMIZATION (PSO) FOR COVID-19 VACCINE SENTIMENT ANALYSIS ON TWITTER Nugraha, Rivan Adi; Hermanto, Teguh Iman; Nugroho, Imam Ma’ruf
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 6 No. 1 (2022): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v6i1.2776

Abstract

The Covid-19 vaccine is a vaccine that is quite popular, because it is the most needed and most discussed vaccine. There are 5 types of vaccines that are very popular including AstraZeneca, Moderna, Pfizer, Sinopharm and Sinovac. Sentiment analysis is a branch of text classification with computational linguistics and natural language processing that refers to a broad field, and text mining has a function to analyze opinions, judgments, sentiments, attitudes, evaluations and emotions of a person regarding an individual, organization, certain topics, services and other activities. This study aims to classify public sentiment towards the type of Covid-19 vaccine on social media Twitter, whether the opinion is positive or negative by using the Naïve Bayes algorithm based on Particle Swarm Optimization (PSO). The conclusion of this study is that the results of testing the Naïve Bayes algorithm with PSO using RapidMiner software are 79.17% accuracy, 87.69% precision, 85.07% recall for AstraZeneca vaccine, 68.82% accuracy, 92.29% precision, 71.72% recall for Moderna vaccine, 67.54% accuracy, precision 77.83%, recall 62.95% for Pfizer vaccine, accuracy 93.33%, precision 91.67%, recall 100.00% for Sinopharm vaccine, and accuracy 74.93%, precision 82.61%, recall 70.90% for Sinovac vaccine. It can be concluded that with the help of optimization PSO, the resulting confusion matrix value is greater and is proven to be more accurate. Keywords : Vaccine; Covid-19; Sentiment Analysis; Naive Bayes; Particle Swarm Optimization.
BATIK MOTIF CLASSIFICATION USING CNN WITH RESNET-50 ARCHITECTURE Wibisono, Muhammad Ridwan; Nugroho, Imam Ma’ruf; Defriani, Meriska
RISTEC : Research in Information Systems and Technology Vol. 6 No. 1 (2025): RISTEC: Research in Information Systems and Technology
Publisher : RISTEC : Research in Information Systems and Technology

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Abstract

Batik merupakan kerajinan tradisional Indonesia yang memiliki nilai seni tinggi dan telah diakui sebagai warisan budaya dunia oleh UNESCO pada 2 Oktober 2009. Namun, pengetahuan tentang identifikasi motif batik umumnya hanya dimiliki oleh mereka yang memiliki keahlian khusus, seperti pengrajin batik. Penelitian ini bertujuan untuk mengembangkan aplikasi berbasis Streamlit yang mampu mengklasifikasikan motif batik menggunakan metode Convolutional Neural Network (CNN) dengan arsitektur ResNet-50 untuk dapat menjadi solusi dalam mengenalkan batik secara lebih luas kepada masyarakat, baik sebagai media edukasi maupun sebagai alat bantu bagi industri kreatif. Penelitian ini menggunakan metodologi CRISP-DM (Cross-Industry Standard Process for Data Mining) yang mencakup tahapan Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, dan Deployment. Model dilatih selama 21 epoch, dengan hasil akurasi pelatihan sebesar 99,31%, akurasi validasi 94,37%, loss pelatihan 2,4%, dan loss validasi 22,25%. Dalam evaluasi menggunakan 140 sampel citra batik, model mencapai akurasi 89,285%. Hasil ini menunjukkan bahwa aplikasi yang dikembangkan berhasil dalam mengklasifikasikan motif batik menggunakan CNN.
IMPLEMENTATION OF HAVERSINE FORMULA IN AN ANDROID-BASED GEOGRAPHIC INFORMATION SYSTEM BPJS HEALTH FACILITIES IN PURWAKARTA Irgiyansyah; Nugroho, Imam Ma’ruf; Defriani, Meriska
RISTEC : Research in Information Systems and Technology Vol. 6 No. 1 (2025): RISTEC: Research in Information Systems and Technology
Publisher : RISTEC : Research in Information Systems and Technology

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Abstract

This study designs and develops an Application Android-based Geographic Information System (GIS) to assist residents of Purwakarta Regency in locating the nearest BPJS-affiliated healthcare facilities, addressing the limitations of distance information and mapping on the Health Office’s website. To compute distances, the application utilizes the Haversine Formula based on the user’s coordinates. It is developed using Flutter for the Android application and Laravel for the web-based admin system, following the Extreme Programming (XP) methodology. Blackbox Testing is used to ensure system functionality. As a result, the application can display a list and geographic locations of healthcare facilities along with the distance from the user. The application is expected to provide easier access to healthcare information and enhance the quality of health services in Purwakarta Regency.
E-COMMERCE WEBSITE DESIGN USING EXTREME PROGRAMMING METHOD (Case Study: UMKM Bolu Ara) Juniar, Rina; Nugroho, Imam Ma’ruf; Muhyidin, Yusuf
RISTEC : Research in Information Systems and Technology Vol. 6 No. 1 (2025): RISTEC: Research in Information Systems and Technology
Publisher : RISTEC : Research in Information Systems and Technology

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Abstract

UMKM Bolu Ara is a micro business engaged in the production of cakes and sponges, which still uses manual methods in recording and managing orders via WhatsApp. This system causes various obstacles such as delays in payment verification, order recording errors, and difficulties in data management. To overcome these problems, the design and development of e-commerce websites using the Extreme Programming (XP) method was carried out. The XP method was chosen because it is iterative and flexible, with stages of planning, design, coding, and testing. The tools used include the CodeIgniter 3 framework, PHP programming language, MySQL database, and Visual Studio Code editor, with XAMPP support as a local server. Testing is done using the Black Box Testing method to ensure system functionality in accordance with user needs. The development results show that the e-commerce website built is able to make the process of recording and managing orders more structured, and provide convenience for users in making transactions independently. This system also supports managers in recording data and reports better.
Co-Authors Defriani, Meriska Hermanto, Teguh Iman Irgiyansyah Juniar, Rina Muhyidin, Yusuf Nugraha, Rivan Adi Wibisono, Muhammad Ridwan