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All Journal RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Generation Journal
Moh Rosidi Zamroni
UNIVERSITAS ISLAM LAMONGAN
Computer Science & IT Engineering

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KLASIFIKASI KUALITAS UDARA DENGAN METODE NAIVE BAYES BERBASIS WEB: AIR QUALITY CLASSIFICATION USING WEB-BASED NAIVE BAYES METHOD Sugeng Dwi Budi Priantoro; M Ghofar Rohman; Moh Rosidi Zamroni
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6447

Abstract

Air quality is a critical indicator for public health and the environment. This study presents the first web‑based implementation for classifying the Air Pollutant Standard Index (ISPU) of Jakarta using the 2024 dataset from Satu Data Indonesia. The Gaussian Naive Bayes method was chosen for its efficiency and ability to handle continuous numerical data. Preprocessing steps included mean imputation, removal of “no data” and “very unhealthy” categories, and a random state 80:20 train‑test split. Evaluation results show 90.57% accuracy surpassing the KNN baseline of 86% with precision and recall F1‑scores for the “Unhealthy” category at 84.09% and 92.50%, respectively. A Flask‑based web application air quality prediction. These findings confirm the superiority of Gaussian Naive Bayes over KNN in handling data imbalance, while providing an accurate, accessible environmental monitoring tool. Contributions of this research include (1) the first deployment of ISPU Jakarta 2024 in a web system, and (2) a measured performance comparison between GNB and KNN.
Implementation of the SAW Method for Mobile Phone Selection Recommendations at Holida Seluler Store Achmad Faiq Mu'afi; M Ghofar Rohman; Moh Rosidi Zamroni
Generation Journal Vol 10 No 1 (2026): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/gj.v10i1.26505

Abstract

Public demand for mobile phones continues to increase as mobile phones evolve as tools for communication, work, entertainment, and access to digital information. With so many products with varying specifications to choose from, consumers often find it difficult to determine which mobile phone suits their needs. Holida Seluler, a store that sells various types of mobile phones, still uses a manual approach in providing recommendations to customers, which can potentially result in inaccurate decisions. This study aims to develop a website using the Simple Additive Weighting (SAW) method to assist customers in determining the best mobile phone, as well as to design a system capable of presenting objective calculation results based on predetermined criteria weights that can be directly applied in the recommendation process. The data used consists of 50 mobile phone products available in stores, with seven main criteria, namely: price, RAM, internal memory, camera, battery capacity, screen, and refresh rate. This system was built using the PHP programming language and MySQL database. The implementation results show that the system can objectively rank mobile phones based on user preferences, with the A45 alternative as the best choice, obtaining the highest score of 0.9100. This system is capable of providing fast, accurate, and data-driven recommendations, thereby increasing service effectiveness and enhancing the customer experience in choosing the right product
Co-Authors Achmad Faiq Mu'afi M. Ghofar Rohman Sugeng Dwi Budi Priantoro