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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Journal of Education Technology and Information System
Mochamad Nizar Palefi Ma’ady
Telkom University
Computer Science & IT Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Library & Information Science

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IoT-based flood disaster early detection system using hybrid fuzzy logic and neural networks Muhammad Adib Kamali; Mochamad Nizar Palefi Ma’ady
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 4: August 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i4.25868

Abstract

A flood stands as one of the most common natural occurrences, often resulting in substantial financial losses to property and possessions, as well as affecting human lives adversely. Implementing measures to prevent such floods becomes crucial, offering inhabitants ample time to evacuate vulnerable areas before flood events occur. In addressing the flood issue, numerous scholars have put forth various solutions, such as the development of fuzzy system models and the es- tablishment of suitable infrastructure. However, when applying a fuzzy system, it often results in a loss of interpretability of the fuzzy rules. To address this issue effectively, we propose to reframe the optimization problem by incorpo- rating stage costs alongside the terminal cost. Results show the proposed model called hybrid fuzzy logic and neural networks (NNs) can mitigate the loss of interpretability. Results also show that the proposed method was employed in a flood early detection system aligned with integrating into Twitter social me- dia. The proposed concepts are validated through case studies, showcasing their effectiveness in tasks such as XOR-classification problems.
Implementation of SVM and GLDA for Gap Analysis on Mobile JKN Balqis Nur Aura Shaviradilla; I Kadek Dwi Nuryana; Mochamad Nizar Palefi Ma’ady
Journal of Education Technology and Information System Vol. 2 No. 02 (2026): Journal of Education Technology and Information System (JETIS)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jetis.v2i02.43505

Abstract

This study aims to analyze user perceptions of the Mobile JKN application developed by BPJS Kesehatan through sentiment analysis, topic modeling, and service quality gap analysis (SERVQUAL). Sentiment analysis was conducted using the Support Vector Machine (SVM) algorithm with linear and RBF kernels. The classification results, based on an 80:20 data split, indicate that the majority of user reviews express negative sentiment—2,784 reviews using the linear kernel and 2,847 using the RBF kernel—followed by positive and neutral sentiments. These findings suggest a general dissatisfaction among users regarding the application’s performance. Topic modeling was performed using the Guided Latent Dirichlet Allocation (GLDA) method, successfully grouping reviews into five main topics aligned with the SERVQUAL dimensions: tangibles, assurance, empathy, reliability, and responsiveness. The empathy topic appeared most frequently, while responsiveness was the least represented. The GLDA model achieved a coherence score of 0.64 and a UMass score of -1.99, indicating the model’s interpretability and consistency. Finally, the dimension-by-dimension gap analysis revealed that the assurance dimension had the smallest gap (-0.06), while the reliability dimension had the largest gap (-0.74). The overall SERVQUAL gap score was 0.11, highlighting a notable disparity between user expectations and their actual experiences. These results underline the need for targeted improvements in several service aspects of the Mobile JKN application.
Co-Authors Balqis Nur Aura Shaviradilla I Kadek Dwi Nuryana, I Kadek Dwi Muhammad Adib Kamali