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All Journal RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JOURNAL OF APPLIED INFORMATICS AND COMPUTING JOURNAL OF INFORMATICS AND COMPUTER SCIENCE International Journal of Engineering, Science and Information Technology Jurnal Tika Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) TECHSI - Jurnal Teknik Informatika Jurnal Teknologi Terapan and Sains 4.0 INOVTEK Polbeng - Seri Informatika Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Risawandi, Risawandi
Universitas Malikussaleh
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PENERAPAN METODE ALGORITMA SVM (SUPPORT VECTOR MACHINE) UNTUK KLASIFIKASI PENDERITA PENYAKIT GASTROESOPHAGEAL REFLUX DISEASE: APPLICATION OF SVM (SUPPORT VECTOR MACHINE) ALGORITHM METHOD FOR CLASSIFICATION OF GASTROESOPHAGEAL REFLUX DISEASE PATIENTS Teuku Ferynanda Ramadhan; Asrianda; Risawandi
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.v10i2.6466

Abstract

Gastroesophageal Reflux Disease (GERD) is a digestive disorder caused by the backflow of stomach acid into the esophagus, with symptoms that often resemble those of other conditions, making diagnosis challenging. This study aims to implement the Support Vector Machine (SVM) algorithm to develop a classification system for GERD patients based on clinical symptom data, including chest pain, swallowing disorders, regurgitation, and others. The research was conducted at Sakinah General Hospital in Lhokseumawe City using patient data from the 2020–2023 period. The classification system was designed through a series of stages including data preprocessing, normalization, and the application of a polynomial kernel in the SVM algorithm. The results demonstrate that the SVM algorithm achieved an accuracy of 82.5% and an F1-score of 58.3%, indicating a strong classification performance in distinguishing between GERD and non-GERD patients, and suggesting its potential as an effective diagnostic support tool for medical professionals.
PERAN PENTING IT TERHADAP PERKEMBANGAN DUNIA DI ERA REVOLUSI INDUSTRI 4.0 Risawandi Risawandi
Jurnal Teknologi Terapan and Sains 4.0 Vol 6 No 3 (2025): Jurnal Teknologi Terapan & Sains
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/tts.v6i3.26349

Abstract

Di dunia developer atau dunianya pengembangan system bertemu beberapa macam jabatan, ada yang menjadi project manager, desainer, konsultan, dan system analyst. Penggunaan teknologi oleh manusia diawali dengan pengubahan sumber daya alam menjadi alat-alat sederhana. Jaman sekarang yang teknologi adalah salah satu sangat dibutuhkan oleh manusia, karena sekarang banyak hal-hal yang dikaitkan dengan teknologi, dan juga sangat membantu manusia dalam segi apapun. Penelitian ini menggunakan pendekatan kuantitatif dengan metode penelitian deskriptif. Pengumpulan data dilakukan dengan metode survei dengan menggunakan instumen kuesioner yang bertujuan untuk mendapatkan gambaran secara sistematis karakteristik populasitertentu atau bidangtertentu secara faktual dan cermat. Teknologi telah memengaruhi masyarakat dan sekelilingnya dalam banyak cara. Di banyak kelompok masyarakat, teknologi telah membantu memperbaiki ekonomi (termasuk ekonomi global masa kini) dan telah memungkinkan bertambahnya kaum senggang. Banyak proses teknologi menghasilkan produk sampingan yang tidak dikehendaki yang disebut pencemar dan menguras sumber daya alam, merugikan, dan merusak Bumi dan lingkungannya. Kata Kunci : Teknologi, Global, Manusia
Implementation of an Artificial Neural Network Algorithm for Mental Illness Virtual Assistant Chatbot Development Muhammad iqbal; eva darnila; risawandi
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/wkj2ks31

Abstract

Mental health is a critical issue in modern society, yet access to psychological support remains limited. This study presents the development of a chatbot as a virtual assistant for individuals experiencing mental illness using the Artificial Neural Network (ANN) algorithm. The dataset was manually constructed and divided using an 80:20 ratio for training and testing. The ANN model employs one hidden layer with ReLU and softmax activation functions to classify user input into relevant mental health categories. The model achieved a training accuracy of 83.2% with a loss of 0.655, and a testing accuracy of 81.5%, indicating solid performance. Compared to rule-based methods, ANN provides better adaptability in recognizing diverse expressions and delivering context-aware, empathetic responses. This study also introduces a custom-built mental health dataset and integrates a crisis response module that is underexplored in previous research. The chatbot targets five categories of mental disorders: Schizophrenia, Bipolar Disorder, Depression, Anxiety, and Personality Disorders. Findings suggest that ANN-based chatbots can serve as reliable, accessible, and scalable early-stage mental health support tools.
Co-Authors Angaw, Mariance Wulan Asrianda Asrianda Asrianda Asrianda Asrul Fahmi Bustami Bustami Bustami Bustami Dahlan Abdullah Dara Maulidia Eva Darnila Eva Darnila Fadlisyah Fadlisyah Fuadi, Wahyu Furqan, Hafizul Gunarwan Gunarwan Gunarwan, Gunarwan Halimatun Sakdiah Halimatun Sakdiah, Halimatun Helmi Naluri Ira Fazira Julita, Rina Khainesya, Khainesya Lidya Rosnita Luqman Nul Hakim M. Irsan Maulana Amri Muhammad Fikry Muhammad Iqbal Muhammad Iqbal Muhammad Wahyu Pohan Mukti Qamal mulkal razali Mutammimul Ula Nurdin Nurdin Nurhaliza Bin Aras Nursanti Nursanti Nursanti Nursanti Nurul Aflah Nurul Aflah Olivia, Karina Pranidana, Abdi Mulia Rian Kelana Putra Riska Yanti RISKA YANTI, RISKA Rizal S.Si., M.IT, Rizal Rosdian Rosdian dian rosdian Rozzi Kesuma Dinata Rozzy Rozzy Safwandi Safwandi Senda, Tito Afwi Teuku Ferynanda Ramadhan Tito Afwi Senda Ulfa, Septia Mulya Wahyu Fuadi Wahyu Fuadi Yesy Afrillia Zahrah, Violita Aditya Zahratul Fitri Zainannur Nasution Zakiatul Husna