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All Journal Pendidikan Matematika Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL PENDIDIKAN TAMBUSAI Health Information : Jurnal Penelitian Jurnal Teknologi Dan Sistem Informasi Bisnis JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Al-Madaris Jurnal Pendidikan dan Studi Keislaman Lentera Perawat Jurnal Hasi Penelitian Dan Pengkajian Ilmiah Eksakta - JPPIE Jurnal Sains Informatika Terapan (JSIT) Knowbase : International Journal of Knowledge in Database Promotor: Jurnal Mahasiswa Kesehatan Masyarakat Jurnal Akademi Akuntansi Indonesia Padang Jurnal Teknik dan teknologi tepat guna Ameena Journal Jurnal Online Skripsi Manajemen Rekayasa Konstruksi (JOS-MRK) Journal of Islamic Education and Law
Suci Wahyuni
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Expert System Diagnosing Gastric Disease Using Hybrid Method Yenila, Firna; Wahyuni, Suci
Knowbase : International Journal of Knowledge in Database Vol. 2 No. 1 (2022): June 2022
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/ijokid.v2i1.5662

Abstract

The gastric is a vital organ that must be maintained by maintaining a balanced life. The lack of time to discuss with patients, the causes of stomach disease is frequently overlooked. Need a new way to consult with patients without seeing the time. Expert consul is an application based on knowledge such as an expert system. This research was proposed to provide education to system users who have problems with the stomach. So that treatment can be obtained quickly and the stomach's condition can be better. This research includes a system designed by incorporating an expert's expertise into a system by combining the forward chaining method by describing the conditions experienced by patients in the form of sequential questions and the certainty of factors that provide some of the patient's belief in experiencing these conditions, which are used as desires in decision making. The result of the expert system using the hybrid method obtained consultation results with a 76 % certainty level, indicating that the patient was quite certain of having the disease that was conveyed in accordance with the knowledge that had been adopted by the expert so that the patient received the right therapy early before further consultation with experts. Lambung merupakan organ vital yang harus dijaga dengan menjaga hidup seimbang. Singkatnya waktu untuk berdiskusi dengan pasien menyebabkan penyakit lambung sering terabaikan. Dibutuhkan cara baru untuk berkonsultasi dengan pasien tanpa melihat waktu konsultasi pakar berupa sebuah aplikasi berbasis pengetahuan seperti system pakar. Penelitian ini diajukan untuk memberikan edukasi kepada pengguna system yang memiliki masalah dengan lambung berupa informasi persentase menderita penyakit tersebut. Sehingga penanganan cepat didapatkan dan kondisi lambung bisa kembali seperti sediakala. Penelitian ini mengusung aplikasi system pakar yang dirancang dengan menyadurkan kepakaran seorang ahli kedalam sebuah system dengan menggabungkan metode forward chaining dengan memaparkan kondisi yang dialami oleh pasien dalam bentuk pertanyaan secara berurutan dan certainty factor yang memberikan persentase tingkat keyakinan pasien mengalami kondisi tersebut yang dijadikan acuan dalam pengambilan keputusan. Hasil yang didapatkan dalam system pakar yang melakukan pengujian terhadap metode hybrid tersebut didapatkan hasil konsultasi dengan tingkat kepastian 76% yang menyatakan bahwa pasien dinyatakan cukup yakin mengidap penyakit yang disampaikan sesuai dengan pengetahuan yang sudah disadurkan oleh pakar, sehingga pasien mendapatkan terapi yang tepat secara dini sebelum berkonsultasi lanjut dengan pakar.
PENERAPAN TEOREMA BAYES PADA SISTEM PAKAR DIAGNOSA GASTROINTESTINAL Wahyuni, Suci; Wiyandra, Yogi; Zain, Ruri Hartika; Kurnia, Hezy; Yenila, Firna
Journal of Information System Management (JOISM) Vol. 5 No. 2 (2024): Januari
Publisher : Universitas Amikom Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24076/joism.2024v5i2.1396

Abstract

Gastrointestinal merupakan penyakit yang disebabkan oleh permaslaahan pada bagian pencernaan yang memiliki fungsi yang tidak maksimal. Hal tersebut terjadi disebabkan karena proses penyerapan makanan dan nutrisi menjadi tidak seimbang. Sistem gastrointestinal melibatkan semua organ dalam dari mulut sampai anus. Pentingnya pemahaman tentang permasalahan gastrointestinal perlu disosialisasikan untuk memberikan edukasi kepada Masyarakat mengenai kondisi tersebut. Salah satu alasan dalam melakukan penelitian ini adalah memberikan informasi berbasis pengetahuan melalui aplikasi yang disampaikan oleh pakar dalam memberikan edukasi kepada Masyarakat mengenai gastrointestinal. Penelitian ini dilakukan dengan menggunakan aplikasi berbasis online berupa sistem pakar dengan mengusung metode teorema bayes yang mampu menghubungkan tingkat keyakinan user (prior) kepada keyakinan baru (posterior) setelah adanya suatu observasi baru (evidence) berdasarkan kemungkinan tertentu. Hasil penelitian ini terhadap ujicoba salah satu rule yang diberikan memberikan nilai keyakinan 32.04% sehingga pengujian tersebut memberikan nilai sesuai dengan ketentuan yang telah ditetapkan oleh pakar.
Smart Health Monitoring: Analisis Suhu Tubuh Dan Respirasi Menggunakan Kamera Termal Wahyuni, Suci; Yenila, Firna; Wiyandra, Yogi
Jurnal Sains Informatika Terapan Vol. 4 No. 3 (2025): Jurnal Sains Informatika Terapan (Oktober, 2025)
Publisher : Riset Sinergi Indonesia (RISINDO)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62357/jsit.v4i3.842

Abstract

The advancement of digital technology and artificial intelligence has opened vast opportunities for intelligent health monitoring systems that operate automatically, in real time, and without physical contact. This study aims to develop a system for detecting human body temperature and respiratory patterns using an infrared thermal camera based on digital image processing and machine learning. The research method involves thermal data acquisition on facial areas (forehead, nose, and mouth), image preprocessing using two-point temperature calibration and Gaussian filtering for noise reduction, and segmentation of the respiratory region using the adaptive thresholding method. Feature extraction is performed by analyzing temperature variations in the nose and mouth regions as thermal signals, which are converted into the frequency domain using the Fast Fourier Transform (FFT) algorithm to determine the respiration rate. Classification is carried out using the Support Vector Machine (SVM) algorithm to distinguish three physiological conditions: normal, fever, and respiratory disorder. The dataset consists of 550 thermal images, divided into 385 images (70%) for training and 165 images (30%) for testing. Experimental results show that the system achieves an accuracy of 98.32%, with an estimated forehead temperature of 145.23°C (a relative value from initial calibration) and a respiration rate of 6.6 bpm, indicating the subject’s condition as fever. This study demonstrates that the combination of thermal image processing, FFT algorithms, and SVM classification is effective for non-invasive, high-precision, and efficient health monitoring systems. The proposed system has the potential to support the development of the Internet of Medical Things (IoMT) for safe, accurate, and adaptive remote health monitoring in response to patients’ physiological changes
Co-Authors Andre Utama Saputra Bancin, Anggina Dodi Guswandi Hadi Syahputra Hafizh, M Hafizh, M. Harahap, Reni Agustina Husna, Annisa ul Kurnia, Hezy Lubis, Arifin Shaleh Nanda, Meutia Nguyen, Thanh Novita, Triana Putri, Hikmathine Osella Rahmi Rahmi RANIDA ARSI Reinita Reinita Rina Asmeri, Rina Ruri Hartika Zain Subkhan, Muhammad Fajar Syamsiar, Syamsiar Tumanggor, Suro Rahmadhona Wiyandra, Yogi Yani, Meri Yenila, Firna Yulinda Ariyani Zahra, Nabila Isma