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All Journal Jurnal Sains dan Teknologi JAIS (Journal of Applied Intelligent System) Sinkron : Jurnal dan Penelitian Teknik Informatika VOLT : Jurnal Ilmiah Pendidikan Teknik Elektro JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURTEKSI EXPLORE JOISIE (Journal Of Information Systems And Informatics Engineering) Jurnal Teknologi Jurnal Teknologi Informasi dan Pendidikan Jurnal Informasi dan Teknologi JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) International Journal of Advances in Data and Information Systems Jurnal Infortech Journal of Computer Scine and Information Technology Jurnal Pustaka Data : Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer Jurnal Ekonomika Dan Bisnis Jurnal Sains Informatika Terapan (JSIT) EXPLORE Jurnal Komtekinfo Knowbase : International Journal of Knowledge in Database Jurnal Teknologi SATIN - Sains dan Teknologi Informasi Jurnal Pustaka Robot Sister
Firna Yenila
Universitas Putra Indonesia YPTK Padang
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering

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Model Analisis Machine Learning dengan Pendekatan Deep Learning dalam Penentuan Kolektabilitas Yenila, Firna; Marfalino, Hari; Defit , Sarjon
JST (Jurnal Sains dan Teknologi) Vol. 12 No. 2 (2023): July
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jstundiksha.v12i2.54035

Abstract

Penelitian ini bertujuan untuk melakukan proses prediksi dan klasifikasi dalam pemberian status pinjaman dengan mengembangkan sebuah model analisis menggunakan Machine Learning (ML). Pembelajaran ML menggunakan pendekatan Deep Learning (DL) dengan beberapa metode diantaranya K-Means Cluster, K-Nearest Neighbor (K-NN) dan Decision Tree (DT). Metode K-Means mampu melakukan clusterisasi terhadap pengelompokan data nasabah. Kinerja KNN juga dapat berkontribusi untuk memberikan hasil prediksi yang tepat dan akurat. Demikian juga dengan performa DT yang mampu melakukan klasifikasi dengan menghasilkan knowladge based dalam penentuan status pinjaman. Adapun variabel analisis yakni usia, status perkawinan, jumlah tanggungan, status tempat tinggal, pendapatan. Hasil penelitian ini menyajikan bahwa keluaran prediksi K-NN memberikan ketepatan dengan akurasi sebesar 90%. Hasil DT juga telah mampu menyajikan knowladge based dalam bentuk pohon keputusan status pinjaman. Dengan hasil tersebut maka penelitian ini secara keseluruhan dapat memberikan kontribusi bagi pihak UPK dalam proses manajemen terkhusus dalam penentuan status peminjaman. Penelitian ini perlu dilakukan untuk memberikan kemudahan dalam memberikan kredit yang tepat sesuai dengan ketentuan yang telah ditetapkan.
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.
Identification and Classification of Cracks in Traditional Pottery from West Sumatra Using Digital Image Processing Mahessya, Raja Ayu; Yenila, Firna
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.12156

Abstract

Cracks in traditional West Sumatran pottery are a major challenge in preserving this cultural heritage. With age and the manual manufacturing process, pottery becomes highly susceptible to physical damage, particularly cracks on the surface and internal structure. These cracks not only affect the functional and aesthetic value but also reduce the cultural and economic value of the pottery. Therefore, an accurate early identification system is crucial to ensure the survival and preservation of this culture. This study developed a digital image processing-based system to detect and classify cracks in traditional pottery. The system integrates image preprocessing, including cropping, resizing, grayscale conversion, contrast stretching, and histogram equalization to improve image quality and highlight thin and irregular cracks. Image segmentation was performed using the Multi-Threshold Otsu method to separate cracks from the background, while classification was performed using a convolutional neural network (CNN). Experimental results show that this system is able to achieve an accuracy of 94.8%, precision of 93.5%, recall of 92.3%, and F1-score of 92.9%, indicating the system's ability to accurately detect cracks. Comparisons with other segmentation and classification methods are needed to provide a more comprehensive picture of the effectiveness of this approach. The implementation of this system is expected to support the preservation of traditional Minangkabau pottery through digitalization, provide an ornament database that can be accessed by researchers, artists, and the general public, and assist in more efficient cultural documentation and archiving.
A Multilevel Image Processing Approach for Minangkabau Ornament Detection Using CLAHE, Multi Threshold Otsu, and CNN Wahyuni, Suci; Wiyandra, Yogi; Yenila, Firna
International Journal of Advances in Data and Information Systems Vol. 7 No. 1 (2026): April 2026 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v7i1.1520

Abstract

Traditional Minangkabau ornaments such as pucuak rabuang, itiak pulang patang, kaluak paku, and rabuang sanjo represent a form of visual cultural heritage with high aesthetic and philosophical value. However, the digital documentation and preservation of these ornaments still face significant challenges, particularly due to variations in media, fine surface textures, uneven illumination, and complex image backgrounds. These conditions complicate the separation of ornament motifs from the background and consequently affect the accuracy of identification and classification processes. This study aims to develop an image processing approach for the detection and identification of Minangkabau ornaments through image quality enhancement and multi-level segmentation. The proposed method begins with a preprocessing stage that includes motif area cropping, image size normalization, noise reduction through filtering, contrast stretching, and Contrast Limited Adaptive Histogram Equalization (CLAHE) to enhance local contrast. Subsequently, segmentation is performed using the Multi-Threshold Otsu method to divide the image into multiple intensity classes, enabling a more detailed separation of ornament structures. The segmentation results are evaluated using morphological analysis and further tested using a Convolutional Neural Network (CNN) to assess classification performance. Experiments were conducted on a dataset of 1,024 images, with a training–testing split of 70% and 30%, respectively. The experimental results demonstrate that the proposed approach produces representative motif segmentation and achieves a classification accuracy of 99.67%. These findings indicate that the integration of systematic preprocessing, multi-threshold segmentation, and CNN-based classification is effective in supporting the digital preservation of Minangkabau ornaments.
Gastric Diagnosis Expert System using the Fuzzy Mamdani Method Rozizah Dwi Gusni; Eva Rianti; Firna Yenila
Journal of Computer Scine and Information Technology Volume 9 Issue 4 (2023): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v9i4.87

Abstract

The stomach is one of the important digestive organs in humans. Gastric disease is inflammation of the stomach lining caused by microorganisms, this disease is caused more by Helycobacterpylori bacteria, apart from being caused by bacteria, stomach disease can also be caused by irregular lifestyle and eating patterns. Diseases that attack the stomach are still considered trivial by the general public, so not many people know about stomach diseases and the symptoms that exist. This is what causes people to be reluctant to see a doctor when they suffer from pain that attacks the stomach. When a disease attacks the stomach, people only use experience or intuition to cure it, so it is not treated properly. By using an expert system, patients can save time going to the hospital and can improve service to patients. The results of the Mamdani fuzzy logic calculations require a report on the possibility of stomach disease suffered by the user/patient, examples of possibilities are small, somewhat large and large based on the highest value results. It is hoped that with this system, it will be easier for patients to diagnose gastric diseases to carry out prevention and early diagnosis and treatment.
Certainty Factor Method for an Expert System for Orthopedic Disease Diagnosis Intan Savilla; Eva Rianti; Firna Yenila
Journal of Computer Scine and Information Technology Volume 9 Issue 4 (2023): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v9i4.88

Abstract

Health is an important thing in human survival, including bone disease. Some people think that bones are passive, dead tissue, but they are not. Bones and skeleton are a very important part of orthopedics. Bones are not only a framework that strengthens the body but are also part of the structure of joints, as protection for the body, where the ends of muscles are attached. One of the diseases that is widely felt in society is bone disease. Bone disease is a condition that damages the skeleton and makes bones weak and susceptible to fractures. The high rate of diseases that attack the bones is caused by the conditions and behavior of society, such as stress, lack of exercise, wrong diet. Another cause is also ignorance and lack of knowledge about bone disease itself. By using an expert system, patients can save time going to the hospital, because the system replaces experts in their field, especially chiropractors. The method that will be used in this research is the Certainty Factor Method. The results obtained later are diagnostic results based on the symptoms entered and issued in the form of decisions and percentages. The diagnosis results identified Cervical Spondylosis (Nerve Pain) with a confidence level of 89.60%. It is hoped that this expert system will make it easier for patients to diagnose bone disease and carry out initial treatment in treating the disease.
Development of a Service Quality Analysis Information System with the Importance Performance Analysis Method Riyan Saputra; Firna Yenila; Sepsa Nur Rahman
Journal of Computer Scine and Information Technology Volume 9 Issue 4 (2023): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v9i4.90

Abstract

Service is an activity where a company helps customers solve their problems. Good service quality can make customers loyal to the company. To maintain service quality, service performance is measured. The Importance Performance Analysis (IPA) method is one method that can be used to measure service performance from a customer perspective. Qanaah Carpet Shop is a business that operates in the field of goods and services. By using the IPA method, Toko Qanaah Karpet measures its service performance manually using paper media, which makes analysis ineffective and inefficient. This research aims to build an information system that can analyze service quality using the IPA method. The analysis was carried out by measuring 30 service attributes which were divided into 5 dimensions, namely: Tangible (Physical evidence), Reliability (Reliability), Responsiveness (Responsiveness), Assurance (Guarantee), and Empathy (Empathy). Data collected through a questionnaire involved 50 respondents. The results of this research show that there are 6 attributes in quadrant A, 10 attributes in quadrant B, 8 attributes in quadrant C, and 6 attributes in quadrant D. Companies can take action to maintain and improve service attributes in accordance with the recommendations from the results of this research.
Smart Health Monitoring: Analisis Suhu Tubuh Dan Respirasi Menggunakan Kamera Termal Suci Wahyuni; Firna Yenila; Yogi Wiyandra
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
Analisa Simulasi Antrian Monte Carlo menggunakan metode Multi Channel Single Phase Trisna, Novi; Mahessya, Raja Ayu; Yenila, Firna
Jurnal Pustaka Data (Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer) Vol 5 No 1 (2025): Jurnal Pustaka Data (Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitekt
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakadata.v5i1.1057

Abstract

Penelitian ini menganalisis sistem antrian pada layanan Laut Carwash menggunakan simulasi Monte Carlo berbasis model Multi-Channel Single-Phase. Hasil simulasi menunjukkan bahwa metode ini efektif dalam memberikan gambaran realistis terkait waktu tunggu dan performa pelayanan. Rata-rata waktu tunggu pelanggan dalam antrian tercatat sebesar 10,75 menit, sementara rata-rata total waktu dalam sistem mencapai 81 menit. Pendekatan Monte Carlo mampu mensimulasikan dinamika layanan secara akurat dan menjadi alat bantu untuk mengevaluasi serta merancang perbaikan sistem pelayanan. Simulasi ini juga membantu memetakan dampak perubahan operasional terhadap efisiensi layanan secara keseluruhan. Dengan demikian, metode ini sangat bermanfaat untuk mendukung pengambilan keputusan strategis dalam meningkatkan kualitas pelayanan pencucian mobil.
Co-Authors Agung Ramadhanu Arsyah Arsyah Ayu Mahessya, Raja Devi Gusmita Devia Kartika Efendi, Gustiawan Eva Rianti Febri Hadi Gema, Rima Liana Gustiawan Efendi Intan Savilla Jamhur, Annisak Izzaty Jehan Harka Khairul, Khairul Zaman Kurnia, Hezy Kurnia, Hezy Larissa Navia Rani, Larissa Marfalino, Hari Mutiana Pratiwi Novi Trisna Novrianto, Andry Permana, Randy Pradana, Taufan Rahman, Sepsa Nur Riyan Saputra Rozi, Fachrul Rozizah Dwi Gusni Ruri Hartika Zain Sarjon Defit Sovia, Rini Suci Wahyuni Suci Wahyuni Suci Wahyuni Syaiffullah, Afif Vivi Anggraini Wifra Safitri Wiyandra, Yogi Yogi Wiyandra Yuhandri Yuhandri, Yuhandri Yuliawati Yunus Yusvi Diana Zefri Yenni Zefriyenni Zefriyenni, Zefriyenni