Article Per Year (5 Year)
p-Index From 2021 - 2026
7.687
P-Index
This Author published in this journals
All Journal Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Teknovasi : Jurnal Teknik dan Inovasi Mesin Otomotif, Komputer, Industri dan Elektronika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Informatika Kaputama (JIK) Jurnal Informasi dan Teknologi Vocatech : Vocational Education and Technology Journal JTIK (Jurnal Teknik Informatika Kaputama) JOURNAL OF INFORMATICS AND COMPUTER SCIENCE G-Tech : Jurnal Teknologi Terapan Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Jurnal Pengabdian kepada Masyarakat Nusantara JINAV: Journal of Information and Visualization International Journal of Engineering, Science and Information Technology MALLOMO: Journal of Community Service Journal of Renewable Energy, Electrical, and Computer Engineering Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Teknologi Terapan and Sains 4.0 Jurnal Pengabdian Masyarakat Bangsa MEUSEURAYA : JURNAL PENGABDIAN MASYARAKAT Jurnal Informatika: Jurnal Pengembangan IT Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS)
Yesy Afrillia
Universitas Malikussaleh
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

Published : 58 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 58 Documents
Search

 1   2   3   4   5 
Expert System for Diagnosing Dengue Fever with Comparison of Naïve Bayes and Dempster Shafer Methods Susanti, Neli; Nurdin, Nurdin; Afrillia, Yesy
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.691

Abstract

An expert system for diagnosing dengue fever (DF) using a comparison of the Naive Bayes and Dempster Shafer methods aims to provide a solution to assist medical personnel in diagnosing this disease. Dengue fever is a disease caused by the dengue virus infection through the bite of Aedes mosquitoes. It has symptoms similar to other diseases and requires rapid and accurate diagnosis. The Naive Bayes and Dempster Shafer methods were chosen because both have different approaches to handling uncertainty and imprecise information. The Naive Bayes method is a probability-based classification that assumes independence between features. Meanwhile, Dempster Shafer is an approach to handling uncertainty. Therefore, comparing Naive Bayes and Dempster Shafer allows for classification with structured and fairly straightforward data, offering accuracy and flexibility in dealing with uncertainty. Applying this expert system with these methods can help in the faster and more accurate diagnosis of DF and provide better recommendations in situations where the available data is incomplete or ambiguous. From the test data calculations, the two methods show that the Naive Bayes method has a higher percentage value of 93%, while Dempster Shafer has 86%.
Application of K-Medoids Clustering Method on Disease Clustering Based on Patient Medical Records Fatika, Dian; Bustami, Bustami; Afrillia, Yesy
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.679

Abstract

Dr. Fauziah Bireuen Regional General Hospital (RSUD) faces daily challenges in managing the ever-increasing medical record data. Currently, the medical record data only consists of reports containing information on the number of patients and their diseases, which are then archived without further processing to generate valuable information. This research aims to cluster diseases based on patient medical records using the K-Medoids Clustering method, thereby providing information on the patterns of disease spread in various regions of the Bireuen Regency. The data used are patient medical records from RSUD Dr. Fauziah Bireuen from 2021–2023, focusing on five common diseases: stroke, hypertension, schizophrenia, dyspepsia, and pneumonia. We conducted Clustering in 17 sub-districts in Bireuen Regency using the K-Medoids method and determined the optimal number of clusters using the Elbow method. The research results show that the K-Medoids method successfully grouped each disease into 3 clusters: high, medium, and low. The results showed that the K-Medoids method successfully grouped each disease into 3 clusters: high, medium, and low. The cluster distribution for stroke disease consists of 7 sub-districts in the high cluster, 7 in the medium, and 3 in the low. Hypertension disease consists of 6 sub-districts in the high cluster, 3 in the medium, and 8 in the low. Schizophrenia disease comprises seven sub-districts in the high cluster, 8 in the medium, and 2 in the low. Dyspepsia disease includes six sub-districts in the high cluster, 2 in the medium, and 9 in the low. Meanwhile, pneumonia disease consists of 8 sub-districts in the high cluster, 5 in the medium, and 4 in the low.
Pelatihan Pembuatan Media Pembelajaran Online dan Perakitan Komputer Pada Sekolah di Desa Paloh Lada Kecamatan Dewantara Bustami, Bustami; Muhammad, Muhammad; Yunizar, Zara; Rosnita, Lidya; Meiyanti, Rini; Afrillia, Yesy; Hafidh Rafif, Teuku Muhammad; Harahap, Ilham Taruna
MEUSEURAYA - Jurnal Pengabdian Masyarakat Vol.1 No.2 (Desember 2022)
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat STAIN Teungku Dirundeng Meulaboh

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (419.218 KB) | DOI: 10.47498/meuseuraya.v1i2.1436

Abstract

Pesatnya perkembangan teknologi informasi saat ini secara tidak langsung juga “memaksa” kita untuk dapat mengikuti perkembangannya, bukan hanya bagi kita yang memang bergerak di bidang IT, namun juga bagi kita yang bergerak disemua bidang, salah satunya di bidang Pendidikan. Teknologi informasi menjadi kebutuhan primer bagi kita yang membutuhkan efisiensi dalam berkegiatan. Guru dan siswa juga merasakan langsung bagaimana teknologi berperan dalam kegiatan Pendidikan, pembelajaran secara daring di masa covid menjadi puncak dari pemanfaatan teknologi didunia Pendidikan. Salah satu point penting dari kegiatan pembelajaran daring adalah pemanfaatan media pembelajaran daring, misalnya google classroom. Kegiatan pengabdian ini bertujuan untuk membantu Guru dan juga siswa/I memanfaatkan teknologi dalam kegiatan pembelajaran. Kegiatan pengabdian ini terdiri dari dua kegiatan besar, yaitu Pelatihan pembuatan media pembelajaran online yang diberikan kepada para guru dan kegiatan pelatihan perakitan komputer dan instalasi komputer kepada para murid. Kegiatan ini dilakukan pada MTsS Jabal Nur dan MTsN 2 Aceh Utara, Kecamatan Dewantara, Kab. Aceh Utara. Output dari kegiatan ini adalah Jurnal yang di submit pada Jurnal Rambieden dan Publikasi media massa. Selain itu, kegiatan ini juga memberikan pemahaman pada para guru dalam pemanfaatan media pembelajaran online dan dapat diterapkan dalam kegiatan pembelajran, sedangkan bagi siswa, kegiatan pelatihan ini memberikan pengetahuan pada mereka tentang perkembangan teknologi informasi.
Diet Recommendation Application for Diabetes Patients Using the Preference Selection Index Method Siregar, Winda Ramadhani; Yunizar, Zara; Afrillia, Yesy
Journal of Advanced Computer Knowledge and Algorithms Vol. 2 No. 2 (2025): Journal of Advanced Computer Knowledge and Algorithms - April 2025
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v2i2.17810

Abstract

Diabetes mellitus is a chronic condition characterized by elevated blood glucose levels. Effective diet management is crucial for controlling this condition and preventing serious complications. This study aims to develop a meal recommendation application for diabetes patients using the Preference Selection Index (PSI) method. The data used include user identity, health conditions, food preferences, and the nutritional content of meal menus. The PSI implementation process involves several key steps: collecting user data, normalizing nutritional values based on the minimum and maximum values in the database, adjusting the criterion weights according to the user's health conditions and food preferences, and calculating the PSI for each meal menu. The study results show that this application can provide meal recommendations that match the nutritional needs and health conditions of users. From a total of 10 user data analyzed, 50% received "Red Bean Soup with Vegetables" as the best menu, 30% received "Grilled Chicken Breast with Vegetables," and 10% each received "Grilled Chicken with Green Beans" and "Quinoa Salad with Avocado." The conclusion of this study is that the PSI method is effective in helping diabetes patients select an optimal diet, which can assist in better managing their condition and improving their quality of life. Suggestions for future research include increasing the variability of nutritional data, integrating with wearable technology, and developing reminder and education features.
Classification of Nutritional Status of Pregnant Women at Risk of Stunting in Prospective Babies Using the Support Vector Machine (SVM) Algorithm Afrillia, Yesy; Fadlisyah, Fadlisyah; Asmi, Nurul Annisa
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 6, No 1 (2025)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v6i1.22393

Abstract

Stunting describes the existence of chronic nutritional problems, influenced by the condition of mothers/mothers-to-be, fetal period, and infants/toddlers, including diseases suffered during toddlerhood. According to a WHO report quoted from Riskesdas, in 2018 the stunting target in Indonesia was 20%, but in 2013 the stunting rate was 37.2%, but in 2018 there was a decrease to 30.8%. However, the stunting rate in Indonesia is still very high and far from what is targeted by WHO. The method with the best level of accuracy for classification in this study is SVM. This study uses the Support Vector Machine (SVM) method as criteria and attributes which take benchmarks in pregnant women with attributes as a reference including gestational age, maternal weight, blood pressure, and pregnancy problems. The reason for taking benchmarks in pregnant women is because in the first 1000 days of a baby's life determines the baby's nutrition. The first 1000 days of life or 1000 HPK is a critical period in the growth and development of children starting from the beginning of pregnancy (270 days) to 2 years old (730 days). Data was obtained from the Tanah Luas Health Center totaling 684 data on pregnant women. The process of manual calculation is data normalization, kernelization, calculating the alpha and alpha delta Ei values, calculating weights, calculating bias values, and calculating f(x) values. In this study, the dataset totaled 680 data with 544 training data and 136 test data with the criteria of gestational age, pregnant woman's weight, blood pressure, and pregnancy problems. The accuracy obtained was 38.90 %. The variables that have the most influence on this classification are 3, namely the weight of pregnant women, blood pressure, and complaints experienced in pregnant women.
Pemilihan Tempat Kost Menggunakan Metode Multi Attribute Utility Theory Dan Algoritma A* Yesy Afrillia; Wahyu Fuadi; Ayu Indah Lestari
Jurnal Teknik Informatika dan Sistem Informasi Vol 9 No 2 (2023): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v9i2.6279

Abstract

Overseas students usually have difficulty finding boarding houses around Malikussaleh University. To get information on boarding houses, they have to search manually, so the time needed to find a boarding house can be very long. The purpose of this research is to produce a Geographic Information System that can make it easier for students to find information about the location of boarding houses, provide recommendations in selecting boarding houses, and find the shortest distance for each boarding house to campus. By using the MAUT method combined with an algorithm A* can provide recommendations in selecting boarding houses and provide the shortest distance from the location of each boarding house to the Campus. The results of this study resulted in recommendations for boarding houses based on the results of ranking using the MAUT method. The boarding houses with the top three rankings are 4G Boarding House, Ceiza Boarding House, and Hj Boarding House. Madriah. With distance of 0.75 km, 2.01 km and 1.38 km. With an algorithmA* to find the closest route it can be concluded that the MAUT method and algorithm A* is a combination that can be used in evaluating boarding houses and solutions in searching for the shortest distance.
ALAT PEMISAH WARNA OBJEK BERBASIS MIKROKONTROLER Afrillia, Yesy
Jurnal Teknologi Terapan and Sains 4.0 Vol 1 No 2 (2020): Jurnal Teknologi Terapan & Sains
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/tts.v1i2.3254

Abstract

Pembuatan alat pemisah warna objek yang dapat memindahkan objek warna dari satu  tempat  ke  tempat lain dengan warna yang telah disesuaikan dari rangkaian tersebut  apabila objek  yang berwarna di letakkan pada corong kemudian turun mengenai sensor TCS3200,  maka  secara otomatis akan memberikan tegangan input ke mikrokontroler, sehingga mikrokontroler akan bekerja dan membaca program yang tersimpan, kemudian  mikrokontroler  akan  memberikan  output  tegangan ke motor servo untuk  menggerakan  objek warna ,dan menjalankan program secara otomatis dimana servo akan  memindahkan objek warna dari tempat sensor ke tempat wadah yang sesuai dengan warna yang  sama  yang  telah di sediakan, alat yang akan dibuat menggunakan mikrokontroler sebagai otak  pengendalinya. Struktur serta antar muka mikrokontroler  yang  sederhana  memberikan  kemudahaan  pengguna  dalam  memahaminya, dan dalam kaitannya dengan penyortiran ini  akan  dibuat  secara  sistematis  dan teliti dimana akan menyortir barang berupa objek warna yang pengendaliannya dan pendeteksian melalui sensor secara otomatis.Kata Kunci : Sensor Warna TCS3200, Mikrokontroler, Motor Servo
PEMBANGUNAN GEDUNG FAKULTAS AKSI-ADB 2020 YANG MENGIMPLEMENTASIKAN TOILET BERBASIS GENDER DAN PENTINGNYA PERLINDUNGAN TENAGA KERJA DI LINGKUNGAN UNIVERSITAS MALIKUSSALEH Fithra, Herman; Sofyan, Sofyan; Sarana, David; Mukhlis, Mukhlis; Siska, Deassy; Afrillia, Yesy
Jurnal Teknologi Terapan and Sains 4.0 Vol 3 No 2 (2022): Jurnal Teknologi Terapan & Sains
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/tts.v3i2.8274

Abstract

Permasalahan ketidakadilan gender bisa ditemukan dalam beragam hal dalam keseharian, salah satunya adalah toilet. Di berbagai tempat hiburan maupun ruang publik lain seperti sekolah dan stasiun, jumlah toilet untuk perempuan bisa dibilang kurang memadai. Universitas Malikussaleh melalui proyek AKSI ADB membangun 7 gedung Fakultas masing-masing 2 lantai dengan penempatan Toilet yang sudah memasukkan unsur gender didalamnya. Permasalahan toilet perempuan ini tidak lepas dari pandangan yang responsive gender yang saat ini sedang marak di masyarakat, termasuk di kalangan ilmuwan dan akademisi. Dalam tahap awal, pandangan ini mengesampingkan fakta biologis bahwa perempuan mempunyai kebutuhan unik sehubungan dengan pengalaman mandi dan bersih menstruasi mereka. Pengalaman ini sangat berpengaruh terhadap waktu yang perempuan habiskan di toilet. Sebuah studi dari Science Daily tahun 2017 pernah menyebutkan, perempuan menghabiskan 50 persen waktu lebih lama dari laki-laki di toilet. Hal ini bisa ditambah faktor sedikitnya jumlah bilik toilet sehingga perempuan mesti mengantre lebih lama di sana. Melalui Peraturan Menteri kesehatan Republik Indonesia nomor 48 tahun 2016 tentang standar keselamatan dan kesehatan kerja perkantoran, Universitas Malikussaleh membangun Toilet yang responsive gender dengan rasio perbandingan toilet 1:25 untuk perempuan dan 1:40 untuk laki-laki yang ada di dalamnya.Keywords: Gender, Rasio Toilet, Responsive
Prediksi Kesehatan Mental Remaja Berdasarkan Faktor Lingkungan Sekolah Menggunakan Machine Learning Rahma, Mutiara; Fikry, Muhammad; Afrillia, Yesy
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 2 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i2.8556

Abstract

Adolescent mental health is a crucial aspect that affects academic performance, social relationships, and overall well-being. The school environment is one of the primary factors influencing adolescents' mental conditions. This study aims to predict adolescent mental health levels based on school environmental factors using the Random Forest algorithm. Data were collected from 229 adolescents in Lhokseumawe and categorized into four classes of mental health conditions. The research methodology includes data preprocessing, model training, and performance evaluation using accuracy and other relevant metrics. The results show that the model achieved an accuracy of 80.43%, with the highest F1-score of 0.90 in the category indicating no mental health issues. Feature importance analysis identified loneliness, feelings of worthlessness, academic pressure, and home-related stress as the most influential factors in the predictions. While the model effectively classified most data, some misclassifications occurred at certain mental health levels. Thus, the Random Forest model proves to be an effective predictive tool for detecting potential adolescent mental health issues. The findings of this study can serve as a reference for educational institutions in designing more targeted intervention strategies to support adolescent mental well-being.
Public Facility Recommendation System in Subulussalam City Using Fuzzy C-Means Algorithm Berutu, Indah Fachlira; Dinata, Rozzi Kesuma; Afrillia, Yesy
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.873

Abstract

Subulussalam City, as one of the autonomous regions in Aceh Province, Indonesia, has excellent potential to develop public facilities to improve the quality of life for its residents. Recommendation systems have become an effective solution in helping users find relevant information based on the preferences and needs of the community. This research focuses on developing a recommendation system using the Fuzzy C-Means algorithm. This algorithm is one of the clustering methods capable of handling uncertainty and ambiguity in data. This study aims to develop and analyze a public facility recommendation system in Subulussalam City using the Fuzzy C-Means algorithm. The dataset in this study was obtained from the Youth, Sports, and Tourism Office of Subulussalam City and the results of a research questionnaire. Regarding the names of each public facility, it provides information about the location and various forms of visitor assessments, including evaluations related to accessibility, facilities, costs, environment, and visitor experiences, using a rating scale of 1-5. Based on the testing results, the Fuzzy C-Means clustering algorithm can group facilities based on characteristics and user preferences, resulting in more personalized and relevant recommendations. The data to be clustered is divided into two categories: recommended and not recommended. The study's results using the Fuzzy C-Means algorithm show the final grouping based on the degree of membership from the last iteration of each public facility, with cluster 1 containing 31 locations and cluster 2 containing 31 locations.
Co-Authors Abadi, Sabani Abdul Hadi Abil Khairi Adek, Rizal Tjut Aldo januansyah. H Ananda Faridhatul Ulva Annas, Muhammad Aqmal, Jamalul Arif, Abdul Halim Arif, M. Arif Saputra Arifa, Cut Hilma Asmi, Nurul Annisa Asrianda Asrianda Asrifan, Andi Asrillah Asrillah Aswandi, Sakti Ayu Indah Lestari Berutu, Indah Fachlira Bustami Bustami Cut Agusniar Dahlan Abdullah Dasril Dasril David Sarana Deassy Siska EDI YUSUF, EDI Effan Fahrizal Ekamaida, Ekamaida Elvina Mutiara Vina Eri Saputra eva darnila, eva darnila Fadlisyah Fadlisyah Fadlisyah Faiz Fadhilla Fakhruddin Ahmad Nasution Farhan Dika Fatika, Dian Fidyati, Fidyati Fikria, Putri Fuadi, Wahyu Gilang Ramadhan Purba Hafidh Rafif, Teuku Muhammad Harahap, Ilham Taruna Herman Fithra Hidayat, Amam Taufiq ilham - sahputra Ilsa Hidayat Intan Putri Dinanti Jamalul Aqmal Julianansa, Ririn Kasihan Muhammad Fajar Kautsar, Al Khairuni Khairuni Lidya Rosnita Mahadika Luqman Mahesa Reglisalo Muhammad Fikry Muhammad Ikhwanus Muhammad Iqbal Muhammad Muhammad Muhammad Yusuf Mukhlis Mukhlis Mukti Qamal Muzaffar Rigayatsyah Muzaffar Rigayatsyah NELI SUSANTI, NELI Nurdin Nurdin Nurqamarina Rahma, Mutiara Rahmawati, Rahmawati Rini Meiyanti Risawandi, Risawandi Riza, Saiful Rizal Rizal Rizal Rizal S.Si., M.IT, Rizal Rizky Putra Fhonna Rozzi Kesuma Dinata Safriand, Safriand Sari, Rika Yulia Sayed Fachrurrazi Selian, Riko Ardiansyah Siregar, Winda Ramadhani Sofyan Sofyan Suci Ramadani Sujacka Retno Teuku M. Arief Afwan Tursina Dewi Uliana, Lisa Ulva Ilyatin Veri Ilhadi Wahyu Fuadi Wahyu Fuadi Wardana, Ade Bagus Widari, Liz Ayu Winda Yanti Yusril Zahratul Fitri, Zahratul Zara Yunizar Zuhra, Elviza Zulfan