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All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING Mulia International Journal in Science and Technical TECHSI - Jurnal Teknik Informatika Jurnal Teknologi Terapan and Sains 4.0 Jurnal Malikussaleh Mengabdi INOVTEK Polbeng - Seri Informatika Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Eva Darnila
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Religion Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Social Sciences Other

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Expert System Technology in Implementation of K-Means Clustering Algorithm in Patients with Tuberculosis at Cut Meutia Hospitals North Aceh Eva Darnila; Mutammimul Ula; Mauliza; Iwan Pahendra; Ermatita; Hardi, Richki
Mulia International Journal in Science and Technical Vol 2 No 1 (2019): August
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Technology in detecting potential drop out tuberculosis (TB) in Cut Meutia hospital and Health Office plays a great role and has been very important. This is seen from the increasing number of patients who could not be cured succesfully and who do not care about TB which will have fatal consequences on their health. In addition, the main cause of the increase in the number of potential drop out TB patients is because of the lack of awareness of the community, especially the middle economic level family of the danger of TB disease as seen from the irregular treatment that they have and the continued smoking habit. In this study, an expert system was used to diagnose patients with potential Drop Out tuberculosis who were then diagnosed into the cluster of each TB patient using the K-Means algorithm. The system implementation in the expert system is that the initial symptoms include the question of whether the patient has cough with phlegm for 2-3 weeks or more (yes), has the patient been treated with TB drugs less than 1 month (no), experienced no appetite and nausea. From the results of these symptoms, there are diagnoses of New Patients, Pulmonary BTA (-) / Ro (+), with sub-acute level having moderate severity and duration, the severity can reduce the health status of the patient, the patient is eventually expected to recover and totally recovered the disease does not develop into a chronic disease. The results of this expert system would be entered into the K-Means clustering. The test results of the k-means clustering algorithm with K = 3 (C1, C2, C3). with initial centroid values of m1: C1, 5, 5, 5, 5, 5, 5 and m_2: C2, 3, 3, 3, 3, 3, with patient p1 with the value of each cluster (C1) = 6.928, ( C2) = 2.828, C3 = (4). For the closest cluster value is C2, then the BCV (Between Cluster Variation) calculation value is 19,596, and the WCV (Within cluster Variation) value is 144. Then the ratio value is 0.136. The result of the iteration -3 can be stopped because it does not experience the movement of the clusters and the clusters have been optimal. The results of this system can classify patients for each village and sub-district area so that the Hospital officials and the Health Office can directly monitor potential drop out TB patients and can facilitate the Head of Office/region in handling clustered TB patients using K-Means. Furthermore, in the coming years, it can be used as a tool in taking preventive measures.
Aplikasi Diagnosa Penyakit Tanaman Palawija dengan Forward Chaining dan Dempster Shafer Berbasis Android Mukti Qamal; Eva Darnila; Balqis Melodi
TECHSI - Jurnal Teknik Informatika Vol 13, No 1 (2021)
Publisher : Teknik Informatika Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/techsi.v13i1.2826

Abstract

Kecerdasan buatan adalah salah satu bagian dari teknologi yang membuat komputer dapat berpikir dan bertindak seperti manusia. Salah satu bagian dari kecerdasan buatan adalah sistem pakar. Pembangunan sistem pakar dapat digunakan untuk mendiagnosa penyakit pada tanaman palawija layaknya seorang pakar sehingga dapat membantu petani untuk dapat mengetahui penyakit yang diderita oleh tanamannya dengan cepat. Sistem ini dibuat dengan menggunakan UML (Unified Modelling Language) dengan mengimplementasikan mesin inferensi Forward Chaining dan Dempster Shafer yang dapat mengidentifikasi masalah dengan perhitungan yang cukup akurat dengan nilai rata-rata mencapai 72,5%. Sistem pakar ini berbasis android sehingga dalam penggunaannya lebih efisien yang dapat digunakan kapanpun dan dimanapun.
Inovasi Pengolahan, Managemen, Produksi Ikan Bandeng Presto Dalam Peningkatan Pemberdayaan Ekonomi Masyarakat Gampong Cot Girek Kandang Kota Lhokseumawe Maryana Maryana; Eva Darnila; Fatimah Fatimah; Zuraida Zuraida
Jurnal Teknologi Terapan and Sains 4.0 Vol 2, No 3 (2021): Jurnal Teknologi Terapan & Sains
Publisher : Jurnal Teknologi Terapan and Sains 4.0

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.1976/tts 4.0.v2i3.5780

Abstract

Inovasi pengolahan, managemen, produksi ikan bandeng presto sangatlah penting bagi warga gampong cot girek kandang, hal ini sangat mendukung untuk peningkatan pertumbuhan ekonomi keluarganya. Tujuan dari pengabdian adalah Untuk melatih ibu-ibu Kelompok wanita tani/ ibu rumah tangga Gampong  Cot Girek  Kandang Kecamatan Muara Dua Kota Lhokseumawe tentang pengolahan produksi Ikan Bandeng Presto berbasis Inovasi, memberikan pengetahuan tentang manajemen usaha yang baik dan benar, serta memberikan pelatihan cara pemasaran produksi menggunakan media online. Metode pelaksanaan  inovasi pengolahan ikan bandeng presto meliputi : (1) Tahapan Perencanaan Pelatihan Olahan Produk Ikan Bandeng; (2) Persiapan Tempat Pelatihan; (3) memberikan penyuluhan/penyampaian materi tentang pengolahan produk ikan bandeng dengan berbagai jenis varian inovasi yang digunakan pada ikan bandeng; (4) Perbaikan tata kelola usaha, baik produksi maupun Penerapan teknologi Vakumn Sealer; (5) pemasaran meliputi media sosial, penggunaan aplikasi android untuk group penjualan dan penjelasan manajemen kelompok untuk aspek produksi dan pemasaran. Luaran yang dihasilkan adalah (1) Adanya inovasi ikan bandeng presto dalam menciptakan peluang usaha warga gampong cot girek kota lhokseumawe; 2. Adanya manajemen (tata kelola)  dalam pengolahan ikan bandeng presto yang mempunyai standar kebersihan dan kualitas yang baik. (3) adanya tata kelola manajemen keuangan untuk warga gampong untuk memasarkan ikan bandeng presto yang sesuai dengan standarnya; (4) Dapat memberikan ilmu kepada warga gampong cot girek kandang yang dimulai dari proses pengolahan secara runtun dan terarah.
Classification of the Number of Malaria Cases in Asahan Regency Using Random Forest Application Naza Amarianda; Eva Darnila; Lidya Rosnita
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9960

Abstract

This study aims to classify the number of malaria cases in Asahan Regency using the Random Forest method. This method was chosen because it is able to handle data with many and complex variables and reduce the risk of overfitting. Data were collected from the Asahan Regency Health Office. The research stages include data collection, preprocessing, model training, and model evaluation. The dataset used consists of 568 malaria case data from 25 sub-districts. The data is divided into 80% for training and 20% for testing. Of the total data, there are 109 data 19.2% in the low category, 334 data 58.8% in the medium category, and 125 data 22.0% in the high category. This classification aims to assist in mapping the level of malaria risk in the area. In this study, several variables were used for model training, including health centers, sub-districts, age, month, and gender. The results of the analysis showed that the most influential variables were health centers 47.53%, followed by sub-districts 43.77%, age 6.07%, months 2.18%, and gender 0.45%. The Random Forest model built was evaluated using accuracy, precision, recall, and F1-Score metrics. The evaluation results showed that the model was able to classify the number of malaria cases well, with an accuracy value of 0.97. With these results, Random Forest has proven effective as a classification method in malaria cases in Asahan Regency.
Optimalisasi Blue Economy Berbasis IoT dalam Pengawasan Kualitas Air Tambak untuk Sustainability UMKM di Kabupaten Aceh Utara Nunsina; Eva Darnila; Munawwar Khalil; Mustaqim; Zahratul Fitri
Jurnal Malikussaleh Mengabdi Vol. 4 No. 2 (2025): Jurnal Malikussaleh Mengabdi, Oktober 2025
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jmm.v4i02.24783

Abstract

Pengabdian kepada masyarakat ini bertujuan untuk meningkatkan produktivitas dan keberlanjutan UMKM sektor perikanan di Kabupaten Aceh Utara melalui penerapan konsep Blue Economy berbasis teknologi Internet of Things (IoT) untuk pengawasan kualitas air tambak. Permasalahan utama yang dihadapi mitra adalah tidak tersedianya sarana untuk memantau kualitas air secara real-time sehingga berpotensi menurunkan hasil produksi. Kegiatan dilakukan melalui sosialisasi, pelatihan, instalasi perangkat IoT, kalibrasi sensor, serta pendampingan penggunaan sistem. Hasil pelaksanaan menunjukkan bahwa penggunaan IoT mampu memberikan data kualitas air secara akurat dan cepat, sehingga petambak dapat mengambil langkah preventif maupun korektif tepat waktu. Hal ini berdampak pada peningkatan hasil panen, efisiensi penggunaan pakan dan air, serta pengurangan risiko kerugian. Program pengabdian kepada masyarakat ini mendukung tercapainya prinsip Blue Economy dan Sustainable Development Goals (SDGs) di sektor perikanan budidaya udang vaname di Aceh Utara.
Application of Genetic Algorithm and Or-Tools for Cloud-Based Course Scheduling Optimization Jabbar, Salamul; Safwandi; Kurniawati; Eva Darnila; Fuadi, Wahyu
INOVTEK Polbeng - Seri Informatika Vol. 11 No. 1 (2026): February
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/qymmt569

Abstract

Course scheduling in higher education institutions is a complex combinatorial optimization problem involving numerous constraints such as lecturer availability, room capacity, time slots, and course distribution across semesters. Manual scheduling practices often result in conflicts, inefficient resource utilization, and prolonged preparation time. This study proposes a hybrid course scheduling system that integrates a genetic algorithm (GA) and constraint programming using the CP-SAT solver from OR-Tools. The GA is employed in the first phase to generate optimal course sections based on student enrollment, lecturer workload, and capacity constraints. The best solution produced by the GA is then refined using CP-SAT to generate a conflict-free timetable that satisfies all hard constraints, including lecturer, room, and time conflicts, while also optimizing selected soft constraints. The proposed system is implemented as a web-based application deployed on Microsoft Azure, enabling scalability and accessibility. Experimental results using real academic data demonstrate that the hybrid approach successfully produces feasible schedules with zero conflicts and significantly reduces scheduling time compared to manual methods. The results confirm that the integration of GA and CP-SAT provides an effective and flexible solution for university course scheduling problems.
Utilization of Radio Frequency for Monitoring the Temperature of Hydroponic Plants Based on the Internet of Things Dara Maulidia; Eva Darnila; RisaWandi
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

This research aims to develop a temperature monitoring system for hydroponic plants based on the Internet of Things (IoT), using the nRF24L01 radio frequency module. The system is designed to monitor the temperature of hydroponic plants, specifically spinach and chili, and to evaluate its range and efficiency compared to traditional methods such as GSM and Wi-Fi. With this technology, users can monitor and control the hydroponic environment in real-time through a smartphone, which can enhance the efficiency and effectiveness of plant cultivation. The research results indicate that the radio frequency module has a better data transmission range and higher reliability compared to traditional methods, making it an effective and practical solution for hydroponic monitoring. Additionally, this system provides significant benefits in improving plant growth and productivity by ensuring optimal environmental conditions. The use of IoT and radio frequency technology in this research demonstrates great potential for broader applications in agriculture, particularly in promoting more sustainable and efficient farming practices. These findings open up opportunities for further development in utilizing technology to support modern, connected, and smart agriculture.
Co-Authors Albertus Tua Simanullang Balqis Melodi Dara Maulidia Ermatita - FATIMAH FATIMAH Fuadi, Wahyu Iwan Pahendra Jabbar, Salamul Kurniawati Lidya Rosnita Maryana Maryana Marzuki, Sinambela Mauliza Mukti Qamal Munawwar Khalil, Munawwar Mustaqim Mutammimul Ula Naza Amarianda Nunsina, Nunsina Patra Mesiari Tarigan Richki Hardi Risawandi, Risawandi Safwandi Teguh Rahayu Wisnu Wardono Yosvin Apriando Zahratul Fitri ZURAIDA ZURAIDA