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All Journal Teknika ELEKTRO SAMUDERA Techno Nusa Mandiri : Journal of Computing and Information Technology METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Building of Informatics, Technology and Science Jurnal Vokasi JTIK (Jurnal Teknik Informatika Kaputama) Jurnal Ners Jurnal Tekinkom (Teknik Informasi dan Komputer) JUKI : Jurnal Komputer dan Informatika MEANS (Media Informasi Analisa dan Sistem) International Journal of Engineering, Science and Information Technology International Journal of Research in Vocational Studies (IJRVOCAS) TECHSI - Jurnal Teknik Informatika Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Teknologi Terapan and Sains 4.0 Journal of Mathematics Instruction, Social Research and Opinion Journal of Advanced Computer Knowledge and Algorithms Jurnal Solusi Masyarakat Dikara INOVTEK Polbeng - Seri Informatika JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) ITEJ (Information Technology Engineering Journals)
Eva Darnila
Unknown Affiliation
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering 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 Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Social Sciences Transportation Other

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Penerapan Logika Fuzzy Tsukamoto pada Rancang Bangun Sistem Deteksi Kekeruhan Air Budi Daya Ikan Lele Rizki, Muhammad; Darnila, Eva; Agusniar, Cut
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp112-120

Abstract

This study develops a water quality monitoring system for catfish farming using the Internet of Things (IoT) and Fuzzy Tsukamoto logic. This system consists of a Turbidity Sensor to measure turbidity levels, a DS18B20 sensor to monitor temperature, and a pH meter to measure water acidity levels. Data from the sensors is sent in Realtime to Firebase and displayed in an Android application based on Kodular. The Fuzzy Tsukamoto method is used to analyze data, determine the water quality status whether the water value is Clean, Normal, or Turbid based on predetermined parameters. Based on 14 tests, the system showed an accuracy level of 85.7%, with 12 matching results. In addition, this system is able to provide automatic notifications to users if there are significant changes in water conditions. As a result, this system can help fish farmers monitor water quality efficiently, as well as make decisions about when is the right time to change pond water.
A Review of Digital Image Classification Based on Fuzzy Logic Sinambela, Marzuki; Rahayu, Teguh; Darnila, Eva; Limbong, Tonni
MEANS (Media Informasi Analisa dan Sistem) Volume 5 Nomor 1
Publisher : LPPM UNIKA Santo Thomas Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (510.127 KB) | DOI: 10.54367/means.v5i1.704

Abstract

Fuzzy logic has long been an important issue for in the field of computer science, computer vision, image processing, machine learning and control theory and mathematics. In this review paper, we also see that the basics of fuzzy logic as well as fuzzy logic system (Fuzzy Inference System) use as decision making technique under a linguistic view of fuzzy sets. In this study, we focused to review the fuzzy logic to classification of digital image. The aim of this study was to review the fuzzy logic algorithm for classification of image.
Development of an Expert System to Detect Mental Disorders in Pregnant Women using Forward and Backward Chaining Methods Dela, Monisa; Darnila, Eva; Rosnita, Lidya
Building of Informatics, Technology and Science (BITS) Vol 7 No 2 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i2.7930

Abstract

Mental health during pregnancy plays a critical role in fetal development and maternal well-being. However, psychological conditions such as depression, stress, and anxiety in pregnant women often go undetected, especially in primary healthcare settings. This research aims to design and develop a web-based expert system capable of diagnosing the mental health conditions of pregnant women using Forward Chaining and Backward Chaining inference techniques. Forward Chaining is applied to infer possible conditions based on reported symptoms, while Backward Chaining is used to validate hypotheses by tracing required supporting symptoms. The system was developed using patient data collected from three health centers in Lhokseumawe City, totaling 500 records with parameters including name, age, gestational age, number of children, and reported complaints. It incorporates 30 symptoms and 9 diagnostic rules to classify the mental condition and its severity.The results indicate that 179 women were diagnosed with depression (mild 107, moderate 33, severe 39), 150 with anxiety (mild 24, moderate 91, severe 35), and 171 with stress (mild 82, moderate 50, severe 39). The system also demonstrates diagnostic probability (e.g., 66.67% in a specific case). Validation using 20 test cases yielded an accuracy of 85%, showing the system performs reliably in aligning symptoms with diagnostic outcomes. This study makes two significant contributions. Practically, it offers a decision-support tool for midwives and general practitioners to perform early mental health screening of pregnant women, especially in regions lacking access to psychiatric specialists. Scientifically, it demonstrates the effectiveness of a hybrid reasoning approach in handling overlapping psychological symptoms and in assessing severity levels, thereby enriching the development of domain-specific expert systems in maternal mental health. In conclusion, this system provides a practical and accessible solution to support early detection and intervention in maternal mental health, ultimately contributing to improved health outcomes for both mothers and their babies.
OPTIMIZING PHARMACEUTICAL DISTRIBUTION IN PUBLIC HEALTH CENTERS USING FUZZY C-MEANS CLUSTERING Nurahma, Syahfitri; Darnila, Eva; Fajriana
Jurnal Techno Nusa Mandiri Vol. 20 No. 2 (2025): Techno Nusa Mandiri : Journal of Computing and Information Technology Period o
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v20i2.7336

Abstract

Efficient drug distribution is fundamental to ensuring the quality of public healthcare services. However, health departments often face challenges with imbalances between drug demand and available supply. This study addresses this issue by applying the Fuzzy C-Means (FCM) clustering algorithm to categorize drug demand levels across 16 public health centers (puskesmas) in Langkat Regency, Indonesia, from 2021 to 2023. Using historical data from 2,400 drug records, the analysis identified five distinct demand clusters: Very Low, Low, Medium, High, and Very High. The results revealed a significant disparity in drug needs, with the "Very High" demand cluster dominating (51.29% of data) in centers like Besitang and Tanjung Selamat, driven by high morbidity rates. In contrast, other clusters were less prevalent, such as the "Low" demand cluster, which was primarily concentrated in the Gebang health center. These findings, visualized using t-SNE plots, highlight significant regional variations in pharmaceutical needs. This data-driven clustering provides a robust framework for the Langkat District Health Office to develop more targeted, efficient, and equitable drug distribution strategies, ultimately improving healthcare service delivery.
VISUAL ANALYSIS OF LOCAL EARTHQUAKE IN NORTH TAPANULI BASED ON DATA SCIENCE Sinambela, Marzuki; Darnila, Eva
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 7 No. 2 (2023): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol7No2.pp363-367

Abstract

Earthquakes are natural phenomena that occur when the Earth's tectonic plates move and release energy. Big Data's emergent epistemological and research paradigms, as well as data science, an increasingly integrated field of data research, are opening up new opportunities. Visualizing earthquake data is all about understanding earthquake characteristics such as size, location and depth. The result show that September was the quietest month in terms of earthquakes, and in this graph we can see the number of earthquakes for each month in 2022. The month of October is the one that has the highest number of earthquakes. We can see the average depth and magnitude of each year on the bubble chart. In addition, the size and color of the bubbles indicate the number of earthquakes that month. In general, most of the earthquakes occurred in the shallow earthquake range and the 1.8-3.85 magnitude range.
Analisa Hubungan Penyakit Jantung Koroner Terhadap Penyebabnya Menggunakan Algoritma Frequent Pattern Growth Darnila, Eva; Nazira, Nazira; Fajriana , Fajriana
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp19-31

Abstract

The increase in cases of coronary heart disease without detailed knowledge of the causes is a serious problem that requires immediate treatment. This study aims to analyze the relationship between causal factors and the incidence of coronary heart disease using the Frequent Pattern Growth (FP-Growth) algorithm. This algorithm is applied to medical data of inpatients at RSUD dr. Fauziah Bireuen to identify patterns of relationships that often arise between risk factors such as age, gender, diabetes, cholesterol, hypertension and uric acid on the diagnosis of coronary heart disease. There were 180 patient medical record data with 17 items used for analysis. The results show the three most significant relationship patterns: the combination of risk factors for diabetes and high cholesterol has a support value of 50% and confidence of 67%, the risk of diabetes in men has a support value of 47% and confidence of 63%, and the combination of cholesterol and hypertension shows a support value of 45 % and confidence 66%. These results are expected to provide better insight into the prevention, early detection and treatment of coronary heart disease, as well as improving health services in hospitals. This research also emphasizes the importance of applying data mining technology in the analysis of complex health data.
Penerapan Logika Fuzzy Tsukamoto pada Rancang Bangun Sistem Deteksi Kekeruhan Air Budi Daya Ikan Lele Rizki, Muhammad; Darnila, Eva; Agusniar, Cut
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp112-120

Abstract

This study develops a water quality monitoring system for catfish farming using the Internet of Things (IoT) and Fuzzy Tsukamoto logic. This system consists of a Turbidity Sensor to measure turbidity levels, a DS18B20 sensor to monitor temperature, and a pH meter to measure water acidity levels. Data from the sensors is sent in Realtime to Firebase and displayed in an Android application based on Kodular. The Fuzzy Tsukamoto method is used to analyze data, determine the water quality status whether the water value is Clean, Normal, or Turbid based on predetermined parameters. Based on 14 tests, the system showed an accuracy level of 85.7%, with 12 matching results. In addition, this system is able to provide automatic notifications to users if there are significant changes in water conditions. As a result, this system can help fish farmers monitor water quality efficiently, as well as make decisions about when is the right time to change pond water.
Prototype Penyiraman Otomatis Pada Tanaman Bawang Putih dengan Metode Fuzzy Sugeno Berbasis Arduino Uno Nunsina, Nunsina; Darnila, Eva; Fadhilah, Cut; Razi, Ar
TEKNIKA Vol. 18 No. 1 (2024): Teknika Januari - Juni 2024
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.10614572

Abstract

Bawang putih merupakan jenis tanaman yang biasa ditanam di dataran tinggi tropis yang sangat sensitif terhadap cekaman kekeringan. Kekurangan air dapat menyebabkan pembentukan umbi terhambat sehingga akan mengurangi hasil poduksi. Penelitian iini bertujuan untuk membuat sebuah perangkat yang mampu mengotomatisasi proses penyiraman tanaman bawang putih . Proses penyiraman bawang putih secara manual memakan waktu yang signifikan karena harus dikerjakan secara individual untuk setiap pohon. Perangkat ini dirancang untuk memberikan manfaat dengan memudahkan pekerjaan manusia dalam menyirami bawang putih. Pendekatan yang digunakan dalam penelitian ini adalah Metode Penelitian dan Pengembangan (R&D). Perangkat ini dilengkapi dengan sensor kelembaban tanah yang berperan sebagai pengecek tingkat kelembaban dan mengirim instruksi kepada Arduino Uno untuk mengaktifkan driver relay, sehingga pompa air untuk melakukan penyiraman otomatis sesuai kebutuhan. Penelitian ini meliputi perancangan, serta implementasi komponen-komponen sistem, termasuk penggunaan Arduino Uno sebagai pengendali dan driver relay untuk mengatur aktivitas pompa air. Data dari penelitian memastikan bahwa perangkat yang dibuat berfungsi secara efektif, di mana relay akan beroperasi dan mengaktifkan pompa ketika tingkat kelembaban tanah di bawah 40%. Sebaliknya, relay akan berhenti beroperasi ketika kelembaban tanah mencapai lebih dari 40%. Agar dapat berproduksi optimal bawang putih memerlukan volume dan interval penyiraman yang tepat.
PREDIKSI HARGA PASAR KOMODITI TANAMAN PANGAN DI ACEH UTARA PADA MASA PANDEMI COVID-19 DENGAN METODE FUZZY TIME SERIES MODEL CHEN Darnila, Eva; Dinata, Rozzy Kesuma; Ramadani, Suci
JTIK (Jurnal Teknik Informatika Kaputama) Vol. 7 No. 1 (2023): Volume 7, Nomor 1, Januari 2023
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jtik.v7i1.26

Abstract

Prediksi atau peramalan harga pasar merupakan suatu kegiatan untuk memprediksi harga dari suatu produk yang akan datang menggunakan data histori. Tanaman pangan sendiri adalah semua jenis tanaman yang memiliki kandungan karbohidrat dan juga protein untuk manusia sebagai sumber energi. Variabel yang dipakai pada penelitian ini adalah beras, jagung, dan kedelai. Hasil dari penelitian ini menunjukkan metode fuzzy time series (FTS) model chen memiliki kinerja yang sangat akurat yaitu ≤ 10%, dimana dari hasil kajian yang telah ditemukan oleh peneliti mendapatkan nilai ukuran ketepatan peramalan yaitu MAPE selama periode 4 tahun tersebut sebesar 3,46% untuk beras, kemudian untuk 4,36% jagung dan sebesar 4,32% untuk kedelai. Dari penelitan yang memakai metode Fuzzy Time Series model Chen ini penulis dapat menyimpulkan bahwa semakin sedikit data yang digunakan untuk mencari keakuratan nilai prediksinya maka MAPE yang dihasilkan semakin tinggi tingkat erornya.
Implementasi Media Augmented Reality dalam Pembelajaran Materi Digital pada Mahasiswa Semester II Teknik Informatika UNIMAL Darnila, Eva; Puspasari, Cindenia; Fadlisyah, Fadlisyah
Jurnal Solusi Masyarakat Dikara Vol 5, No 3 (2025): Desember 2025
Publisher : Yayasan Lembaga Riset dan Inovasi Dikara

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

Abstract

Implementasi media Augmented Reality (AR) sebagai inovasi pembelajaran pada mata kuliah materi dasar digital untuk mahasiswa semester 2 Program Studi Teknik Informatika Universitas Malikussaleh. Teknologi AR digunakan untuk menghadirkan visualisasi tiga dimensi pada konsep-konsep digital yang bersifat abstrak, seperti sistem bilangan, gerbang logika, aljabar Boolean, peta Karnaugh, dan rangkaian flip-flop. Penggunaan AR memungkinkan mahasiswa berinteraksi langsung dengan objek 3D sehingga proses pemahaman materi menjadi lebih konkret, menarik, dan mudah dipahami. Metode pelaksanaan kegiatan meliputi penyampaian materi teori mengenai konsep dasar digital dan prinsip kerja AR, bimbingan praktik menggunakan aplikasi AR berbasis marker-based tracking, serta evaluasi yang dilakukan melalui angket skala Likert dan observasi. Instrumen penilaian difokuskan pada aspek pemahaman, motivasi belajar, tampilan visual, dan interaktivitas dalam proses pembelajaran. Hasil implementasi menunjukkan bahwa 40 mahasiswa yang terlibat memberikan respons positif terhadap penggunaan AR, dengan nilai rata-rata penilaian berada pada kategori baik hingga sangat baik. Mahasiswa terlihat lebih aktif, antusias, dan mampu menghubungkan teori dengan praktik melalui eksplorasi objek 3D. Visualisasi AR yang jelas dan fitur interaktif seperti rotasi, zoom in, dan zoom out membantu memperkuat pemahaman konsep digital yang sebelumnya sulit dibayangkan melalui metode konvensional. Secara keseluruhan, AR terbukti efektif sebagai media pembelajaran yang inovatif, interaktif, dan mampu meningkatkan kualitas pembelajaran materi dasar digital di Perguruan Tinggi.
Co-Authors Angaw, Mariance Wulan Asrianda Asrianda Bakti Viyata Sundawa Cindenia Puspasari Cut Agusniar Cut Dewi Aida Soraya Cut Fadhilah Dela, Monisa Dhyra Gibran Alinda Dinata, Rozzy Kesuma Ermatita - Fadisar, Nanda Fadlisyah Fadlisyah Fajriana , Fajriana Fajriana, Fajriana Febrin Aulia Batubara Fuadi, Wahyu Hafiz Al-Kautsar Hafni Hafni Hafni Hafni Harahap, Lina Mardiana Hazmanan Khair Hizamrul jaen Ichsan ilham - sahputra Irhami, Putri Iwan Pahendra jaen, Hizamrul Jannah, Rauzatul Japirman Purba Julita, Rina Khainesya, Khainesya Khairunnisa Khairunnisa Khalid Mawardi Lidya Rosnita Lina Mardiana Harahap M. Althaf Kiram Mandala, Rizki Maryana Maryana Maryana Marzuki, Sinambela Mauliza, Mauliza Melly, Melly Yani Melodi, Balqis Muhammad Azmi, Muhammad Muhammad Fikry Muhammad Iqbal Muhammad Rivai Muhammad Rizki Mukti Qamal Mutammimul Ula Nasution, Tuti Adi Tama Nazimah Nazimah Nazira Nazira Nilahayati Nunsina, Nunsina Nurahma, Syahfitri Nurdin Nurdin Nurfaiza Nursanti Nursanti Nursanti Nursanti Pahendra, Iwan Pane, Syamsul Buchori Ramadani, Suci Rauzatul Jannah Razi, Ar Rini Meiyanti Risawandi, Risawandi Ritonga, Maya Syarah Rozzi Kesuma Dinata Safrizal Safrizal Safwandi Safwandi Salsabila, Cut Syahira Serlina Serlina Sinambela Marzuki Suci Ramadani Syaiful Bahri Syamsul Buchori Pane Teguh Rahayu TONNI LIMBONG Ulvityatni Wahyu Fuadi Yaumil Iksan Zahratul Fitri, Zahratul Zara Yunizar