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Ramadhani, Fanny
Universitas Negeri Medan
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K-Means and K-Medoids Algorithm Comparison for Clustering Forest Fire Location in Indonesia Ichwanul Muslim Karo Karo; Sri Dewi; Mardiana Mardiana; Fanny Ramadhani; Putri Harliana
Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) Vol 10 No 1 (2023): Jurnal Ecotipe, April 2023
Publisher : Jurusan Teknik Elektro, Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/jurnalecotipe.v10i1.3896

Abstract

Forest fires are the most common cause of deforestation in Indonesia. This condition has a negative impact on the survival of living things. Of course, this has received special attention from various parties. One effort that can be made for prevention is to group these points into areas with the potential for fire using the clustering method. In this research, a comparative study of the clustering algorithm between K-Means and K-Medoids was conducted on hotspot location data obtained from Global Forest Watch (GFW). Besides that, important variables that affect the clustering process are also analyzed in terms of feature importance. There are nine important variables used in the clustering process, of which the Acq_time variable is the most important. The cluster quality of both algorithms is evaluated using the silhouette coefficient (SC). Both algorithms are capable of producing strong clusters. The best number of clusters is six clusters. The K-medoids algorithm is better at grouping data than K-means.
Implementasi Algoritma Convolutional Neural Network dalam Mengidentifikasi Dini Penyakit pada Mata Katarak Fanny Ramadhani; Andy Satria; Salamah Salamah
sudo Jurnal Teknik Informatika Vol. 2 No. 4 (2023): Edisi Desember
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/sudo.v2i4.408

Abstract

Katarak adalah kekeruhan pada lensa mata yang disebabkan oleh kalsifikasi fibrosa pada kapsul lensa atau bahan lensa. WHO memperkirakan sekitar 18 juta orang mengalami kebutaan pada kedua matanya akibat katarak, yang mencakup total 47,8% dari seluruh penyebab kebutaan mata. Katarak dapat diobati dengan mendeteksi penyakit sejak dini untuk mengurangi kerusakan akibat penyakit tersebut dengan bantuan dokter spesialis mata. Di Indonesia sendiri, akses terhadap dokter spesialis mata terkadang cukup sulit ditemukan, terutama di wilayah pedesaan Indonesia. Oleh karena itu penelitian ini akan membangun model klasifikasi yang digunakan untuk mendeteksi dini penyakit katarak dengan menggunakan bantuan machine learning menggunakan metode Convolutional Neural Network. Berdasarkan hasil penelitian ditemukan bahwa model yang dibangun dengan metode CNN dapat mendeteksi penyakit katarak dengan baik dibuktikan dengan tingkat akurasi sebesar 92,5%. Dengan demikian model ini dapat digunakan untuk mendeteksi penyakit katarak secara dini, kemudian model tersebut dapat diintegrasikan ke dalam berbagai platform seperti aplikasi berbasis mobile untuk memudahkan penggunaan.
KLASIFIKASI RISIKO GIZI BURUK PADA IBU HAMIL MENGGUNAKAN METODE RANDOM FOREST Ramadhani, Fanny; Septiana, Dian; Amalia, Sisti Nadia; Fadilah, Putri Maulidina; Satria, Andy
Djtechno: Jurnal Teknologi Informasi Vol 5, No 2 (2024): Agustus
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v5i2.4815

Abstract

Penelitian ini bertujuan untuk mengidentifikasi ibu hamil yang berisiko mengalami gizi buruk menggunakan metode klasifikasi machine learning, khususnya Random Forest, dengan memanfaatkan data dari RISKESDAS 2018. Dataset yang digunakan mencakup informasi demografi dan pola makan, termasuk usia, pendidikan, pekerjaan, status ekonomi, pola makan, dan akses ke layanan kesehatan. Data tersebut diolah melalui proses preprocessing yang meliputi penanganan nilai yang hilang, transformasi variabel kategori menggunakan OneHotEncoder, dan normalisasi fitur numerik. Model Random Forest kemudian dilatih dan dievaluasi menggunakan metrik akurasi, precision, recall, dan F1-score, serta confusion matrix untuk memahami kinerja klasifikasi. Hasil penelitian menunjukkan bahwa model Random Forest memiliki akurasi sebesar 0.67, precision sebesar 0.6, recall sebesar 0.67, dan F1-score sebesar 0.63 dalam mengklasifikasikan risiko gizi buruk pada ibu hamil. Confusion matrix memperlihatkan distribusi prediksi yang benar dan salah, sedangkan feature importance analysis mengidentifikasi fitur pola makan dan status ekonomi sebagai yang paling berpengaruh dalam prediksi risiko gizi buruk. Model Random Forest ini dapat digunakan sebagai alat yang efektif untuk mengidentifikasi ibu hamil yang berisiko tinggi mengalami gizi buruk, memungkinkan intervensi dini dan terarah dalam program kesehatan ibu hamil, sehingga dapat membantu meningkatkan kesehatan ibu dan anak. Penelitian ini juga menyediakan dasar untuk studi lanjutan yang dapat menggunakan dataset yang lebih luas dan beragam untuk memperbaiki akurasi dan generalisasi model.
Pelatihan Dan Pendampingan Pembuatan Media Pembelajaran Interaktif Berbasis Adobe Flash CS3 Pada Materi Statistika Ramadhani, Fanny; Afiati Nasution, Nadrah; Nadia Amalia, Sisti
Jurnal Pengabdian Masyarakat Gemilang (JPMG) Vol. 2 No. 5: November 2022
Publisher : HIMPUNAN DOSEN GEMILANG INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/jpmg.v2i5.77

Abstract

Media pembelajaran berperan sebagai salah satu sumber belajar siswa. Dengan pemanfaatan media siswa akan lebih tertarik dalam belajar serta dapat mengasah pengetahuan mereka demi mencapai tujuan pembelajaran. Pembelajaran yang menyenangkan dengan penggunaan Media Interaktif berbasis IT misalnya mampu menarik minat siswa untuk lebih mendalami materi yang diajarkan. Terlebih jika guru yang bersangkutan menerapkan pembelajaran yang aktif, inovatif, kreatif, efektif dan menyenangkan. Namun sayangnya masih banyak guru yang tidak memperdulikan pemanfaatan Media Interaktif berbasis IT serta kegunaannya dalam proses pembelajaran. Beberapa guru yang telah diwawancarai mengaku bahwa tidak menggunakan Media Interaktif berbasis IT seperti Adobe Flash CS3 dikarenakan tidak pandai dalam mengoperasikan Aplikasi tersebut. Hal inilah yang menjadi latar belakang tujuan pengabdian masyarakat ini yakni untuk membantu guru-guru matematika dan bidang keahlian lainnya khususnya menggunakan Adobe Flash CS3 sebagai salah satu media pembelajaran. Kegiatan yang dikemas dengan pelatihan langsung ini telah meningkatkan pengetahuan guru-guru di SMK Sandhy Putra–2 Medan. Kegiatan pengabdian ini terdiri dari tiga tahapan, yaitu tahapan pertama persiapan dengan mengadakan wawancara kepada kepala sekolah, tahap kedua pelatihan dan pendampingan dan tahap ketiga evaluasi. Hasil pelatihan dan pendampingan ini menunjukkan bahwa 10 guru (83,33%) guru mampu membuat media pembelajaran interaktif berbasis Adobe Flash CS3 dan 3 guru (16,7%) belum mampu membuat media pembelajaran berbasis Adobe Flash CS3. Hal ini terjadi karena guru baru pertama kali menggunakan Aplikasi Adobe Flash CS3 untuk membuat media pembelajaran.
Implementasi Metode Weight Product untuk Menentukan Jurusan IPA atau IPS di Sekolah Muhammadiyah 18 Sunggal Hutagalung, Fatma Sari; Ramadhani, Fanny; Sari, Indah Purnama
IHSAN : JURNAL PENGABDIAN MASYARAKAT Vol 3, No 2 (2021): Ihsan: Jurnal Pengabdian Masyarakat (Oktober)
Publisher : University of Muhammadiyah Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/ihsan.v3i2.7650

Abstract

Ada beberapa metode yang dapat digunakan untuk membantu dalam menentukan jurusan. Salah satunya adalah metode Weight Product. Metode Weighted Product adalah salah satu penyelesaian pada sistem pendukung keputusan. Metode ini mengevaluasi beberapa alternatif terhadap sekumpulan atribut/kriteria, dimana setiap atribut tidak bergantung antara satu dengan lainnya. Dalam buku kusumadewi yang diterbitkan pada tahun 2006 disebutkan bahwa metode WP menggunakan teknik perkalian untuk rating atribut. dimana rating atribut harus dipangkatkan dengan bobot atribut yang bersangkutan.
Implementasi E-Monitoring Aktivitas Siswa Pada SMKN 5 dan SMKS 2 Medan Putri Berbasis Web Ramadhani, Fanny; Al-Khowarizmi, Al-Khowarizmi; Hutagalung, Fatma Sari
IHSAN : JURNAL PENGABDIAN MASYARAKAT Vol 3, No 2 (2021): Ihsan: Jurnal Pengabdian Masyarakat (Oktober)
Publisher : University of Muhammadiyah Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/ihsan.v3i2.7571

Abstract

SMK Negeri 5 Medan is one of the vocational high schools in the city of Medan. One of the visions and missions of this school is to increase discipline in complying with existing regulations. One of the things that must be disciplined is attendance, timely collection of assignments and payment of tuition fees that must be on time. But in reality there are still some students who do not attend school because the student withdraws so that parents feel worried about the condition of their children at school, whether they actually go to school or not and parents also cannot know the progress of how many grades their children have earned in general directly because of busy work, there are even students who cannot maintain the mandate to pay tuition fees that have been deposited by their parents. Therefore, a system is needed to monitor student activities at school. Monitoring activities are the main activities in the world of education. However, these activities cannot be carried out optimally. Parents still find it difficult to monitor their children's learning activities at school. Notification of student achievement (grades) is only made at the time of receipt of the final report. Therefore we need a system that facilitates the process of monitoring and assessing students, both for teachers and parents to overcome these problems. The purpose of this research is to develop a student monitoring system (E-Monitoring). The method used to develop this system is data collection, hardware and software analysis, system design and analysis as well as system implementation and testing. The result of this study is a system that can assist teachers in managing grades, recap student errors, and facilitate parents to monitor and obtain information about their children's learning activities clearly and in real time.
Implementasi Algoritma Naive Bayes dalam Meningkatkan Akurasi Diagnosa Penyakit Tumor Otak Surianto, Stacyana Jesika; Putra, Samuel Anaya; Ananta, Willy Pramudia; Sitorus, Rizki Risdah; Ramadhani, Fanny
JATISI Vol 11 No 3 (2024): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v11i3.8113

Abstract

A brain tumor is an abnormal growth of cells in the brain that often requires an accurate diagnosis from a radiologist. This study aims to implement the Naive Bayes algorithm in improving the accuracy of brain tumor diagnosis. Naive Bayes is a popular classification algorithm in data mining that can provide accurate results even with limited datasets. The study used a dataset of MRI images of brain tumors from Kaggle consisting of 2044 image samples with three classes: meningioma tumors, pituitary tumors, and no tumors. The process starts with image preprocessing, then feature extraction using Local Binary Pattern (LBP), and classification using Naive Bayes algorithm. The test results showed the best parameters of LBP were radius 1 and neighborliness 8, while the Naive Bayes model achieved 68% accuracy, 67% precision, and 66% recall in classifying all three classes of brain tumors. The study expands knowledge of the potential of the Naive Bayes algorithm in brain tumor diagnosis and may form the basis for further research.
Pengembangan Bahan Ajar Digital Flipbook Dalam Meningkatkan Kompetensi Guru TK di TK Citra Indonesia Satria, Andy; Ramadhani, Fanny; Salamah, Salamah
Jurnal Pengabdian Pada Masyarakat Indonesia Vol 2 No 5 (2023): Oktober : Jurnal Pengabdian Pada Masyarakat Indonesia
Publisher : Universitas Gajah Putih, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55542/jppmi.v2i5.880

Abstract

Improving the quality of learning at the basic education level, especially in Kindergarten (TK), is an urgent need in facing the demands of developments in information technology. This service aims to develop and evaluate digital teaching materials in the form of Flipbooks as an innovative means of improving the competency of kindergarten teachers at Citra Indonesia Kindergarten. The development method used is the ADDIE (Analysis, Design, Development, Implementation, Evaluation) development model, which involves needs analysis, design, development, implementation and evaluation of digital teaching materials. The Flipbook digital teaching materials developed focus on increasing kindergarten teachers' understanding and skills in managing interesting and interactive learning. The materials presented are designed to fulfill the kindergarten curriculum and integrate technology as a learning medium that can motivate pre-school children. The implementation of Flipbook in learning activities at Citra Indonesia Kindergarten is carried out through intensive training and mentoring to ensure teachers' mastery of technology. The evaluation was carried out through observation, interviews and questionnaires to measure the effectiveness of using Flipbook digital teaching materials in improving the competence of kindergarten teachers. The evaluation results show a significant increase in understanding of interactive learning concepts and mastery of technology by kindergarten teachers. Therefore, the development of Flipbook digital teaching materials can be an effective alternative in improving the quality of learning at Citra Indonesia Kindergarten, as well as stimulating teacher creativity and motivation in teaching.
CLUSTERING HIV/AIDS DISEASE USING K-MEANS CLUSTERING ALGORITHM Sari, Indah Purnama; Hariani MD, Pipit Putri; Al-Khowarizmi, Al-Khowarizmi; Ramadhani, Fanny; Sulaiman, Oris Krianto; Satria, Andy; Manurung, Asrar Aspia
Proceeding International Seminar of Islamic Studies INSIS 6 (February 2024)
Publisher : Proceeding International Seminar of Islamic Studies

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

Abstract

The HIV (Human Immunodeficiency Virus) is an infection-causing virus that targets the immune system, making it more vulnerable to illness and infection. East Java (33,043), Papua (25,586), West Java (24,650), and Central Java (18,038 persons) all had more HIV/AIDS infections in 2017 than DKI Jakarta (46,378), which was followed by East Java (33,043), West Java (24,650), and a smaller number—25,586—in Papua. Nationally, West Java is still among the four provinces with the highest HIV/AIDS cases. This shows that HIV/AIDS has become a threat to the wider community because in addition to threatening the lives of sufferers, this disease is at risk of transmission that will increase. The increase in HIV/AIDS cases can be a problem in the psychology of the sufferer, because this disease can have a negative impact in the form of physical, psychological, social and spiritual problems that cause PLWHA (People with HIV AIDS) to live a stressful life. In this study, calculations were carried out using the K-Means algorithm with the Optimize Parameters Grid on data on the spread of HIV / AIDS cases in 2019-2021 sourced from the West Java Provincial Health Office. K-Means is one of the algorithms in data mining that can be used for grouping / clustering of data. The data used in this study were 971 records. The purpose of this study was conducted to determine the cluster of t h e spread of HIV/ AIDS as an effort to assist the government in reducing the number of HIV / AIDS cases in West Java province. The results o f this study are comparing DBI with the K-Means method from k-2 to k-20 contained in the table above, it can be seen that the cluster that is close to 0 is k-2, with a DBI value of 0.414. Because the value of k-2 is the smallest value compared to other k, it can be concluded that k-2 with a value of 0.414 which is closest to 0 is the best cluster result.
IMPLEMENTASI ALGORITMA CNN DALAM MENGIDENTIFIKASI TINGKAT KEPARAHAN JERAWAT PADA WAJAH Adhi Guna, Ekin; Fransiska Sihombing, Esra; Nico Pasaribu, Michael; Syahputra, Hermawan; Ramadhani, Fanny
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 8 No. 4 (2024): JATI Vol. 8 No. 4
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v8i4.10010

Abstract

Penggunaan teknologi komputer di sektor kesehatan telah berkembang pesat, terutama dalam sistem rekomendasi dan promosi kesehatan. Perkembangan kecerdasan buatan, khususnya deep learning, telah terbukti sangat bermanfaat dalam deteksi dini penyakit melalui analisis pencitraan medis. Convolutional Neural Network (CNN), sebagai salah satu bagian dari deep learning, menunjukkan kinerja tinggi dalam berbagai aplikasi, termasuk identifikasi jerawat. Jerawat pada remaja memiliki dampak signifikan pada aspek personal, sosial, dan psikologis, seringkali menyebabkan depresi dan rendahnya percaya diri. Pengetahuan masyarakat tentang perawatan jerawat yang tepat masih terbatas, yang sering kali menyebabkan kesalahan perawatan dan memperburuk kondisi. Penelitian ini bertujuan untuk mengembangkan sistem berbasis CNN guna mengidentifikasi tingkat keparahan jerawat sehingga dapat memberikan penanganan yang tepat. Implementasi CNN memungkinkan model untuk mengekstraksi hierarki fitur dari citra, sehingga menciptakan representasi visual yang lebih baik untuk variasi dari tingkat keparahan jerawat. Hasil penelitian dengan 1.106 dataset dari tiga label menunjukkan akurasi sebesar 75%, menegaskan efektivitas CNN dalam mengidentifikasi pola visual tingkat keparahan jerawat. Sistem ini diharapkan mampu memberikan solusi dalam mengatasi masalah keparahan jerawat dan mengurangi kesalahan perawatan yang sering terjadi, sehingga meningkatkan kualitas hidup remaja yang terpengaruh oleh jerawat.
Co-Authors Abadi Simanullang, Paskah Ade Amelia, Tasya Ade Setiawan Adhi Guna, Ekin Advis Ambrosius Sitohang, Yuda Afiati Nasution, Nadrah Africano, Fernando Afrrahman S. Effendi, Ali Agung Wijaya, Agung Agus Waruwu, Stefen Ahmad Rahmatika Al Hamidy Al Kautsar, Muhammad Zidane Al Khowarizmi Alby Savana HSB, Muhammad Alfin, Muhammad Amalia, Sisti Nadia Amanah, Fadilla Ambarwati, Nilasari Eka Amelia Br Siregar, Ririn Amelia Vega S. Meliala, Ruth Ananda Hafika, Rizky Ananta, Willy Pramudia Andika Maulana, Sandy Andy Satria Apandi, Khairul Aprilia, Adinda Putri Arnita Arnita Arnita Arnita Asri Angel Tumanggor Asro Harahap, Fatimah Audy Priscilia, Selfi Audy Priscillia, Selfi Aulia, Windy Ayu Sekar Ayu Syahfitri Ayu, Silvana Oyasi Azima Lubis, Fauzan Azmi Lubis, Fauzan br.Hutagalung, Fhadillah Budi Akbar, Muhammad Bush Henrydunan, John Daulay, Parhan Dedy Kiswanto Defiyanti, Aqilah Diah Retno Wahyuningrum Dian Damayanti Dian Septiana Dicky Apdilah Dimas Fadhlurohhman Dimas Prayoga Dina Aulia Djasmayena, Selvia Dly, Revidamurti Dobry Sianipar, Freyro Drilanang, Mhd Ilyasyah Dwi Zahra Putri, Raisya Elza Ahmad Erlangga, Farizi Evanthe, Hansel Evelyn Keisha Silalahi Fadilah, Putri Maulidina Fahmi Sagala, Khairul Farezi, Nazwar Fatma Hutagalung Fatma Sari Hutagalung Fauzan, M Rosyid Fauzan, Rosyid Fayadhilah, Muhammad Apta Fhadillah, Fhadillah Fitra, Muhammad Rizki Andrian Fransiska Sihombing, Esra Giovanni, Teuku Muhammad Hafiz, Alfin Haikal Al Majid, Muhammad Hapzi Ali Harahap, Fatimah Asro Hasan, Afrizal Hermawan Syahputra Hidayat, Muhammad Ferdiansyah Hidayatul Arifin, Muhammad Husna Batubara, Shabrina Hutagalung, Fatma Sari Ichwanul Muslim Karo Karo Impana Manik, Kristin Indah Purnama Sari Indah Purnama Sari Indriani.S, Dechy Deswita Insan Pratama Siagian, Raihan Irya Shakila Syukron, Ananda Islamia, Aulia Ismail Hanif Batubara Iwan Agi Berutu Jailani Arsad John Pardamean Hutabarat, Felix Juliana Silalahi, Feby Khildan Rifail Azis Khoiriah, Najwatul Latifah Hasibuan, Najwa Listia, Hijka Lubis, Muhammad Ghafur Rahman Lutfi Basit M. Fahri Fahroza Manurung, Asrar Aspia Mardiana Mardiana Maulana, Raihan Maulida Surbakti, Nurul Mei Lammi Malau Mhd. Basri Mufit, Muhammad Ilham Muhammad Habib Muhammad Naufal Musyafa Muhammad Ridho Muhammad Ridho Muhammad Rizki Alfahri Muslim Sinaga, Rizal Nadia Amalia, Sisti Nadrah Afiati Nasution Najwa Latifa Hasibuan Nasution, Nadrah Afiati Nico Pasaribu, Michael Nst, M. Fahri Fahroza Nurul Maulida Surbakti Nurul Sasti Diningsih Oktavia, Grace Oktaviani, Nadya Sisil Oris Krianto Sulaiman Pebiana Putri, Fahra Permata Putri Pasaribu, Yohanna Pipit Putri Hariani MD Prana Walidin, Adamsyach Pratama, Ega Prihatin Ningsih Sagala Putra Paskah Halawa, Sovantri Putra, Samuel Anaya Putri Harliana Putri Sartika Putri Tasya Agustina Raffi Akbar, Muhammad Rahma, Aulya Raihan Insan Pratama Siagan Ramadhan Manik, Albert Ramadhani, Sigi Pegi Ramadhani, Umaya Rangga Mahara Miko Ravindra Singh Richi, Alfina Rizki Andrian Fitra, Muhammad Rizki, Widya Selia Rushainy, Siti Raisha Sadion Tumpal Damanik Sagala, Khairul Fahmi Said . Iskandar Salamah Salamah salamah salamah Salsabila Zahra, Salsabila Sapta Warman Zai, Tri Siagian, Angel Agasari Siallagan, Sanri Yuliana Simbolon, Agata Putri Handayani Sinaga, Elya Juni Arta siti wulandari Sitompul, Dicky Sambora Sitorus, Rizki Risdah Situngkir, Silvia Wulandari Sri Dewi Sri Dewi Sri Dewi Steviana Viviola Wicesti Nasution Sumita Wardani Surianto, Stacyana Jesika Susanto, Raoul Syahri, Alfin Tanjung, Muhammad Raffi Akbar Todo Simanjuntak Trimuliani, Diva Tymoty Hutabarat, Peter Wahyu Pratama, Rangga Wahyudi, Rizky Wardaniah, Sabina Warjaya, Angga Yazid Noor, Muhammad Zai, Tri Sapta Warman Zaki Zain Zulfahrizan, Atta