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Determinant of Primary Preventive Behaviour Cervical Cancer in an Adolescent Girl Muh Zul Azhri Rustam; Dwi Helynarti Syurandhari; Deni Susyanti; Irma Handayani; Fitriani Pramita Gurning; Muchti Yuda Pratama
Indian Journal of Forensic Medicine & Toxicology Vol. 15 No. 4 (2021): Indian Journal of Forensic Medicine & Toxicology
Publisher : Institute of Medico-legal Publications Pvt Ltd

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37506/ijfmt.v15i4.17044

Abstract

Cervical cancer is caused by infection with the human papilloma virus which can infect the genitals, anus,throat, mouth and cells on the surface of the skin. Cervical cancer is often late so that it can cause death,so efforts are needed to reduce the risk factors for cervical cancer, namely through primary preventionefforts. The purpose of this study was to determine the relationship between primary factors and cervicalcancer prevention behavior in adolescent girls. The sample in this study were 77 young women who weretaken by technique purposive sampling. The research design used was an observational analysis using across sectional approach and analyzed using chi-square. The results of this study illustrate that there is arelationship between knowledge, attitudes and social support with cervical cancer prevention behavior inadolescent girls. So we need efforts to reduce cervical cancer risk factors, namely through primary preventionefforts, by increasing outreach activities in the community to carry out a healthy lifestyle.
PERILAKU KOMSUMSI BUAH DAN SAYUR ANAK SEKOLAH DASAR NEGERI 020583 BINJAI ESTATE Irma Handayani
Jurnal Maternitas Kebidanan Vol. 4 No. 2 (2019): Jurnal Maternitas Kebidanan
Publisher : Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jumkep.v4i2.740

Abstract

CONSUMPTION BEHAVIOR OF VEGETABLES AND VEGETABLES OF STATE ELEMENTARY SCHOOLS 020583 BINJAI ESTATE Irma Handayani Diploma Nursing Study Program, Healthy Nursing Academy Binjai, Indonesia email: handay1502@gmail.com ABSTRACT One of the balanced nutrition guidelines is adequate consumption of fruits and vegetables. Currently children aged 5-14 have a tendency to consume 20% of fruits and vegetables lower when compared to adults 30-59 years. The main problem arising from lack of fruit and vegetable consumption is calorie and protein deficiency disease (KKP), vitamin A deficiency (KVA), disorders due to iodine deficiency (IDD), and iron (Fe) deficiency anemia. The purpose of this study was to determine the consumption behavior of fruit and vegetables in children SDN 020583. This type of research is descriptive by using a cross sectional design. The population in this study was 38 people, the results of this study showed three domains of behavior, namely knowledge, attitudes, and actions, where good knowledge was 25 people (65.78%), enough as many as 12 people (31.57%) and less as many 1 person (2.63%), positive attitude as many as 37 people (97.36%) and those who have negative attitudes as much as 1 person (2.63), and who have actions in good fruit consumption as many as 32 people (84.21 %) and less as many as 6 people (15.78%), for actions in good vegetable consumption as many as 32 people (89.47%) and less than 4 people (10.52%).
PENERAPAN ALGORITMA C4.5 UNTUK KLASIFIKASI PENYAKIT DISK HERNIA DAN SPONDYLOLISTHESIS DALAM KOLUMNA VERTEBRALIS Irma Handayani
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol 1, No 2 (2019): Vol 1, No 2 (2019): Desember 2019
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v1i2.3185

Abstract

Disk Hernia dan Spondylolisthesis merupakan contoh penyakit yang dapat terjadi pada kolumna vertebralis atau tulang belakang. Suatu proses ekstraksi untuk mencari informasi dalam data yang belum diketahui sebelumnya dikenal dengan istilah data mining. Salah satu peranan utama data mining adalah klasifikasi. Klasifikasi banyak digunakan untuk menentukan keputusan sesuai pengetahuan baru yang didapat dari pengolahan data lampau menggunakan algoritma. Penelitian ini melakukan penerapan nilai akurasi algoritma C4.5 pada klasifikasi penyakit disk hernia dan spondylolisthesis serta kecepatan waktu pada proses klasifikasi. Proses klasifikasi dilakukan dengan cara memasukkan data dari sumber utama ke dalam sistem, kemudian melakukan proses perhitungan menggunakan metode algoritma C4.5. Hasil penelitian menunjukkan bahwa akurasi dari classifier C4.5 sebesar 89%. Rata-rata lama waktu yang dibutuhkan untuk melakukan klasifikasi classifier C4.5 0,00912297 detik. DOI : https://doi.org/10.26905/jasiek.v1i2.3185
Pengembangan media animasi Flash untuk meningkatkan critical thinking skill Remaja melawan hoaks Ulfa Amalia; Erlin Fitria; Irma Handayani
Counsellia: Jurnal Bimbingan dan Konseling Vol 10, No 2 (2020)
Publisher : Universitas PGRI Madiun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25273/counsellia.v10i2.7600

Abstract

Peredaran berbagai informasi di dunia maya sangat beragam. Remaja yang cenderung aktif di media sosial memiliki resiko besar untuk terpapar hoaks. Kemudahan dalam mengakses dan menyebarkan informasi dengan bebas tanpa meninjau kebenarannya menjadi persoalan yang berpotensi untuk menimbulkan kesalahpahaman dan konflik. Karena itu, perlu upaya preventif dan interventif yang dapat dilakukan dengan memberikan pendekatan melalui edukasi dengan menggunakan media interaktif dalam lingkup layanan informasi. Penelitian ini bertujuan untuk menghasilkan media animasi flash dalam upaya meningkatkan critical thinking remaja melawan informasi hoaks. Metode penelitian dengan menggunakan R n D (research and development) mulai dari tahap perencanaan, desain, validasi ahli media dan ahli materi. Uji coba produk juga dilakukan pada kelompok terbatas untuk mendapatkan penilaian dari pengguna. Berdasarkan validasi ahli materi mendapatkan nilai 82,95% artinya sangat layak sedangkan menurut ahli media produk animasi dinilai sebesar 85,71% artinya juga sangat layak. Pada kelompok pengguna, produk mendapatkan nilai 84,40% dengan menggunakan standar penggunaan usability. Sesuai dengan hasil validasi dan penilaian maka hasil penelitian berupa animasi sebagai multimedia interaktif dianggap sangat layak untuk dapat digunakan dalam memberikan stimulasi positif bagi remaja dalam layanan informasi sebagai langkah membangun dan meningkatkan kemampuan berfikir kritis.Abstract: The circulation of various information in cyber space is very diverse. The ease of accessing and disseminating information freely without reviewing the truth is an issue that has the potential to cause misunderstanding and conflict. Therefore, preventive and interventive efforts are needed to carry out by providing an educational approach using interactive media within the scope of information services. This study aims to produce flash animation media as an effort to improve adolescent critical thinking to fight hoax. The research method used in this study is Reseach and development starting from the planning, design, expert validation, media and material validation. Product testing is also carried out in limited groups to get ratings from users. Based on the validation of material experts, the figure is 82.96% meaning that it is very feasible. In addition, according to media experts, the figure of animation products is 85.71% which means that it is also very feasible. In the user group, the product figure is 84.40% by using the usability standard. Related to the validation results and assessment, it is implied that animation as interactive multimedia is considered very feasible to be used in providing positive stimulation for adolescents in information services as a step to build and improve critical thinking skill
COMPARISON OF K-NEAREST NEIGHBOR AND NAÏVE BAYES FOR BREAST CANCER CLASSIFICATION USING PYTHON Irma Handayani; Ikrimach Ikrimach
IJISCS (International Journal of Information System and Computer Science) Vol 5, No 1 (2021): IJISCS (International Journal of Information System and Computer Science)
Publisher : STMIK Pringsewu Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/ijiscs.v5i1.953

Abstract

Classification is widely used to determine decisions according to new knowledge gained from processing past data using algorithms. The number of attributes can affect the performance of an algorithm. Several data mining methods that are widely used for classification include the K-Nearest Neighbor and naïve Bayes algorithm. The best algorithm for one data type is not necessarily good for another data type. It is even possible that a good algorithm will be horrendous for other data types. To overcome this issue, this study will analyze the accuracy of the K-Nearest Neighbor and Naïve Bayes algorithms for the classification of breast cancer. So that patients with existing parameters can be predicted which are malignant and benign breast cancer. This pattern can be used as a diagnostic measure so that the cancer can be detected earlier and is expected to reduce the mortality rate from breast cancer.
Peningkatkan keterampilan guru Sekolah Luar Biasa (SLB) dalam pembelajaran daring Erlin Fitria; Ulfa Amalia; Irma Handayani
KACANEGARA Jurnal Pengabdian pada Masyarakat Vol 5, No 2 (2022): Juli
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/kacanegara.v5i2.1085

Abstract

Pandemi yang terjadi di seluruh dunia berdampak pada aspek kehidupan manusia, salah satunya adalah bidang pendidikan. Pembelajaran tatap muka beralih menjadi daring. Pembelajaran daring menimbulkan keresahan dari sisi guru, diantaranya kesulitan guru dalam menggunakan media penunjang pembelajaran daring seperti zoom, google meet, screen cast o matic dll. Berawal dari keresahan dari guru di lapangan tersebut, maka kegiatan pengabdian ini dilakukan. Kegiatan pengabdian yang dilakukan bertujuan untuk meningkatkan keterampilan guru dalam menggunakan media pembelajaran daring, sehingga dapat melakukan modifikasi dalam pembuatan materi pembelajaran untuk siswa berkebutuhan khusus. Guru diberikan pelatihan untuk menggunakan aplikasi Gem Reflektif dan aplikasi Screen Cast O Matic. Pelatihan ini berlangsung selama empat hari di SLB Tunas Sejahtera Seyegan. Pengukuran tingkat keterampilan sebelum dan sesudah kegiatan menggunakan instrument kuesioner keterampilan dalam pembelajaran daring. Dari hasil analisis data ditemukan adanya perbedaan yang signifikan antara keterampilan guru dalam pembelajaran daring sebelum dan sesudah diberikan pelatihan
Application of K-Nearest Neighbor Algorithm on Classification of Disk Hernia and Spondylolisthesis in Vertebral Column Irma Handayani
Indonesian Journal of Information Systems Vol. 2 No. 1 (2019): Agustus 2019
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v2i1.2352

Abstract

Vertebral column as a part of backbone has important role in human body. Trauma in vertebral column can affect spinal cord capability to send and receive messages from brain to the body system that controls sensory and motoric movement. Disk hernia and spondylolisthesis are examples of pathologies on the vertebral column. Research about pathology or damage bones and joints of skeletal system classification is rare whereas the classification system can be used by radiologists as a second opinion so that can improve productivity and diagnosis consistency of the radiologists. This research used dataset Vertebral Column that has three classes (Disk Hernia, Spondylolisthesis and Normal) and instances in UCI Machine Learning. This research applied the K-NN algorithm for classification of disk hernia and spondylolisthesis in vertebral column. The data were then classified into two different but related classification tasks: “normal” and “abnormal”. K-NN algorithm adopts the approach of data classification by optimizing sample data that can be used as a reference for training data to produce vertebral column data classification based on the learning process. The results showed that the accuracy of K-NN classifier was 83%. The average length of time needed to classify the K-NN classifier was 0.000212303 seconds.
Function Consuming sebagai Tingkat Kecakapan Literasi Media Digital Masyarakat Yogyakarta Ade Irma Sukmawati; Irma Handayani
Jurnal Komunikasi Vol. 16 No. 2 (2022): VOLUME 16 NO 2 APRIL 2022
Publisher : Program Studi Ilmu Komunikasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/komunikasi.vol16.iss2.art6

Abstract

Digital competence is one of the skills for users in using digital media. Research on mapping the digital competence category of the people of Yogyakarta was carried out to know the media digital positioning competence of digital media users. The position of digital media user skills is categorized by the k-NN (k Nearest Neighbor) technique data mining method. The objective of this research using the k-NN technique data mining method was carried out by compiling categories that refer to attributions where the attribution refers to the ten competencies of Japelidi's digital media users. The digital media user skills category has four quadrants: Function Consuming, Function Prosuming, Critical Consuming, and Critical Prosuming. This research was conducted in Yogyakarta from June-July 2020 because, during this period, there was a surge in digital media users due to the pandemic. The findings in this research provide information that the competence of using digital media for Yogyakarta residents in the period of June-July 2020 is in the Function Consuming section, and it is in the first quadrant
Accuracy Analysis of K-Nearest Neighbor and Naïve Bayes Algorithm in the Diagnosis of Breast Cancer Irma Handayani; Ikrimach Ikrimach
JURNAL INFOTEL Vol 12 No 4 (2020): November 2020
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v12i4.547

Abstract

In the medical field, there are many records of disease sufferers, one of which is data on breast cancer. An extraction process to fine information in previously unknown data is known as data mining. Data mining uses pattern recognition techniques such as statistics and mathematics to find patterns from old data or cases. One of the main roles of data mining is classification. In the classification dataset, there is one objective attribute or it can be called the label attribute. This attribute will be searched from new data on the basis of other attributes in the past. The number of attributes can affect the performance of an algorithm. This results in if the classification process is inaccurate, the researcher needs to double-check at each previous stage to look for errors. The best algorithm for one data type is not necessarily good for another data type. For this reason, the K-Nearest Neighbor and Naïve Bayes algorithms will be used as a solution to this problem. The research method used was to prepare data from the breast cancer dataset, conduct training and test the data, then perform a comparative analysis. The research target is to produce the best algorithm in classifying breast cancer, so that patients with existing parameters can be predicted which ones are malignant and benign breast cancer. This pattern can be used as a diagnostic measure so that it can be detected earlier and is expected to reduce the mortality rate from breast cancer. By making comparisons, this method produces 95.79% for K-Nearest Neighbor and 93.39% for Naïve Bayes
Implementasi Augmented Reality untuk Media Pembelajaran Tata Surya pada Anak Usia Dini Dzaki Padhlurrahman; Irma Handayani
Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Vol 14, No 2 (2023): Desember
Publisher : Universitas Bandar Lampung (UBL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/jsit.v14i2.3341

Abstract

Tata Surya adalah kumpulan benda langit yang terdiri atas sebuah bintang, yakni matahari, serta semua objek yang terikat oleh gaya gravitasinya. Objek tersebut bukan hanya berupa delapan planet, tetapi juga berupa lima planet kerdil, 173 satelit alami yang telah diidentifikasi, serta jutaan benda langit lainnya berupa meteor, asteroid, komet, dan lainnya. Media pembelajaran yang mengangkat tema pengenalan tata surya bagi anak-anak seperti buku yang berisi gambar-gambar planet dan bintang 2 dimensi belum begitu mampu menarik minat anak-anak untuk mau mengenali objek-objek yang ada di tata surya. Berdasarkan permasalahan tersebut, penulis membangun sebuah aplikasi augmented reality pengenalan tata surya yang menampilkan objek tata surya 3D dan memiliki fitur quiz mengenai tata surya sebagai sarana pembelajaran interaktif dan menarik bagi anak-anak yang dikemas dalam sebuah aplikasi berbasis android. Pada penelitian ini digunakan Game Engine Unity 3D untuk membangun aplikasi berbasis android serta Vuforia SDK agar aplikasi yang dibangun dapat menjadi aplikasi berteknologi Augmented Reality. Media pengenalan tata surya dengan teknologi Augmented Reality ini dapat dijalankan pada platform android minimal versi 8.1, dengan adanya aplikasi ini dapat mempermudah proses pembelajaran dan menambah minat belajar anak.