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All Journal Jurnal Transformatika Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Dedikasi: Jurnal Pengabdian Masyarakat Jurnal Informatika: Jurnal Pengembangan IT
Ashri Shabrina Afrah
Program Studi Teknik Informatika, UIN Maulana Malik Ibrahim Malang
Religion Aerospace Engineering Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Social Sciences

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Sosialisasi Pengenalan Teknologi Informasi Beserta Manfaat dan Bahayanya di SDN 1 Banturejo Helmi Noor Hafidz; Alifah Shofia Fuadah; Amirah Salsabila S.F.D; Ashri Shabrina Afrah
Dedikasi: Jurnal Pengabdian kepada Masyarakat Vol 16 No 1 (2023): Januari-Juni
Publisher : Pusat Pengabdian Kepada Masyarakat Lembaga Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32678/dedikasi.v16i1.7888

Abstract

In this era of rapid technological development, Information Technology (IT) needs to be taught at all levels of education, including at the elementary school level. The introduction of Information Technology at SDN 1 Banturejo was carried out by holding Information Technology socialization which was held on Saturday, January 7 2023 at 08.00-11.00 WIB. Participants in this activity were students in grades 4 and 5 of SDN 1 Banturejo, totaling 46 students. This activity includes presentation of material, games, and mentoring as well as practice using Microsoft Word and Canva. The method used is a survey technique with test instruments in the form of pre-test and post-test. From the pre-test results, 84% of them did not know the dangers and benefits of information technology, 82% did not know about the Microsoft Word application, and 78% did not know about the Canva application. Meanwhile, from the results of the post-test after the socialization, almost all students at SDN 1 Banturejo already know the dangers and benefits of information technology and how to use Microsoft Word and Canva.
Meningkatkan Kesadaran akan Bahaya Pernikahan Dini pada Remaja di Pedesaan melalui Teknik Sosialisasi di SMP PGRI 1 Ngantang Ayu Shafira Puspitasari; Ashri Shabrina Afrah
Dedikasi: Jurnal Pengabdian kepada Masyarakat Vol 16 No 1 (2023): Januari-Juni
Publisher : Pusat Pengabdian Kepada Masyarakat Lembaga Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32678/dedikasi.v16i1.7894

Abstract

Marriage is the right of every human being. Human instinct to continue civilization. Marriage is the key word for the development of a nation's civilization. Marriage becomes the foundation for better social engineering (Julianto, 2015). Early marriage is a serious case in Indonesia. Early marriage is a social phenomenon that occurs in many regions. The phenomenon of early marriage is like an iceberg phenomenon that only appears a small part on the surface, very little exposed in the public sphere, but in fact it occurs so much among the wider community (Rifiani, 2011). This phenomenon is motivated by several factors such as economic factors, education, customs / culture, religion and because of pregnancy out of wedlock. The impact obtained after early marriage is mostly very detrimental to the perpetrators, such as stress, depression, social conditions such as increasing levels of poverty, the population in Indonesia is increasing, and the impact on health such as pregnant women in adolescence are vulnerable to anemia, babies born to adolescent mothers are at risk of prematurity and low birthweight, babies born to mothers under 20 years old are at risk of malnutrition and stunting, and the risk of dying during childbirth is higher and much more. This community service activity aims to provide proper socialization for adolescents, at which age early marriage often occurs. The method used in this socialization is to use the lecture method, where the speaker delivers the material directly with power point slides. Before and after socialization, the speaker gave questionnaires to students of SMP PGRI 1 Ngantang. This service activity is carried out to provide insight / knowledge to students about early marriage and its harmful effects, as well as preventive ways that can be done to prevent early marriage  
Sistem Diagnosa Penyakit Liver Menggunakan Metode Artificial Neural Network: Studi Berdasarkan Dataset Indian Liver Patient Dataset Ashri Shabrina Afrah
Jurnal Informatika: Jurnal Pengembangan IT Vol 8, No 3 (2023)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v8i3.5346

Abstract

Penyakit Hati atau liver merupakan penyakit yang menyerang organ hati pada manusia dimana organ hati berfungsi dalam pengelolaan kolesterol atau lemak pada tubuh. Dampak yang diberikan oleh penyakit liver ini berbeda-beda tergantung pada tingkat keparahan dan respons pengobatan yang dilakukan oleh individu. Oleh karena itu, pengembangan sistem prediksi penyakit liver menjadi relevan dan bermanfaat dalam membantu dokter dan tenaga medis untuk mengambil tindakan yang tepat secara lebih cepat. Untuk dapat mengembangkan sistem ini maka dapat dilakukan dengan menggunakan metode Artificial Neural Network (ANN). Tujuan dilakukan klasifikasi ini adalah untuk membantu mengetahui keakuratan model ANN dalam mengklasifikasi dataset penyakit liver. Menggunakan metode tersebut dataset dibagi menjadi 3 tahapan yaitu preprocessing data, pemrosesan data, dan evaluasi data. Preprocessing data dilakukan perbaikan terhadap dataset dan melakukan split data sehingga dihasilkan dataset baru. Pada pemrosesan data dilakukan penentuan hidden layer, model aktivasi, dan normalisasi pada model. Pada tahap terakhir yaitu evaluasi dataset, terdapat nilai akurasi, confusion matrix, dan classification report. Pada model ini didapatkan sebuah prediksi true negatif 70, true positif 14, false negatif 16, dan false positif 17. Dengan menggunakan model ini didapatkan hasil akurasi 71,79% yang menandakan bahwa model baik dalam melakukan klasifikasi pada dataset.
The Utilization of Deep Learning in Forecasting The Inflation Rate of Education Costs in Malang Afrah, Ashri Shabrina; Lestandy, Merinda; Suwondo, Juwita P. R.
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 7 No. 1 (2023)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v7i1.729

Abstract

The public needs information about the predicted inflation rate for education costs to manage family finances and prepare education funds. This information is also beneficial for the government to create policies in education. Malang is one of the educational cities in Indonesia, but research on the prediction of the inflation rate of education costs in the city still needs to be made available. Besides, the researchers have yet to find previous studies on forecasting that used the specific inflation rate for education costs in Indonesia by applying the Deep Learning method, especially those using the Consumer Price Index (CPI) data for the Education Expenditure Group. This research aims to develop a model to forecast the inflation of education costs in Malang using the Deep Learning Method. This research was conducted using Consumer Price Index (CPI) data for the Education Expenditure Group in Malang during 1996-2021s taken from the Central Bureau of Statistics (BPS) Malang. The forecasting method used is the Long and Short-Term Memory (LSTM) method, which is a development of the Recurrent Neural Network (RNN). The results showed that it achieved the best accuracy by a model with one hidden layer and four hidden nodes, namely MAPE=2.8765% and RMSE=8.37.
IDENTIFIKASI PENYAKIT JANTUNG MENGGUNAKAN MACHINE LEARNING: STUDI KOMPARATIF Sintiya, Endah Septa; Rizdania, Rizdania; Afrah, Ashri Shabrina; Pramudhita, Agung
Jurnal Transformatika Vol 21, No 1 (2023): July 2023
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v21i2.6274

Abstract

Heart disease is the number one cause of death globally. This condition is followed by an unhealthy lifestyle. Heart disease prediction needs to be done considering the importance of health. The presence of machine learning has made it easier for humans to make early detection of patterns that are close to heart disease. Prediction of heart disease is important given the behavior of people who are still prone to risk factors. Conditions where predictions using machine learning for heart disease have not been compared with many using machine learning methods. Predictions of heart disease are needed along with the interrelationships of the variables. This research compares 6 machine learning methods for disease classification with KNN, Naïve Bayes, Decision tree, Random forest, logistic regression, and SVM. The final classification obtained ranking accuracy with the highest value of 82% in the KNN method with the confusion matrix test, precision, accuracy, re-call, and fi-score. These results can be applied to real case studies of heart disease
Identifikasi Penyakit Jantung Menggunakan Machine Learning: Studi Komparatif sintiya, endah septa; Rizdania, Rizdania; Afrah, Ashri Shabrina
Jurnal Transformatika Vol. 21 No. 2 (2024): Januari 2024
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v21i2.7144

Abstract

Heart disease is the number one cause of death globally. This condition is followed by an unhealthy lifestyle. Heart disease prediction needs to be done considering the importance of health. The presence of machine learning has made it easier for humans to make early detection of patterns approaching heart disease. This study compares 6 machine learning methods for disease classification with KNN, Naïve Bayes, Decision tree, Random forest, logistic regression, and SVM. The final classification obtained ranking accuracy with the highest value in the KNN method with precision, accuracy, re-call, fi-score tests. It is hoped that these results can be applied to real case studies of heart disease.
Co-Authors Alifah Shofia Fuadah Amirah Salsabila S.F.D Ayu Shafira Puspitasari Helmi Noor Hafidz Merinda Lestandy Pramudhita, Agung Rizdania, Rizdania Sintiya, Endah Septa Suwondo, Juwita P. R.