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All Journal Jurnal Pekommas CogITo Smart Journal JurTI (JURNAL TEKNOLOGI INFORMASI) Joined Journal (Journal of Informatics Education) Water Circulation Monitoring System in The Vanname Shrimp Cultivation based on Internet of Thing
ST. Aminah Dinayati Ghani
Universitas Dipa Makassar
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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Performance Analysis of Weather Forecasting using Machine Learning Algorithms (Analisis Performansi Prakiraan Cuaca Menggunakan Algoritma Machine Learning) Indo Intan; Rismayani Rismayani; St. Aminah Dinayati Ghani; Nurdin Nurdin; Aswar TC. Koswara
Jurnal Pekommas Vol 6, No 2 (2021): Oktober 2021
Publisher : BBPSDMP KOMINFO MAKASSAR

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30818/jpkm.2021.2060221

Abstract

Weather forecasting are very important in various fields of human life, including in big cities. The need for accurate weather forecasts will be effective and efficient in managing the quality of civilization flexibly. In many cases it is found that the results of weather forecasts in the same city differ depending on the radius. This of course requires a precise and accurate algorithm to determine it. The algorithm used is based on machine learning type of artificial neural network which compares backpropagation and bayessian regularization. The results obtained show that bayessian regularization outperforms backpropagation with the smallest MSE and the highest accuracy and the shortest computation time to determine sunny, cloudy, light rain and heavy rain forecasts. The unbalanced distribution of data causes fluctuations in the MSE calculation and accuracy. The addition of training will improve system performance which is indicated by a significant increase in accuracy. Likewise, decreasing the MSE can increase the accuracy of the system to reach the point of convergence. This is an indicator that the performance of Bayessian regularization is the recommended algorithm for forecasting weather in cities and their surroundings, even between provinces or between countries.
Implementasi Aplikasi Berbasis Android Pengembangan Ide Resep Makanan dan Minuman Pada Restoran Sitti Aisa; ST. Aminah Dinayati Ghani
(JurTI) Jurnal Teknologi Informasi Vol 5, No 1 (2021): JUNI 2021
Publisher : Universitas Asahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36294/jurti.v5i1.1790

Abstract

Abstract – This study aims to design and implement an android-based application for the development of food and beverage recipe ideas. Data collection techniques in this study are observation and interviews. The test model that will be carried out in this study is Black Box testing. System modeling using Unifield Modeling Language (UML) The results of testing an android-based application for the development of cooking and beverage ideas in restaurants and tests carried out using this application restaurant owners can develop recipes where they receive recipe ideas from visitors and can easily see the sales that occur in restaurants and can assist chefs in implementing recipes given by visitors so as to increase the number of food menus in the restaurant. Keywords  - Android, Applications, Food, Beverages, Restaurants Abstrak - Penelitian ini bertujuan untuk merancang dan mengimplementasikan aplikasi berbasis android pengembangan ide Resep makanan dan minuman. Teknik pengumpulan data dalam penelitian ini yaitu observasi dan wawancara. Model pengujian yang akan dilakukan dalam penelitian ini adalah pengujian Black Box. Pemodelan sistem dangan Unifield Modeling Language (UML)  Hasil pengujian implementasi aplikasi berbasis android untuk pengembangan ide masakan dan minuman pada restoran serta pengujian yang dilakukan penggunaan aplikasi ini pemilik restoran dapat mengembangkan resep masakan dimana menerima ide resep masakan dari pengunjung dan dapat dengan mudah melihat penjualan yang terjadi di restoran serta dapat membantu koki dalam mengimplemetasi resep yang telah diberikan oleh pengunjung sehingga menambah jumlah menu makanan yang ada direstoran. Kata Kunci – Android, Aplikasi, Makanan, Minuman, Restoran
Performance Analysis of Weather Forecasting using Machine Learning Algorithms (Analisis Performansi Prakiraan Cuaca Menggunakan Algoritma Machine Learning) Indo Intan; Rismayani Rismayani; St. Aminah Dinayati Ghani; Nurdin Nurdin; Aswar TC. Koswara
Jurnal Pekommas Vol 6, No 2 (2021): Oktober 2021
Publisher : BBPSDMP KOMINFO MAKASSAR

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30818/jpkm.2021.2060221

Abstract

Weather forecasting are very important in various fields of human life, including in big cities. The need for accurate weather forecasts will be effective and efficient in managing the quality of civilization flexibly. In many cases it is found that the results of weather forecasts in the same city differ depending on the radius. This of course requires a precise and accurate algorithm to determine it. The algorithm used is based on machine learning type of artificial neural network which compares backpropagation and bayessian regularization. The results obtained show that bayessian regularization outperforms backpropagation with the smallest MSE and the highest accuracy and the shortest computation time to determine sunny, cloudy, light rain and heavy rain forecasts. The unbalanced distribution of data causes fluctuations in the MSE calculation and accuracy. The addition of training will improve system performance which is indicated by a significant increase in accuracy. Likewise, decreasing the MSE can increase the accuracy of the system to reach the point of convergence. This is an indicator that the performance of Bayessian regularization is the recommended algorithm for forecasting weather in cities and their surroundings, even between provinces or between countries.
Aplikasi Pengenalan Pola Penyakit Kulit Menggunakan Algoritma Linear Discriminant Analysis ST. Aminah Dinayati Ghani; Indo Intan; Nur Salman
CogITo Smart Journal Vol. 8 No. 1 (2022): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v8i1.365.206-218

Abstract

Sometimes, someone underestimates to check up skin disease unless the disease has affected his face or body in severe condition. The checkup fees for skin diseases are relatively expensive because they require a specialist. While the reach of society, in general, is the lower community. The purpose of this study is to bridge the gap between the patient and the examination of the disease based on the patient's skin image. The methods used in feature extraction and classification are Linear Discriminant Analysis LDA and Euclidean Distance respectively. LDA performs image feature extraction through a matrix operation process and distinguishing features in the same class and different classes. Classification will give the output of disease: abscess, eczema, ringworm, and urticaria. The accuracy results obtained are 80%. The next research is on adding features in the form of skin color so that it can be an input feature in the image as well as to improve its performance in the future. This application can be an alternative initial checkup for patients. It will detect the type of skin disease be suffered before consulting an expert.
Neural Network Berbasis Algoritma Genetika untuk Prediksi Kesempatan Kerja Siti Aminah Dinayati G.
Joined Journal (Journal of Informatics Education) Vol 1 No 1 (2018): JOINED Journal of Informatics Education
Publisher : Universitas Ivet

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (785.397 KB) | DOI: 10.31331/joined.v1i1.611

Abstract

ABSTRAK Kesempatan kerja merupakan aspek kehidupan yang paling dibutuhkan dalam memenuhi kebutuhan hidup manusia. Oleh karena itu perlu diketahui faktor-faktor ekonomi apa saja yang mempengaruhi pertumbuhan kesempatan kerja dengan cara pengelolaan yang tepat untuk mengantisipasi kemungkinan buruk yang dapat mengganggu pertumbuhan kesempatan kerja. Tujuan dari penelitian ini adalah untuk mengetahui akurasi dari prediksi kesempatan kerja dengan menggunakan Neural Network dan pembobotan menggunakan Algoritma Genetika. Hasil penelitian menunjukkan bahwa akurasi yang didapatkan untuk prediksi kesempatan kerja menggunakan Algoritma Neural Network adalah sebesar 87,45 % dengan AUC 0,89 termasuk dalam good classification, sedangkan apabila menggunakan Algoritma Neural Network berbasis Algoritma Genetika untuk pembobotan atribut maka nilai akurasi yang didapatkan adalah sebesar 88,30 % dan AUC 0,92 termasuk dalam excelent classification. ABSTRACT Employment is an aspect of life is most needed in meeting human needs. Therefore, please note the economic factors that influence the growth of employment by means of proper management to anticipate the possibility of bad that can interfere with the growth of employment. The purpose of this study was to determine the accuracy of the prediction of employment by using Neural Network and weighting using Genetic Algorithms. The results showed that the prediction accuracy is obtained for employment using Neural Network algorithm is equal to 87.45% with 0.89 AUC included in good classification.
Co-Authors Aswar TC. Koswara Indo Intan Indo Intan Nur Salman Nurdin Nurdin Rismayani Rismayani Sitti Aisa