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All Journal ComEngApp : Computer Engineering and Applications Journal Jurnal Simantec POSITIF Sistemasi: Jurnal Sistem Informasi BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Teknologi dan Informasi Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Vokasi Journal of Artificial Intelligence and Engineering Applications (JAIEA) Proceeding Applied Business and Engineering Conference Journal Of Artificial Intelligence And Software Engineering Jurnal INFOTEL Jurnal Sistem Informasi dan Manajemen eProceeding of TIK Jurnal Teknologi Rekayasa Informasi dan Komputer
Arhami, Muhammad
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Journal : Proceeding Applied Business and Engineering Conference

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Weather Forecasting Using Neural Networks with Backpropagation and ADAM Optimizer for city of Lhokseumawe Arhami, Muhammad; Aulia, Annisa Rizka; Salahuddin, Salahuddin; Desiani, Anita; Yassir, Yassir
ABEC Indonesia Vol. 12 (2024): 12th Applied Business and Engineering Conference
Publisher : Politeknik Negeri Bengkalis

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Abstract

Weather forecasting in Lhokseumawe is crucial due to its diverse climate and impact on community activities.It serves as an operational responsibility of the Meteorology, Climatology and Geophysics Agency (BMKG) worldwide.The method of forecasting currently employed by the BMKG involves meteorological teams observing and analyzingstatistics based on principles of mechanics and physics. Artificial Neural Networks (ANN) can be utilized to forecastlong-term weather conditions, with the backpropagation algorithm being an ANN algorithm employed for short-termweather prediction. This involves training the backpropagation architecture data, which includes an input layer with asize of 6 using Relu activation, one hidden layer with a size of 64 using Relu activation, and an output layer with a size of3 using softmax activation. We also apply the ADAM optimizer, loss sparse categorical crossentropy, and accuracymetrics. However, the backpropagation algorithm displays weaknesses, including slow convergence, overfitting, andsusceptibility to local minima, which can be addressed by utilizing the ADAM optimization algorithm. The researchutilizes Artificial Neural Network (ANN) with the backpropagation algorithm and ADAM optimization to predictweather conditions in Lhokseumawe City with high accuracy. The research methods comprise of data collection,preprocessing, division, model building, and evaluation. The study outcomes present the weather conditions as sunny,cloudy, or rainy with an algorithm accuracy of 72%.
Co-Authors ., Mursyidah Abdi, Musta’inul Adhimullah, Adhimullah Adriana Adriana Affandi, Azhar Kholiq Agustin, Riya Sri Al Fath, Muhammad Fajar Ali Amran Amirullah -, Amirullah Andhini, Shania Putri Anita Desiani Anwar Anwar Aulia, Annisa Rizka Azhar Azhar Davi, Muhammad Des Alwine Zayanti, Des Alwine Dian Cahyawati Fajriaty, Siti Fauzani, Lia Fitri, Intan Ginting, Rachel Ardana Putra Hendrawati Hendrawati Hendrawaty Hendrawaty, Hendrawaty Henisaniyya, Nabila Hidayat, Hari Toha Husaini Husaini Huzaeni, Huzaeni Indrawati Indrawati Insan, Jamalul Irmeilyana Isnani Isnani Kanda Januar Miraswan Khadafi, M. Khairunnas, Muhammad Fadil Kurniawati, Devy Mahdi Mahdi, Mahdi Mahmudah, Rifa’atun Masyitha, Masyitha Maulana, Muhammad Andra Meilisa, Dinda Meilvinasvita, Dwi Mesti, Mesti Mortara, Alda Amalia Muakhir, Muakhir Mufida, Nabila Muhammad Arifai Muhammad Davi Muhammad Nasir Muhammad Reza Zulman Muhammad Rizka, Muhammad Mulyadi Mulyadi Muzammil, Muzammil Nahar, Nahar Narti Narti, Narti Nasution, Siti Aisyah Novi Rustiana Dewi Nurakmalinda, Nurakmalinda Permatasari, Mitta Pertiwi, Citra Purnahar, Fadhil Rahmadhani, Syiva Rahmadita, Suristhia Raiyan, Muhammad Ramayanti, Indri Rifkie Primartha Rizqillah, Rizqillah Rudi F, Fachri Yanuar Safriadi Safriadi Safriani, Yuni Salahuddin Salahuddin Salahuddin Salahuddin Salnadila, Salnadila Sari, Suci Indah Sasongko, Muhammad Aditya Sitorus, Dina Suzzete Sri Indra Maiyanti Sugandi Yahdin Sugeng, Santoso Sukma, Melati Dian Yadi Utama Yassir Yassir Yuli Andriani Yuliana Yuliana Zahara, Fitria