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All Journal Journal of Innovation and Applied Technology ComTech: Computer, Mathematics and Engineering Applications
Novi Nur Aini
Brawijaya University
Computer Science & IT Engineering Mathematics

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Community Assistance For Quality Improvement And Testing Of Dairy Products As A Superior Product In Krisik Village, Gandusari District, Blitar Regency Henny Pramoedyo; Novi Nur Aini; Bestari Archita Safitri; Suci Astutik; Achmad Efendi; Loekito Adi Soehono
Journal of Innovation and Applied Technology Vol 8, No 1 (2022)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jiat.2022.008.01.5

Abstract

Krisik Village is one of the villages located in Gandusari District, Blitar Regency, East Java Province. Krisik Village has abundant natural resources. Krisik Village has livestock products in the form of milk and its processed products which are managed independently by the Bumdes Krisik. Krisik Village already has several types of dairy products, namely fermented milk, milk sticks, milk candy and milk ice cream. As a step to improve the typical product of Krisik village, it is necessary to have an activity that is able to increase public understanding in product processing and marketing. This service activity aims to improve the quality and marketing of dairy products in Krisik village. Activities that have been carried out are in the form of coordination with the village, making ice cream packaging designs and product marketing training by utilizing social media. This activity is expected to increase the independence of the crisis village community in marketing their products.
Comparison of Adaptive Holt-Winters Exponential Smoothing and Recurrent Neural Network Model for Forecasting Rainfall in Malang City Novi Nur Aini; Atiek Iriany; Waego Hadi Nugroho; Faddli Lindra Wibowo
ComTech: Computer, Mathematics and Engineering Applications Vol. 13 No. 2 (2022): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v13i2.7570

Abstract

Rainfall forecast is necessary for many aspects of regional management. Prediction of rainfall is useful for reducing negative impacts caused by the intensity of rainfall, such as landslides, floods, and storms. Hence, a rainfall forecast with good accuracy is needed. Many rainfall forecasting models have been developed, including the adaptive Holt-Winters exponential smoothing method and the Recurrent Neural Network (RNN) method. The research aimed to compare the result of forecasting between the Holt-Winters adaptive exponential smoothing method and the Recurrent Neural Network (RNN) method. The data were monthly rainfall data in Malang City from January 1983 to December 2019 obtained from a website. Then, the data were divided into training data and testing data. Training data consisted of rainfall data in Malang City from January 1983 to December 2017. Meanwhile, the testing data were rainfall data in Malang City from January 2018 to December 2019. The comparison result was assessed based on the values of Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE). The result reveals that the RNN method has better RMSE and MAPE values, namely RMSE values of 0,377 and MAPE values of 1,596, than the Holt-Winter Adaptive Exponential Smoothing method with RMSE values of 0,500 and MAPE values of 0,620. It can be concluded that the non-linear model has better forecasting than the linear model. Therefore, the RNN model can be used in modeling and forecasting trend and seasonal time series.
Co-Authors Achmad Efendi Atiek Iriany Bestari Archita Safitri Faddli Lindra Wibowo Henny Pramoedyo Loekito Adi Soehono Suci Astutik Waego Hadi Nugroho