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R., Rakhmat Kurniawan
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Computer Science & IT

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Pengatur Temperatur Minuman pada Dispenser Berbasis Mikrokontroler dengan Logika Fuzzy Mamdani Saragih, Rafif Aprizki; R., Rakhmat Kurniawan
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 1 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i1.37925

Abstract

The need for hot water is something that is needed in everyday life, with hot water it will facilitate the serving of drinks that are favored by the community such as coffee, milk and tea. However, in certain conditions, a person needs water with varying temperatures around 15°C to 95°C. Variations in water temperature needed in making drinks can affect the quality of the drinks served. The need for a temperature device on the dispenser to make it easier to adjust the water temperature. Dispensers with features that can control water temperature so that someone is easier to set how much water temperature is needed by combining hot and normal water into one output without having to mix, increase or decrease the volume. One of the control techniques that is often used today is control with Mamdani fuzzy logic. In this research, fuzzy controllers are used to keep the temperature stable. The water temperatures used in this dispenser are 65°C for tea, 75°C for milk and 90°C for coffee. The time required to reach the highest temperature of 90 from the normal temperature of 29.50 is 5 minutes. There is a temperature difference on the LCD display with a thermometer during testing, namely for tea 2.30%, milk 2.66% and coffee by 1.66%. These errors can occur due to the tolerance of the components used. From the test results, the application of fuzzy logic in the dispenser for temperature regulation is very effective in stabilizing the water temperature in tea, milk and coffee.
Penerapan Algoritma Backpropagation untuk Prediksi Hasil Panen Padi di Kabupaten Labuhan Batu Utara Tbn, Ahmad Fauza Anshori; R., Rakhmat Kurniawan
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 1 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i1.38318

Abstract

Rice is a food crop that has vital benefits and important benefits for human survival. Rice plants are often found in the surrounding environment, especially those living in rural areas. Farmers use various methods to continue to increase rice yields. However, in reality the rice harvest results are not stable from year to year, this is because farmers' businesses still depend on natural factors which have a risk of causing a high chance of crop failure, thus accumulating the risk of low income received by farmers, including in the Regency. North Labauhanbatu so a prediction is needed to find out the future picture of the rice harvest. Predictions are also made so that lowland rice production remains stable. One way that is often used to make predictions is to use artificial neural networks. Artificial Neural Networks (ANN) are designed based on the structure and function of the human brain as a model of intuitive imitation. In an artificial neural network there are a number of neurons. One network can connect to many other networks, and each connection (link) has a weight (weight). Prediction of rice harvest results in Kabuipatein Labuihan Batui Uitara using the backpropagation algorithm. The results of trials carried out with the Rapid Mineir architectural model software with an RMSEi amount of 0.403 +/- 0.000 in the implementation of backpropagation. The smaller the RMSEi (Root Meian Squiareid Eirror) the better the teirseibuit model.
Co-Authors Saragih, Rafif Aprizki Tbn, Ahmad Fauza Anshori