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Weather Prediction for Strawberry Cultivation Using Double Exponential Smoothing and Golden Section Optimization Methods Herlinah, Herlinah; Asrul, Billy Eden William; HS, Hafsah; Faisal, Muhammad; Lee, Swa Lee; Gani, Hamdan; Feng, Zhipeng
ILKOM Jurnal Ilmiah Vol 16, No 3 (2024)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v16i3.2290.305-317

Abstract

Strawberry is one of the fruit commodities that has a high demand so that it is widely cultivated by most people in Bantaeng Regency to meet with the market needs. The high intensity of weather changes is the main challenge in the strawberry production, which is influenced by climate dynamics and the start season time changes. Climate change does not only affect the amount of rainfall, but also causes a shift in the rainy season and dry season start. As a result, in the cultivation of plants such as strawberries, there are often difficulties in adjusting or slow anticipation in the extreme changes of rainfall. This research began with the data collection stage through field observations, interviews, and literature studies. The design tool used a systematically organized UML, which included a use case diagram, then an activity diagram, as well as an elaboration into sequence diagrams, and class diagrams. The system was developed by implementing the PHP programming language on the interface design as well as MySQL as a database processing. The algorithm used to predict the air temperature feature, wind speed feature, and rainfall feature was Double Exponential Smoothing, followed by the optimization of the Golden Section method to select the right smoothing value. Referring to the results of this study, the system can provide planting time recommendations based on prediction of rainfall, air temperature, and wind speed parameters through a web-based platform. Based on the calculation of the accuracy value of the prediction results using the Mean Absolute Percentage Error (MAPE), the obtained forecast error value was of 5.89% for wind speed, 0.63% for air temperature, and 0.69% for rainfall. The Golden Section Optimization in Double Exponential Smoothing provided the best smoothing for prediction.
Augmented reality application on the tourism orientation sign digital system at the 'Bawah Langit' museum Zuhriyah, Sitti; William Asrul, Billy Eden; Jura, Suwatri
ILKOM Jurnal Ilmiah Vol 13, No 3 (2021)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i3.857.216-225

Abstract

One of the most visited tourism icons in Makassar is the Losari Beach Pavilion which provides many choices ranging from beautiful sunsets, typical banana epe cuisine, floating mosques, and rows of statues of heroes and icons of Makassar City which are spread over four platforms, namely Makassar Pavilion, Bugis Pavilion, Mandar and Toraja which is commonly called the Museum Under the Sky. In supporting the attraction, it is necessary to be equipped with an accurate explanation of the statues in the attraction. In the new normal that limits interaction with other people, digital and virtual explanations will be one solution to provide attractive and up-to-date information. This study aims to create a Digital Tourism Orientation Sign System, which is an information system that provides accurate explanations and descriptions of the hero statues in the Underground Sky Museum. With this application, the Losari Pavilion is one of the futuristic tourist attractions with local wisdom. This application has been tested using Alpha testing which includes distance testing with test results a minimum distance of 10 cm and a maximum distance of 1 m marker will be detected; light testing with object test results will appear from a room brightness level greater than 10 Lux.