Clouds become an important part of human life and are studied in several disciplines in the form of important analyses in some applications. Examples of application of cloud analysis on solar panels or photovoltaics, accurate weather forecasts, accuracy of rainfall predictions, application in the field of meteorology, imaging of the sky in some cases, air humidity survey, and the case of turbulence on Aircraft caused by clouds cumulonimbus. The structure and shape of the clouds are continuously changing, becoming an interesting part to detect. The cloud detection process can be done by taking several samples of imagery from the cloud and the image processing process is done. Most research processes RGB cloud imagery into HSV cloud imagery, Some research using the image detection method of flying apply the channel's convolution R-B, R/B, ????−????????+????, dan chroma C = max(R, G, B)-min(R, G, B). Gamma correction has an efficient characteristic of storing and dividing imagery by small bits, thus the study proposed an image detection development using automatic gamma correction, with ground truth being Image data from SWIMSEG Nanyang Technological University Singapore. The proposed method in the proposed study obtained a precision value and better computing time with a precision value of 0.93 and a computational time of 0.71 sec.
Web phishing is a type of cybercrime that occasionally threatens the online activities of website visitors. Web phishing uses a phoney website page that closely mimics the legitimate Website in order to fool its target into providing crucial information. Web phishing attacks also continue to grow in popularity year after year. As a result, it is vital to design a web phishing detection system in order to reduce the number of victims and financial losses caused by web phishing attacks. The development of a web phishing detection system continues to this day, with machine learning being the most often used model. Unfortunately, the construction of a machine learning-based web phishing detection system frequently employs only a single classification step; however, the feature selection process enables an increase in the performance of the resultant classification. Thus, an experiment was conducted in this paper by using a feature selection procedure based on the Pearson correlation algorithm prior to doing machine learning modelling utilizing popular algorithms such as Naive Bayes, Decision Tree, and Random Forest. As a result, using a web phishing dataset from the UCI Machine Learning Repository, it was determined that the addition of the feature selection process based on the use of decision tree and random forest algorithms resulted in an increase in accuracy of up to 94.60 percent and 95.50 percent, respectively, and a slight decrease in accuracy of 0.4 percent when implemented in the Naive Bayes algorithm.
This study aims to produce Exe-Learning-based mathematics e-modules on sequences and series material for grade XI Vocational High School (SMK) that are valid, effective, and practical. This research is development research (RD) with the ADDIE development model. The research subjects were math teachers and class XI students at SMK Putra Jaya Centre. The research instruments were expert assessment sheets, posttest questions, and teacher and student response assessment sheets. Based on the results, the e-module is categorized as very valid with an average score for content eligibility was 3.41, presentation feasibility was 3.60 and language was 3.50. Furthermore, the assessment of media experts obtained an average score on the aspect of graphic feasibility of 3.61 and media feasibility of 3.50. Testing the effectiveness of the e-module based on the results of the students' posttest obtained classical completeness results of 91% in the very effective category, while the teacher and student response questionnaire for the practicality of the e-module was 90% and 88% in the practical category. Thus, the Exe-Learning-based mathematics e-module on sequences and series material for grade XI Vocational High School students that has been developed is declared valid, effective, and practical.
Unit usaha Saking Griya merupakan salah satu bidang usaha minuman tradisional dengan produk utama yang ditawarkan adalah wedang uwuh. Wedang uwuh merupakan minuman tradisional yang menyegarkan dan memiliki berbagai manfaat kesehatan. Sayangnya, di era modern seperti sekarang ini, eksistensi dari wedang uwuh mulai terkikis dan bahkan banyak dari generasi sekarang justru belum mengenal wedang uwuh. Hal tersebut dimungkinkan proses untuk memperkenalkan wedang uwuh seringkali dilakukan secara tradisional dan manual secara mulut ke mulut dan tidak mencakup sampai dengan lintas generasi. Sedangkan adanya teknologi komunikasi dan internet memiliki potensi yang besar untuk dapat membawa wedang uwuh agar dapat dikenal oleh masyarakat luas. Dikarenakan adanya berbagai keterbatasan terkait dengan pemanfaatan teknologi untuk proses promosi produk wedang uwuh Saking Griya, maka diperlukan adanya pemaparan dan pendampingan yang dapat digunakan untuk meningkatkan strategi pemasaran dan promosi produk wedang uwuh Saking Griya. strategi yang meliputi proses rebranding logo dan desain produk, pemanfaatan fitur instagram sebagai media social untuk promosi, dan pendampingan untuk pembuatan konten berdasarkan foto dan video menjadi hal yang diperlukan guna meningkatkan strategi pemasaran produk wedang uwuh Saking Griya. Berdasarkan hasil pendampingan, diketahui adanya peningkatan nilai engagement yang terlihat dari naiknya jumlah follower dari social media beberapa waktu setelah strategi pemasaran dilakukan
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