Indonesia has been known as an agrarian country because of its fertile soil and is very suitable for agricultural land, including rice. Yogyakarta is one of the most significant granary regions in Indonesia, especially in the Sleman region. However, one of the main challenges in rice planting in recent years is the erratic rainfall patterns caused by climate anomalies due to the El Nino and La Nina phenomena. As a result of this phenomenon, farmers have difficulty determining planting time and harvest time and planting other plants. Therefore, we make rainfall predictions to recommend planting varieties with Moving Average and Naive Bayes Methods in Sleman District. The results showed that moving averages well use in predicting rainfall. From these results, we can estimate that in 2020 rice production will below. That can saw from the calculation of the probability of naive Bayes on rice plants being low at 0.999 and 0.923. So that the recommended intercrops planted in 2020 are corn and peanuts. We also find that rainfall prediction with Moving Average using data from several previous years in the same month is more accurate than using data from four past months or periods.

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Providing nutrition for COVID-19 patients is one of many actions to reduce the risk due to symptoms of COVID-19. To help meet the nutritional needs of COVID-19 cured patients, we developed a nutritional needs recommendation system and predicted nutritional needs for COVID-19 recovered patients in West Nusa Tenggara, Indonesia with Technique for the Order of Preference by Similarity to Ideal Solution method (TOPSIS). We use data from COVID-19 Task Force in this province along with The Indonesian Dietary Recommendations to help decide which nutrition is needed by recovered patients. The criteria used in the prototype of this system are Age Group weight 3, Vegetable Consumption weight 4, Fat Consumption weight 4, Salt & Sugar Consumption weight 2, and Sports weight 3. After cranking the two patterns used, the Pattern Preference value is obtained 1 = 0.34980639174099 and Pattern 2 = 0.65019360825901 so that the highest preference value that can be used as a recommendation is Pattern 2 with a preference value of 0.65019360825901.

One of the easiest manipulation methods is a copy-move forgery, which adds or hides objects in the images with copies of certain parts at the same pictures. The combination of SIFT and Zernike Moments is one of many methods that helping to detect textured and smooth regions. However, this combination is slowest than SIFT individually. On the other hand, Gaussian Pyramid Decomposition helps to reduce computation time. Because of this finding, we examine the impact of Gaussian Pyramid Decomposition in copy-move detection with SIFT and Zernike Moments combinations. We conducted detection test in plain copy-move, copy-move with rotation transformation, copy-move with JPEG compression, multiple copy-move, copy-move with reflection attack, and copy-move with image inpainting. We also examine the detections result with different values of gaussian pyramid limit and different area separation ratios. In detection with plain copy-move images, it generates low level of accuracy, precision and recall of 58.46%, 18.21% and 69.39%, respectively. The results are getting worse in for copy-move detection with reflection attack and copy-move with image inpainting. This weakness happened because this method has not been able to detect the position of the part of the image that is considered symmetrical and check whether the forged part uses samples from other parts of the image.

Komponen penting yang dibutuhkan dalam sistem informasi atau perangkat lunak adalah basis data. Basis data membantu perangkat lunak dalam mengolah data yang datang dari input yang masuk ke dalam sistem. Untuk menjaga integritas dan keamanan data, programmer wajib memberikan fitur validasi data pada input. Validasi data dapat dilakukan dengan membuat batasan di tingkat aplikasi maupun di tingkat basis data. Sangat penting melakukan validasi data tingkat basis data tidak hanya pada tingkat pemrograman saja. LaundryPOS adalah aplikasi karis berbasis mobile yang diperuntukkan untuk usaha laundry. Penelitian ini akan melakukan analisis keuntungan dari CHECK constraint di database pada aplikasi LaundryPOS dalam aspek kebenaran data. Pengujian dilakukan dengan menggunakan query dan kendala. Hasil dari pengujian ini membuktikan bahwa constraint CHECK mampu menjaga aspek kebenaran pada basis data aplikasi LaundryPOS dengan menyaring data input yang tidak sesuai dengan format yang ditentukan.Kata Kunci—CHECK constraint, integritas data, validasi data, aspek kebenaran data, MySQLAn importantcomponents in the information system or software is database. The database helps the software process data that comes from the input that enters the system. To maintain data integrity and security, programmers must provide data validation features on the input. Data validation can be done by creating constraints at the application level or at the database level. It is very important to do database level data validation not only at the programming level. LaundryPOS is a mobile-based cashier application intended for laundry businesses. This study will analyze the benefits of CHECK constraints in the database on the LaundryPOS in terms of data correctness. Tests carried out using the query and constraints. The results of this test demonstrate that CHECK constraint is able to maintain the Correctness Aspects of the LaundryPOS database by filtering input data that does not match the specified format.Keywords—CHECK constraints, data integrity, data validation, aspek kebenaran data, MySQL