Determination of damage and losses after natural disasters is carried out to determine the type of damage and the amount of loss after natural disasters that must be borne by the government. In order for the type of damage and the magnitude of the loss after natural disasters according to the data in the field, a study is carried out that implements the Decision Support System (DSS) with the Weighted Product (WP) method. The results obtained are tests of pattern data which are calculated using Weighted Product (WP) compared to 3 different test data, namely using damage and loss data after the natural disaster in East Java in 2010, 2011. The results of the 3 test data used the first amount of 373 data, which produces precision 56.50%, recall 50.50%, accuracy 53.30%, and f-measure 39.10%. For the second data using the data 77, which produces precision 52.80%, recall 36.30%, accuracy 43.02%, and f-measure 36.30%. And for the third data using data from data 24, which produces 50% precision, 50% recall, 50% accuracy, and 50% f-measure. From the 3 types of test data used can be concluded that the Weighted Product (WP) method has a high level of precision, f-measure, recall, and accuracy if the amount of data used is increasing.

At present many old semester students are starting to be undisciplined in attending lectures, this is due to the increasing burden of their assignments causing the enthusiasm of students to relax. This can create serious problems in the department because it can affect the accreditation level of the department. The purpose of this journal, which is to help the department admins to determine students who have problems in the field of lectures, so that the department can find out how many problem students can affect the accreditation of majors. In this journal, we implement the Decision Support System for manufacturing the system. With the TOPSIS method for calculations on the system, and using the Confusion Matrix for testing the system. From testing using confusion matrix, it can be concluded that precision produces 75%, recall produces 75%, accuracy produces 73%, and f-measure produces 75%. This shows that the system has a pretty good ability because it has exceeded the value of 70%.

Lots of applications or programs that are very useful to simplify human work. This includes applications that are made within a company. A company needs an intelligent system or an agent that controls the company's system. In a company has employees who work. This research will discuss the Dynamic Decision Support System in determining the best employees using one of the web-based Multi-Criteria Decision Making methods, which is Simple Additive Weighting (SAW). By using 2 types of data namely pattern data and test data. The data inputted were 15 data consisting of 10 test data and 5 pattern data. Then a confusion matrix can be obtained in the form of an accuracy value of 25%, a precision of 100%, a recall of 14%, and an F Measure of 24.5%.

Penerapan scraping dan Backpropagation Neural Network dapat menjadikan penilaian Self- Assessment Questionnaire (SAQ) website Pemerintah Daerah Provinsi Jawa Timur lebih smart jika dibandingkan dengan model assessment yang sudah ada. Langkah awal yaitu melakukan scraping website Pemerintah Daerah Provinsi Jawa Timur untuk mendapatkan nilai SAQ. Hasil scraping tersebut akan digunakan sebagai data uji pada metode Backpropagation Neural Network, kemudian hasil data uji akan di proses menggunakan 4 jenis model data yang berbeda-beda dari segi jumlah iterasi dan hidden layer untuk mendapatkan akurasi terbaik. Pada model data A menggunakan iterasi 1000 dan 5 hidden layer menghasilkan nilai Mean Squared Error (MSE) 0,0117, Mean Absolute Percent Error (MAPE) 39,36% dan Akurasi 60.64%. Model data B menggunakan iterasi 1000 dan 7 hidden layer menghasilkan nilai MSE 0,0087, MAPE 29,49% dan Akurasi 70,50%. Model data C dengan menggunakan iterasi 2000 dan 9 hidden layer menghasilkan nilai MSE 0,0064, MAPE 24,46% dan Akurasi 75,53%. Model data D menggunakan iterasi 2000 dan 9 hidden layer menghasilkan nilai MSE 0,0036, MAPE 18,71% dan Akurasi 81,28%. Dari hasil ujicoba tersebut bahwa model data D yang menggunakan iterasi 2000 dan 9 hidden layer menghasilkan tingkat akurasi yang terbaik sehingga model data D dapat dijadikan acuan hasil penilaian website Pemerintah Daerah Provinsi Jawa Timur tahun 2021.

Information technology is an important part in the management and development of the company's business. However, there are several problems and challenges in managing information technology resources. So it is necessary to design a good and structured information technology governance to overcome it. Good technology governance can take advantage of opportunities in a planned, coordinated, prioritized and cost-effective way. This paper proposes a comprehensive and integrated design of information technology governance for UMKM plants. The design of IT governance is based on five focus areas of IT governance and also uses the Service Oriented Architecture (SOA) method as a guide in creating UMKM web services. This is because many applications of IT governance in UMKMs have not run optimally, even most UMKMs do not implement information technology strategies in their businesses. Therefore, it is necessary to design information technology governance for UMKMs to support the development of UMKMs. The design of IT governance in this paper is based on five focus areas of information technology governance and also uses the Service Oriented Architecture (SOA) method as a guide in making UMKM web services. The importance of this research is to develop UMKM business by utilizing information technology governance.