Degree certificate legalization system with encryption security feature using Advanced Encryption Standard (AES) in Semarang University has a purpose to support academic to do online document legalization through a system. The main problem which occurs in academic administration is a long document legalization process that causes an ineffective and inefficient legalization process. To solve the problem, a system that can encrypt a document for better security is required. This system is built with the Advanced Encryption Standard algorithm with a 128-bit sized key to encrypt confidential information inside the document. During the encryption process, this algorithm operates using 4x4 bit array blocks and passing many encryption processes for at least 10 (ten) times. The application is analyzed with object-oriented analysis and modeled with Unified Modeling Language.  The result of this research is a system which can secure document with AES algorithm with a 256-bit sized key. The security element in this algorithm will make easier to identify the owner of the document. The secured document is easily accessible through PHP-based web or available QR code. When decrypting the document, the application will activate the camera function and decrypt the information document.

<p>Pengabdian ini dilatarbelakangi oleh permintaan salah satu guru SMKN 6 Semarang, agar siswa di SMKN 6 Semarang ini dibekali pengetahuan melalui pelatihan sebelum bekerja di industry <em>hospitality</em> khususnya mengenai <em>service quality</em> yang terdiri dari faktor <em>Reliability,<strong> </strong></em><em>Assurance</em>, <em>Tangible, Empathy</em> dan <em>Responsivenes.</em></p><p><strong>Tujuan:</strong> Tujuan dilakukannya pelatihan ini adalah menambah pengetahuan dan wawasan dalam memberikan pelayanan kepada tamu sehingga siswa siap kerja di industri <em>hospitality </em>sesuai kompetensi yang diharapkan. Dengan bekal pengetahuan tentang <em>service quality</em> di industry <em>hospitality </em>para siswa diharapkan memperoleh wawasan dan pengetahuan tentang pelayanan prima yang nantinya akan dipergunakan pada saat mereka bekerja melayani tamu.</p><p><strong>Metode:</strong> Metode yang dilaksanakan dalam kegiatan ini adalah metode ceramah<strong>. </strong>Masing-masing siswa mengikuti dengan antusias selama pelatihan berlangsung. Kegiatan dilaksanakan dalam 1 (satu) hari dengan durasi Peningkatan kemampuan adalah 4 (empat) jam, terdiri dari : 30 menit perkenalan, 30 menit untuk persiapan buku <em>check list</em> kebutuhan<em> </em><em>Service Quality, </em>180 menit praktek dan keseluruhan penyusunan kebutuhan <em>Service Quality.</em></p><p><strong>Hasil:</strong> Hasil dari pengabdian ini adalah rata-rata seluruh peserta pelatihan memberikan tanggapan positif tentang kegiatan pelatihan pengetahuan dan praktek <em>Reliability, Assurance</em>, <em>Tangible, Empathy, Responsivenes</em> serta memperkenalkan teknologi informasi untuk mendukung <em>service quality</em> sehingga pelaksanaan pengabdian kepada masyarakat ini dinyatakan berhasil mencapai tujuan dan target sesuai yang telah ditetapkan.</p><p><strong>Manfaat/Kontribusi: </strong>Manfaat pengabdian ini adalah siswa-siswi SMKN 6 Semarang diberi rangkaian kegiatan untuk mendapatkan pengetahuan tentang <em>Service Quality</em> dalam berbagai bidang sehingga mereka akan terbiasa menghadapi masalah yang terjadi pada saat mereka berada di dunia industri khususnya industri perhotelan.</p><p><strong> </strong></p><p> </p><p><strong>Kata Kunci: </strong> Industri <em>hospitality</em>, <em>Service Quality</em>, kompetensi</p>

This The speed of information, the accuracy of data, the ease of information services, and accountability are very important reasons for the implementation of the system. Semarang University (USM) is a private university in Semarang that has the most 2 students in Central Java. Based on the 2019 USM tracer data showing horizontal alignment, namely how close the relationship between the field of study and alumni work is, it appears that there is still a discrepancy in the ability of graduates with stakeholders.  The Apriori algorithm is the best-known algorithm for finding high-frequency patterns  Rules that state associations between attributes are often called affinity analysis or market basket analysis. The use of the Apriori Algorithm in data mining calculations using data from the Semarang University tracer that the limit of the minimum support is 50% and the minimum confidence is 100% so that it forms 4 rules. From the four rules produced that modeling using the Apriori Algorithm can produce several rule formations so that it can provide an evaluation to the University for compiling steps, this can be seen because the resulting rules are different because each graduate relationship with the desired desires and different styles.
 

This The speed of information, the accuracy of data, the ease of information services, and accountability are very important reasons for the implementation of the system. Semarang University (USM) is a private university in Semarang that has the most 2 students in Central Java. Based on the 2019 USM tracer data showing horizontal alignment, namely how close the relationship between the field of study and alumni work is, it appears that there is still a discrepancy in the ability of graduates with stakeholders.  The Apriori algorithm is the best-known algorithm for finding high-frequency patterns  Rules that state associations between attributes are often called affinity analysis or market basket analysis. The use of the Apriori Algorithm in data mining calculations using data from the Semarang University tracer that the limit of the minimum support is 50% and the minimum confidence is 100% so that it forms 4 rules. From the four rules produced that modeling using the Apriori Algorithm can produce several rule formations so that it can provide an evaluation to the University for compiling steps, this can be seen because the resulting rules are different because each graduate relationship with the desired desires and different styles.
 

The most important part in software engineering is a software defect prediction. Software defect prediction is defined as a software prediction process from errors, failures, and system errors. Machine learning methods are used by researchers to predict software defects including estimation, association, classification, clustering, and datasets analysis. Datasets of NASA Metrics Data Program (NASA MDP) is one of the metric software that researchers use to predict software defects. NASA MDP datasets contain unbalanced classes and high dimensional data, so they will affect the classification evaluation results to be low. In this research, data with unbalanced classes will be solved by the AdaCost method and high dimensional data will be handled with the Average Weight Information Gain (AWEIG) method, while the classification method that will be used is the Naïve Bayes algorithm. The proposed method is named AWEIG + AdaCost Bayesian. In this experiment, the AWEIG + AdaCost Bayesian algorithm is compared to the Naïve Bayesian algorithm. The results showed the mean of Area Under the Curve (AUC) algorithm AWEIG + AdaCost Bayesian yields better than just a Naïve Bayes algorithm with respectively mean of AUC values are 0.752 and 0.696.

During the screening of new students, each state and private institution is required to carry out promotion in order to obtain the number of students according to the predetermined target. Problems that often occur when determining the location of promotion, the New Student Admission Team (PMB) determine the location of promotions randomly without considering several factors that can affect the number of students who will join. This is often done mainly by private university such as Semarang University (USM). To overcome this, a system is needed to provide information for the New Student Admission Team (PMB) in making decisions on the location of USM promotions. This system applies the Additive Ratio Assessment (ARAS) method and criteria that can affect the number of students who will later register because the determination of the location of the promotion is right on target. Criteria and weights include: Distance (cost) with a weight of 30%, number of students (benefit) with a weight of 40%, school status (benefit) with a weight of 20%, and a source of information (benefit) with a weight of 10%. The programming language used by PHP and data bases uses MySQL. The final result of this study is a decision support system that can provide information to the PMB team about the location of the school that has the potential for USM promotion.

Kegiatan akademik yang dilakukan oleh Universitas menjadi tolak ukur keberhasilan kelulusan mahasiswanya. Fakultas Teknologi Informasi dan Komunikasi Universitas Semarang mempunyai 2 jurusan dan 3 program studi sistem informasi. Di Jurusan Teknologi Informasi seringkali mahasiswa mengalami kebingungan dalam mengambil mata kuliah pilihan, yang mana tidak didasarkan pada kemampuan prestasi yang dimiliki namun berdasarkan pada jumlah mahasiswa yang mengambil mata kuliah tersebut. Hal ini akan mengakibatkan pengelola kesulitan memploting kelas yang akan dibuka semester yang akan berjalan. Yang sering terjadi adalah mahasiswa kehabihan kuota untuk mata kuliah pilihan tertentu dan pengelola harus menambah kelas untuk mata kuliah tertentu. Oleh karenanya dibutuhkan suatu pola dengan menggunakan data matakuliah pilihan yang akan diambil di semester selanjutnya menggunakan metode Apriori. Tujuannya adalah bisa menemukan pola data mahasiswa yang akan mengambil mata kuliah sehingga memudahkan pengelola program studi dalam memprediksi kelas yang dibuka.

Managing car stock is the biggest challenge for a company, especially in PT. New Ratna Motor engaged in automotive. The problem is related to the process of selling goods where the sales and car stock are out of balance. Comparisons between cars entering and cars coming out (sales) are larger cars that enter so that there is a buildup of stock in the number of cars which results in company losses which include running taxes that must be paid each year, as well as the accumulation of certain types of cars and spending on car parking. The ELECTRE method is applied as a method in determining what types of cars should be stocked by the company based on customer satisfaction, if the customer is satisfied with one type / type of car and quickly gets the unit, chances are the customer will buy or reference the product. The final result of this study is the ranking of the alternatives for determining the stock of the car.