Digital watermarking is an important field of technological development that has now grown in the digital era. Digital era encourage the spread digital images on internet by the websites with a large scale. On the other hand, digital images are objects that are very easy to change or manipulate, and even copied irresponsibly. Meanwhile it is very difficult to prove the image has been changed by existing equipment at this time, and it is difficult to prove its ownership. This is an important issue, when the image is one of the evidences for legal cases, news reporting and medical filing, where the image must be ensured that the digital image is not subject to change or manipulation. In this paper, we present the application of digital watermarking to authentication and ownership validation of digital image so the image can be ascertained its validity. This research applies blind watermark scheme by using secret key that inserted at least-significant bits (LSB) of host image therefore the watermark is invisible watermark. The result of watermarked image has a small decrease in quality with the mean value of PSNR and MSE about 34.08 and 14.62.

The need of student attendance information in schools is a major factor in success of the academic process. Often there are validation and identification errors in the student attendance process (human error or manipulation process) as well as the slowness of information obtained, since the attendance is recorded manually in each class. This has an impact on success of the academic process directly and the community at large. Because the importance of attendance information, various studies have offered the system in the process of student attendance, with various technologies. One popular technology and believed to be validating and identifying well is the fingerprint. Therefore, this paper proposes the introduction of attendance system in schools by utilizing fingerprint technology integrated with android smartphone so that information can be delivered quickly. This study use Fingerprint X-100C as a means of identification of student data at the time of absence then the attendance data will be sent to the system database by SOAP (Simple Object Access Protocol) Web Service. The system will validate and transmit that information on the android Smartphone via the newly created XML Service. The success rate of this system in processing absence reach around 90,47% with delay time of sending information 0.0024 s This system has been tested and applied to SMK N 1 Indramayu.

Portable vacuum grain conveyor (PVGC) work as transporting grain materials such as grain, wheat, sorghum, corn and its kind using air media. The advantages of this machine are that it can move material quickly, the material does not fall in the transportation process, it can move from the bottom to the top or vice versa, it does not require a feed hopper, and the machine can move places. How the PVGC machine works by utilizing the suction and thrust of a vacuum blower. The seed material is sucked in by the input hose and then into the cyclone to separate the air and seed material. Air from the cyclone enters the vacuum blower through the input hole and is blown into the output line to push the material falling from the cyclone through the rotary airlock. Seed material out through the output hose is directed to the desired place. Performance testing of the PVGC engine includes noise, the air suction speed of the input hose and the thrust speed of the output hose, the engine capacity, and thermal testing. The highest noise test results in the electric vacuum blower motor was 95.5 dBA ±1, the air suction speed at the input hose was 38 m/s ±3, the air thrust speed at the output hose was 44 m/s ±2, the capacity of the PVGC machine could transport IR64 of grain type with weighing 88 kg/minute. The hottest component was in the vacuum blower with a temperature of 52.50C.

Sistem informasi penelitian internal adalah aplikasi yang digunakan untuk mengelola data usulan penelitian dalam lingkup Politeknik Negeri Indramayu (POLINDRA) mulai dari pengajuan, penilaian, pelaksanaan sampai pelaporan. Pada mulanya sistem yang ada di Politeknik Negeri Indramayu masih belum terintegrasi dengan baik dalam hal pengajuan usulan dari dosen, karena proses pengiriman masih menggunakan email . Kemudian untuk proses persetujuan usulan tersebut akan dilihat oleh Reviewer eksternal. Selanjutnya untuk proses penilaian sendiri dengan dilakukan dengan cara mengisi form penilaian yang disediakan oleh P3M, kemudian akan dikirimkan kepada Reviewer melalui email. Pemilihan sistem website untuk pengembangan aplikasi ini selain lebih mudah dalam pengoperasiannya dan juga sifat website yang fleksibel jadi salah satu alasannya. Permasalahan yang diangkat dalam topik ini adalah pengiriman usulan masih manual menggunakan email sehingga kemungkinan masih terjadi kesalahan data, data hilang atau rusak. Dengan adanya aplikasi ini diharapkan dapat mengelola data usulan agar cepat, efisien dan optimal data tersimpan pada sistem. Pembuatan aplikasi ini menggunakan metode Kanban. Kanban dipilih karena mampu merespon perubahan proyek dengan mudah, mudah diterapkan, dan sesuai dengan kebutuhan dan perancangan perangkat lunak tanpa merubah atau mengulang lagi dari awal. Aplikasi ini juga dibuat menggunakan Framework Laravel dan Database MariaDB. Pengujian yang dilakukan pada penelitian ini menggunakan black-box testing dengan hasil pengujian fitur-fitur yang tersedia berhasil dan program berjalan dengan baik. Dengan adanya Sistem Informasi Penelitian Internal melalui fitur pengusulan yang menampilkan daftar usulan penelitian yang ada pada pengusul. Sehingga dalam pengiriman, penilaian usulan dan pengelolaan usulan penelitian agar proses pengiriman, penilaian dan persetujuan usulan yang diajukan dosen Politeknik Negeri Indramayu menjadi lebih mudah, cepat, efisien, dan terintegrasi dengan baik.

Nowadays, pre-collision warning is one of the substantial aspects of the transportation sector. One of the steps to detect the collisions is by classifying and predicting the collisions. There are many supervised machine learning algorithms used, such as Least Square – Support Vector Machine (LS-SVM). Radial Based Function (RBF) is one of the LS-SVM kernels, which is a well-known method to support reliable performance. However, C and Gamma of its parameters are chosen randomly. This makes the performance of the classifier less optimal. To overcome that problem, this paper proposed a cuckoo search algorithm for optimizing two parameters to get optimal accuracy. The proposed approach is applied to 8437 transportation records and evaluated by using Accuracy. In addition, the performance of the proposed method is compared to other well-known meta-heuristic optimization algorithms, namely: Bat Algorithm (BA-SVM) and Firefly Algorithm (FA-SVM). Experimental results show that the Cuckoo Search Algorithm (CSA-SVM) yields the best performance for each of the 10-folds cross-validation by reaching 84.817% for accuracy, compared to the Bat Algorithm and Firefly Algorithm.