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The existing oil waste water contains oil, solids, water and heavy metals. This oil waste is a contaminant material that can cause negative impacts to the aquatic environment as well as the existing living creatures around it so that it requires a careful and fast handling to clean. The research resulted in the tracking system on the image-based-ship robot by using the method of   histogram and fuzzy logic controller that can detect the image of waste water well. The result of the testing of the ship robot done on the pool indicated   that it took about ± 196.92 seconds for the robot to detect the image of oil waste objects. The oil waste suctioning process took a maximum of 60 seconds for once.

Kasus pencurian kendaraan terjadi karena berbagai faktor, yaitu: sistem keamanan kendaraan yang minim, kurangnya pengawasan dan lokasi mudah untuk melakukan pencurian. Pencurian kendaraan bermotor, sering terjadi pemilik kendaraan kesulitan dalam tracking kendaraan yang dibawa oleh pencuri. Pembuatan sistem pengaman kendaraan bertujuan sebagai pengaman kendaraan pada saat parkir dan monitoring koordinat kendaraan secara real time yang terintegrasi web server thingspeak dan pesan telegram sebagai kontrol sistem. Rancang bangun alat diawali mencari referensi tinjauan pustaka, mendesain sistem, yang meliputi perancangan hardware dan perancangan software, selanjutnya sistem akan diuji. Pengujian dan analisa meliputi pengujian respon alat terhadap pesan telegram, pengujian lock sinyal GPS, pengujian akurasi pembacaan data GPS, pengujian sensor getar SW-420 pada sistem dan pengujian sistem secara keseluruhan. Hasil pengujian respon alat terhadap pesan telegram dengan rata-rata waktu 19.8 second. Hasil pengujian lock sinyal GPS dengan rata-rata waktu 266.67 second. Hasil pengujian akurasi pembacaan data GPS dengan rata-rata selisih jarak 19.99 meter. Hasil pengujian sensor getar SW-420 Pada sistem, jika kondisi sensor mendeteksi getaran maka output sensor High sehingga buzzer aktif dan notifikasi pesan telegram masuk ke akun telegram pengguna. Pengujian sistem secara keseluruhan meliputi pengujian mode kontrol sistem dan pengujian mode informasi sistem

A pattern recognition technique in the field of machine learning and can be defined as "the act of taking raw data and act upon data classification". Much research has been done on the topic of pattern recognition using a variety of methods one of which is by using the cellular automata. In this study used cellular automata method for finding and extracting characteristics of an image of the signature and realized in a pattern recognition software that can verify the authenticity of the signature image by using cellular automata method for the extraction process characteristics. In this study used data 57 respondents with 6 signatures used as a reference image. Three pieces of the original signature image and 10 pieces of counterfeit signature image is used as the test images (query). From the testing that has been done precision 88.30%, recall 65.37% and accuracy 71.31%.