Judul: Pengembangan Program Pengolahan Citra Real-time untuk Deteksi Rintangan pada Traktor Tanpa Awak
Abstrak: Obstacle detection sensor is an important task for development of autonomous vehicles in recognizing its environment. An examination of various research studies on autonomous vehicles/robots shows that there are only five to six different types of effective obstacle detection sensors. These sensors ranged in price from inexpensive to very expensive. Each of them has their own unique advantages and disadvantages for different applications. If a sensor can be effectively used to create accurate maps for the vehicle environment then applying of such sensor on detection of obstacles in farming environment would be possible. The sensors were consisted of CCD camera, Ultrasonic sensors, Scanning laser, 3D Scanning lasers, and Millimeter wave radar. The purpose of this research was to develop the algorithm of real-time image processing that will be used as obstacles avoidance for unmanned tractor. The equipments in this research were divided into two catagories, including hardware and software platforms. The hardware consisted of Yanmar Tractor EF453T types, Acer Aspire 2930 with Express card slot, CCD camera, cctv lens, express card d/34 to fire wire IEEE 1394A Adapter, fire wire cable, tripleks wood, red pointer laser<5mW, LM 7805, resistor 82 ohm, capacitor 100 μF, luxmeter, and akrilik. While the software consisted of Visual C#, Sharp Develop 3.2 version, and Paint Shop Pro 6 version. The procedure used in present study consisted of the following steps, such as identifying a problem through observation, designing a system for obstacle detection system of unmanned tractor, fabrication of obstacle detection system, capturing the RGB (Red, Green, Blue) values in both static, and dynamic conditions, testing the calibration and validation of optical camera, functional testing, testing the static and real-time performances on unmanned tractor. Image processing techniques such as threshold, erotion, and dilation has achieved successfully to get perfect binary image. The white drop in binary image was then used to detect potential obstacle. Our system is capable to recognize an obstacle in tractor path so that it could give a motion command such as advance, turn left, turn right, or stop. For instance, if the tractor detects the obstacle at less than 7 m then the system would give the command to turn left if the obstacle located in right tractor path. In contrast, it would command to turn right if the obstacle position located in the left tractor path. In case of the obstacle is located at throughout the tractor path, the system would give a command to stop. However, if there is an obstacle in the path tractor, but its range is more than 7 m, the system would give the tractor command to advance. The speed of the vehicle in outdoor application of real-time obstacle avoidance system 0.5 m/s and required 1.3 second for one data processing. This system worked perfectly in 500-200 lux (06.15-08.00 am in normal condition). This system can read the range of obstacle with an accurate up to 81.6% for obstacle in range 2 m, 77.1% in 3 m, 71.5% in 4 m, 69.5% in 5 m, 68% in 6 m, and 48.4% in 7 m. The more obstacle
Keyword: 

Judul: Deteksi Rintangan Mengggunakan Kamera CCD untuk Aplikasi pada Traktor Tanpa Awak
Abstrak: Obstacle detection is designed as a guidance for unmanned tractor to knowing the distance of obstacle in front of the tractor. The purpose of this research is to develop vision system that will be used as the guidance for unmanned tractor. CCD camera to acquire image of scene in front of tractor was placed at a tripod with height 1 meter. The position of camera is bow with 50. The image of track for tractor is captured and image was recorded in 640 x 480 pixel resolution. Six red laser pointer were added surrounding CCD camera to get obstacle image. The images were captured from 1, 2, 3, 4 and 5 meter until CCD camera cannot capture the reflection of red laser. There are some factors that effected this research: solar intensity, red laser pointer and CCD camera lens focus. The captured image were processed by image processing program for obstacle detection. The result of image processing program for obstacle detection is a prediction of an obstacle distance in front of the tractor with success rate of 100 % for 1 meter, 80 % for 2 meter, 40 % for 3 meter, 0 % for 4 meter and 5 meter, and the accuracy rate of 68 %. When the solar intensity is high, image processing of obstacle detection could not detect the obstacle from more than 3 meter.
Keyword: 

Judul: Lejeuneaceae Subfamily Ptychanthoideae (Hepaticae) in  West Java
Abstrak: Subfamily Ptychanthoideae of the family Lejeuneaceae (Hepaticae) in West Java is still poorly known. Publications on this subfamily are out of dated and written in the 19th or early of 20th century. The last taxonomic treatment of Ptychanthoideae of West Java was in 1933, many species names have changed since then. Studies on Ptychanthoideae of West Java are urgently needed. Studies on the Ptychanthoideae were based on the specimens collected from West Java. A total number of 361 of specimens deposited in the Herbarium Bogoriense (BO), Herbarium Biotrop (BIOT), Gottingen Herbarium (GOET) and Bangi Herbarium (UKMB) were examined, those are old and several recent specimens collected in West Java. Recent collections were made from Telaga Warna, Ciater, Gunung Halimun Salak National Park, Cibodas Botanical Garden, Bodogol Education Center and Conservation (Gunung Gede Pangrango National Park), University of Indonesia Campus Depok, including several collections from Banten Province. Twenty four species of Lejeuneaceae subfamily Ptychanthoideae are known from West Java, belonging to 8 genera namely Acrolejeunea (Spruce) Schiffn. (2 species), Archilejeunea (Spruce) Schiffn. (1 species), Lopholejeunea (Spruce) Schiffn. (10 species), Mastigolejeunea (Spruce) Schiffn. (3 species), Ptychanthus Nees (1 species), Schiffneriolejeunea Verd. (1 species), Spruceanthus Verd. (2 species) and Thysananthus Lindenb. (4 species). Two new records of Ptychanthoideae: Mastigolejeunea indica Steph. and Thysananthus minor Verdoorn are reported for Java. A determination key to the species is presented including their descriptions and illustrations.
Keyword: