Analisis Unjuk Kerja GCMOS

Paulisan ini adalah suatu analisa terhadap divais Graded-Channel Metal-Oxide- Semiconductor Fietd-Effea-Transistor atau disingkat GCMOSFET- Telanlogi GCMOSFET ini bertrembang sebagai salah satu usaha untukmenenuhi kebutuhan divais dalam aplikas

Simulasi Graded Channel Mosfet Dengan S-pisces 2b

Graded Channel MOSFET simulation with S-Pisces 2B. Graded-Channel Metal-Oxide-Semiconductor Field-effect-Transistor or GCMOSFET is being discussed in this paper. GCMOSFET technology has been developed to meet thegrowing demand for low power and high performance application. In this paper, it will be shown that, compared toungraded MOSFET, the GCMOSFET device offers the advantage of significantly higher drive current. The higher drivecurrent is achieved because the effecctive channel length of GCMOSFET is shorter than the ungraded MOSFET's.From the simulation result with S-PISCES 2B and MATLAB, it can been shown that the ID from GCMOSFET ishigher than the ID from ungraded MOSFET. As an example, with VG = 4 V and VD = 4 V, ID from MOSFET is equalwith 9.78 e-06 A and ID from GCMOSFET is equal with 16.56 e-06 A. Beside that, as an example, to get ID = 1.13 e-05A with MOSFET will need VG = 4 V and VD = 4.7 V, and with GCMOSFET VG = 4 V and VD = 1.2 V will be needed.This result has shown that GCMOSFET needs lower supply voltage than the ungraded MOSFET which means thatGCMOSFET needs lower power consumption than ungraded MOSFET. From the simulation results, it can be provedthat GCMOSFETwith shorter LGC (graded channel region length) will give larger ID than ID from GCMOSFET withlonger LGC. As we can see that for VGS = 4 V and VDS = 2 V, GCMOSFET with LGC = 4 μm will give ID = 16,56E-06A, GCMOSFET with LGC = 3,5 μm will give ID = 17,51E-06 A, and GCMOSFET with LGC = 3 μm will give ID =18,49E-0

SIMULASI RANGKAIAN DIGITAL MESIN PENJUAL KOPI DENGAN XILINX

Rangkaian Digital Mesin Penjual Kopi”merupakan rangkaian digital yang dirancang untuk membuat vending machineyang dapat mengeluarkan 3 pilihan kopi, yaitu kopidengan rasa “original”, “vanilla” dan “cappucino” dengan memasukkan uang Rp.5000,-. Rangkaian ini dirancang menggunakan gerbang logika dan D flip-flop dengan melalui beberapa tahap diantaranya: identifikasi masalah, state diagram, tabel kebenaran, K-map, IFL (Input Forming Logic), OFL (Output Forming Logic), simulasi dan analisa

Graded Channel MOSFET simulation with S-Pisces 2B

Graded Channel MOSFET simulation with S-Pisces 2B. Graded-Channel Metal-Oxide-Semiconductor Field-effect- Transistor or GCMOSFET is being discussed in this paper. GCMOSFET technology has been developed to meet the growing demand for low power and high performance application. In this paper, it will be shown that, compared to ungraded MOSFET, the GCMOSFET device offers the advantage of significantly higher drive current. The higher drive current is achieved because the effecctive channel length of GCMOSFET is shorter than the ungraded MOSFET’s. From the simulation result with S-PISCES 2B and MATLAB, it can been shown that the ID from GCMOSFET is higher than the ID from ungraded MOSFET. As an example, with VG = 4 V and VD = 4 V, ID from MOSFET is equal with 9.78 e-06 A and ID from GCMOSFET is equal with 16.56 e-06 A. Beside that, as an example, to get ID = 1.13 e-05 A with MOSFET will need VG = 4 V and VD = 4.7 V, and with GCMOSFET VG = 4 V and VD = 1.2 V will be needed. This result has shown that GCMOSFET needs lower supply voltage than the ungraded MOSFET which means that GCMOSFET needs lower power consumption than ungraded MOSFET. From the simulation results, it can be proved that GCMOSFETwith shorter LGC (graded channel region length) will give larger ID than ID from GCMOSFET with longer LGC. As we can see that for VGS = 4 V and VDS = 2 V, GCMOSFET with LGC = 4 μm will give ID = 16,56E-06 A, GCMOSFET with LGC = 3,5 μm will give ID = 17,51E-06 A, and GCMOSFET with LGC = 3 μm will give ID = 18,49E-0

Glasses for the blind using ping ultrasonic, ATMEGA8535 and ISD25120

For doing their activities, blind people need tools. The idea for designing this device is for helping the blind person. This device is a glasses specially for blind person which gives information in the form of voices through an earphone if there is an obstacle in the range of 0–58 cm. The device is using PING ultrasonic sensor, ATMEGA8535 microcontroller, and ISD25120 for recording and saving the voices. After designing and making the device, we tested the device to take the data. We use three PING ultrasonic sensors which are put at the sides of the glasses. The device will give eight different kinds of voices through the earphone. The voices depend upon the output of the PING ultrasonic sensors

Analysis the effect of reflector (flat mirror, convex mirror, and concave mirror) on solar panel

At the time of the sun a straight line with solar cells may not necessarily produce the maximum output. Various ways continue to be done in order to get the maximum output. The maximum utilization of output from solar cells will accelerate the function of the solar cell. The use of reflectors is an excellent way to maximum output with effective time. The author will analyze solar cells with flat mirror, convex mirror, concave mirror, and without reflector. Each reflector is given varying treatment by calibrating the angle of the reflector to the solar cell by 60o, 90o, and 120o. After testing and data retrieval turns reflector very influential on the output of solar cells. The solar cell output power increases with each different reflector. Maximum output is obtained in a concave mirror with an angle is 90o

SIMULASI GRADED CHANNEL MOSFET DENGAN S-PISCES 2B

Graded Channel MOSFET simulation with S-Pisces 2B. Graded-Channel Metal-Oxide-Semiconductor Field-effect-Transistor or GCMOSFET is being discussed in this paper. GCMOSFET technology has been developed to meet thegrowing demand for low power and high performance application. In this paper, it will be shown that, compared toungraded MOSFET, the GCMOSFET device offers the advantage of significantly higher drive current. The higher drivecurrent is achieved because the effecctive channel length of GCMOSFET is shorter than the ungraded MOSFET's.From the simulation result with S-PISCES 2B and MATLAB, it can been shown that the ID from GCMOSFET ishigher than the ID from ungraded MOSFET. As an example, with VG = 4 V and VD = 4 V, ID from MOSFET is equalwith 9.78 e-06 A and ID from GCMOSFET is equal with 16.56 e-06 A. Beside that, as an example, to get ID = 1.13 e-05A with MOSFET will need VG = 4 V and VD = 4.7 V, and with GCMOSFET VG = 4 V and VD = 1.2 V will be needed.This result has shown that GCMOSFET needs lower supply voltage than the ungraded MOSFET which means thatGCMOSFET needs lower power consumption than ungraded MOSFET. From the simulation results, it can be provedthat GCMOSFETwith shorter LGC (graded channel region length) will give larger ID than ID from GCMOSFET withlonger LGC. As we can see that for VGS = 4 V and VDS = 2 V, GCMOSFET with LGC = 4 μm will give ID = 16,56E-06A, GCMOSFET with LGC = 3,5 μm will give ID = 17,51E-06 A, and GCMOSFET with LGC = 3 μm will give ID =18,49E-06Keywords: S-Pisces 2B, MOSFET, GCMOSFE

Classification of nutmeg ripeness using artificial intelligence

Nutmeg seeds can produce a lot of oil if they have optimal maturity. In other words, they have little moisture content. Based on observations made at one of the refineries in Sukabumi, farmers do not pay attention to the maturity level of nutmeg seeds after drying which can cause a decrease in the quality of nutmeg seeds and the quality of the oil produced. This study aims to make it easier for nutmeg farmers to classify the maturity of nutmeg seeds. This study used the convolutional neural network (CNN) method to help with classification problems and several image processing methods. This program will be run through an Android application. When the application containing this CNN model is run, the camera system will turn on, and the program will classify in real-time nutmeg objects into 1 of 3 class labels namely LowQuality, MidQuality, or HighQuality class labels classifying. The results will be displayed on the application screen, the results are displayed in the form of class names and scores. The results of CNN model training accuracy are 97.92%

DEDUCTIVE OR INDUCTIVE? PROSPECTIVE TEACHERS’ PREFERENCE OF PROOF METHOD ON AN INTERMEDIATE PROOF TASK

The emerging of formal mathematical proof is an essential component in advanced undergraduate mathematics courses. Several colleges have transformed mathematics courses by facilitating undergraduate students to understand formal mathematical language and axiomatic structure. Nevertheless, college students face difficulties when they transition to proof construction in mathematics courses. Therefore, this descriptive-explorative study explores prospective teachers' mathematical proof in the second semester of their studies. There were 240 pre-service mathematics teachers at a state university in Surabaya, Indonesia, determined using the conventional method. Their responses were analyzed using a combination of Miyazaki and Moore methods. This method classified reasoning types (i.e., deductive and inductive) and types of difficulties experienced during the proving. The results conveyed that 62.5% of prospective teachers tended to prefer deductive reasoning, while the rest used inductive reasoning. Only 15.83% of the responses were identified as correct answers, while the other answers included errors on a proof construction. Another result portrayed that most prospective teachers (27.5%) experienced difficulties in using definitions for constructing proofs. This study suggested that the analytical framework of the Miyazaki-Moore method can be employed as a tool to help teachers identify students' proof reasoning types and difficulties in constructing the mathematical proof