Fakultas Ilmu Komputer

On this occasion, the author developed an instructional media of teaching of microcontroller 8051-based control teaching using a simulator called MCU 8051 IDE that runs on Windows XP (MCU 8051 IDE runs on various operating systems) by implementing the function of C programming language in accessing port " bit-wisely " in reading port bit P1.0 status that mimics as sensory input, displaying or reporting the sensor status at port bit of P2.0 in the form of LED status On for high, Off for low, and P0 in the form of character of H for high and character of L for low to support the implementation of active learning in higher education– ALFHE. This program runs in closed loop mode, and it will be stopped only by clicking the stop button of the MCU 8051 IDE and can be run again by re-clicking it again. The developed Learning Media is in the form of simulation control program in C language embedded in MCU 8051 named Small Devices C Compiler (SDCC). MCU 8051 can be downloaded for free at sourceforge.net site [3]. According to the writer's observation the developed simulation program has been stable and successful in increasing the participation and engagement of the students in the learning process, allowing and enabling the teacher, the lecturer, or the instructor to apply their teaching strategies (active learning) more flexible, comfortable, and successfully overcome the lack of funds to meet the need of equipment in supporting active learning [1][2][6]. The simulation program has also been successful in reducing errors in developing or manufacturing the real equipment (reducing costs) [7] .

In recording the EEG signals are often contaminated by a large of signals called artifacts such that the brain activity (source) difficult to estimate. There are different kinds of artifacts such as power line noise, electromyogram, electrocardiogram and electrooculogram. In this research, an adaptive recurrent neural network (ARNN) for estimation of source and reduction of noise from recorded EEG signals is proposed. In the experiment, the EEG signals are recorded on three conditions, which is normal conditions, closed eyes, and blinked eyes. After processing, the dominant frequency of the EEG signal is obtained in the range of 12-14 Hz either on normal conditions, closed eyes, and blinked eyes. The experimental results show that the ARNN method was effectively estimated the brain activity according to the given stimulus and remove the artifacts from all subjects.

Faculty of Computer Science is one of the faculties at the University Methodist Indonesia. At this school there is a sistemabsensi faculty and students who are still running it manually, which dalampenerapan attendance system, there are some things that become obstacles, which include the effectiveness and efficiency of time and prosespengabsenan. With the above reasons, the authors try to memberikanalternatif solving problems by creating a software absensiyang system will record data and a list of faculty and student attendance, number and recapitulation presence of faculty and students, which will be made in a systematic and computerized WITH barcode, which will eliminate the process attendance of lecturers and students who have been running it manually in the Faculty of Computer Science. Barcode will method of reducing levels of fraud at the time of charging absent students, and to improve discipline in attendance. At this writing will also be explained stages of processing, mulaidari process of analysis, planning, design by using VB.Net and MySQL for its database, to manufacture DFD (Data Flow Diagram) as an indication of the current procedure that akanditerapkan data on the system, and the analysis of inputs and output, to know anything what the data will be input and output.

Measures the percentage similarity becomes important documents today because of the many digital documents in particular scientific work. Measurements were performed by using keywords solution of some of the documents that the user selected after the competition keywords. The process of determining keywords algorithm solution with genetics to produce the latest generation of the best with Jaccard Function. Then the similarity calculation process will be done using the keyword query comparing the solution with an existing document in a database that is in the post title, abstract, keywords and references. Similarity calculation method used is the Percentage of Similarity (POSI) Formulation. The number of keywords found on each document will be distributed in the whole of keywords that are found to produce a percentage of similarity. From the tests results obtained similarity of documents idDoc-661 amounted to 32.26%, 24.19% in the second sequence idDoc-665 and the third number of 19.35% on idDoc-663 and fourth at 12.90% in idDoc-667 and the latter by 11.29% in idDoc-666. Based on these tests can find out similarities with the other documents.

In general, students are more tightly when faced with personal problems, financial problems, family and moral issues. So often there is a failure as a result of the issue unresolved. So expect the need for an application or system for media consulting experts to find a solution in accordance with their respective problems. So that problems can be detected early, it can use an application that has been designed based on the data of experts that has been incorporated into the database of knowledge. These types of problems and solutions are dynamic based on user needs and new knowledge experts found. Categories are often problematic issues of personality, economics and finance, family, education and other social issues. Data experts will first be incorporated as early knowledge that has been given by the experts. Sources of data obtained from the experience of experts encountered during counseling in college. Then the inference engine will draw final conclusions based on searches that have been determined on the basis of the rules. The goal is student can perform expert counseling through applications designed. The method used in the search is a method Best First Search and search by the method of backward chaining. Results from this study is a useful application for counseling for troubled students.

ABSTRAK Improving the quality of decisions in an organization's decision-making is part of the management process. Any decisions always have implications for both organizational implications than previously thought (predictable) or not. One implementation is to determine high performing employees with multiple criteria. With the help of a computer as a data processor is helpful in doing the calculations, and sequence analysis according to the weight and value of each employee. The method used is Analytical Hierarchy Process (AHP) because it supports multi-criteria decision making. Settlement calculations can be run quickly through the application made. This method can help with systematic framework as the basis of human thinking is the process of establishing a numerical value to construct rank on any alternative options. And it can also solve the problem of complex structured by a hierarchy of criteria, helping each employee assessment, adding variables, change criteria and criteria weights. Applications are designed to be used by the Methodist University of Indonesia to the decision-making determination of high performing employees by following the steps made. So the processing time and the data used in the calculation process faster. Accuracy of data becomes the main thing in the process to obtain maximum results. This application is designed to be dynamic to changes in the criteria, values and weights, and easy to use.

Pada era digital sekarang ini banyak pihak telah memberdayakan teknologi komputer untuk menjalankan aktifitasnya tanpa harus menggunakan dokumen manual seperti kertas dan sejenisnya. Khususnya dalam pengolahan atau visualisasi gambar tidak lagi mengandalkan cetakan namun sudah menggunakan file digital terutama dalam pengarsipan digital. Semua dokumen teks dan gambar sudah diarsipkan secara digital dalam bentuk file gambar agar tidak mudah dilakukan modifikasi serta tetap seperti aslinya. Untuk keamanan data maka perlu dibuat tanda atau bukti kepemilikan dengan melakukan penyisipan teks atau gambar tertentu ke dalam file citra tersebut (watermaking). Tujuannya adalah untuk membuktikan originalitas file tersebut serta untuk menjaga adanya modifikasi atau pemalsuan. Perguruan Tinggi perlu melakukan pengamanan pada setiap karya atau file yang bersifat penting seperti Ijazah, Surat Keputusan, Transkrip Nilai maupun dokumen penting lainnya yang dimiliki. Sehingga arsip file digital aman dan original selalu. Kata Kunci: digital watermaking, metode LSB, keamanan arsip File Digital

Increased utilization of service learning with information technology (IT) is a matter that can provide added value to an institution. Students can obtain additional services outside of the processes that occur during this time. Learning without having face-to-face between students and professors did not greatly reduce the learning outcomes. In the design of the Electronic Learning (e-learning) is a web-based involving students, faculty, courses, facilitators, support staff, and administrators. The other major component is the availability of the network infrastructure (Internet), the application of e-learning (e-learning web-based application) and e-learning content itself. E-learning has the main function of the nature of choice as a supplement, complement, or replacement. Applications designed using the Model View Controller architecture method (MVC) is to separate the interface and navigation mechanisms of behavior which is owned by the application. The goal is an activity that is conducted every user can run well and the quality of the application can be guaranteed. Content provided in the application covers the user registration process with different access rights, data management participants of e-learning, courses, lectures given material management professors, management tasks, quizzes and discussion facilities. Display used by all users equally and given the opportunity to make changes to the profile of each user. In the implementation of e-learning will be opened for every lecturer who will implement e-learning by stages to register first. Then the administrator opens the class and then the students who complete the class can register in advance and then approved by the admin, the e-learning process can be implemented in accordance with the existing rules on the system.

In recording the EEG signals are often contaminated by a large of signals called artifacts such that the brain activity (source) difficult to estimate. There are different kinds of artifacts such as power line noise, electromyogram, electrocardiogram and electrooculogram. In this research, an adaptive recurrent neural network (ARNN) for estimation of source and reduction of noise from recorded EEG signals is proposed. In the experiment, the EEG signals are recorded on three conditions, which is normal conditions, closed eyes, and blinked eyes. After processing, the dominant frequency of the EEG signal is obtained in the range of 12-14 Hz either on normal conditions, closed eyes, and blinked eyes. The experimental results show that the ARNN method was effectively estimated the brain activity according to the given stimulus and remove the artifacts from all subjects.

Tmajcooent tuentiis-pinene and the main hyratipdt a-pinen a-terpineol. To obtain the optimal process design of a-terpineol production, some initial information regarding the principle of the thermodynamics and phase equilibrium are required. The aim of this paper is to present liquid-liquid equilibrium (LLE) of sym ntnga-pinene, a-terpineol and water. Ternary LLE a-pinene, a-terpineol and water system was determined by experiment at the temperatures of 301, 327 and 353 K and atmospheric pressure. The three component mixture was stirred for about 30 min, then the mixture was left for about 2 h for complete phase separation. The composition of both phases was analyzed by using a Gas Chromatograph. The thermodynamic equilibrium models were proposed. LLE model in this study includes activity coefficient model based on NRTL and UNIQUAC models. The NRTL model (a = 0.2) correlates the LLE data for the system of a-pine+a-terpineol + water at the temperatures 301, 327 and 353 K with RMSD of 0.5464%, 0.000169% and 0.0054%, respectively. The UNIQUAC model correlates the LLE data for the system of apine +-terpineol + water at the temperatures 301, 327 and 353 K with RMSD of 0.756%, 1.314% and 1.6615%, respectively.

Domestic passenger forecasting provides key input into decisions of daily operation management and infrastructure planning of airports and air navigation services and for aircraft ordering and design. Planning for the future is one of the most important keys to success, forecasting is the way. The goal of this study to predict the number of domestic passengers at Kualanamu International Airport. The time-series data were employed from Badan Pusat Statistik (BPS). The result is then discussed in the context of the potential use of the proposed for a new perspective for the predicting of domestic passengers at Kualanamu International Airport, Indonesia. The machine learning approach using long short term memory (LSTM) presents a useful way of observing the domestic passenger predict the passenger time series.

Forest fires are a major environmental issue, creating economical and ecological damage while dangering human lives. The investigation and survey for forest fire had been done in Aek Godang, Northern Sumatera, Indonesia. There is 26 hotspot in 2017 close to Aek Godang, North Sumatera, Indonesia. In this study, we use a data mining approach to train and test the data of forest fire and the Fire Weather Index (FWI) from meteorological data. The aim of this study to predict the burned area and identify the forest fire in Aek Godang areas, North Sumatera. The result of this study indicated that Fire fighting and prevention activity may be one reason for the observed lack of correlation. The fact that this dataset exists indicates that there is already some effort going into fire prevention.

The Fine Fuel Moisture Code (FFMC) is a numeric rating of the dampness substance of litter and other restored fine fills. This code is a pointer of the general simplicity of start and the combustibility of fine fue. In this study we observed the rainfall time series as a parameter to get the index of FFMC. The main goal of this study to predict the amount of rainfall in a particular division or state well in advance. We predict the amount of rainfall using past data to generate the parameter of FFMC using SVM model in North Sumatera. Based on the result, the various visualizations of data are observed in Aek Godang, North Sumatera which helps in implementing the approaches for rainfall prediction to evaluate the parameter of fuel moisture code as fire weather index. The analysed individual year rainfall patterns for 2017, 2018, 2019, the approximately close means, noticed less standard deviations.

Tmajcooent tuentiis-pinene and the main hyratipdt a-pinen a-terpineol. To obtain the optimal process design of a-terpineol production, some initial information regarding the principle of the thermodynamics and phase equilibrium are required. The aim of this paper is to present liquid-liquid equilibrium (LLE) of sym ntnga-pinene, a-terpineol and water. Ternary LLE a-pinene, a-terpineol and water system was determined by experiment at the temperatures of 301, 327 and 353 K and atmospheric pressure. The three component mixture was stirred for about 30 min, then the mixture was left for about 2 h for complete phase separation. The composition of both phases was analyzed by using a Gas Chromatograph. The thermodynamic equilibrium models were proposed. LLE model in this study includes activity coefficient model based on NRTL and UNIQUAC models. The NRTL model (a = 0.2) correlates the LLE data for the system of a-pine+a-terpineol + water at the temperatures 301, 327 and 353 K with RMSD of 0.5464%, 0.000169% and 0.0054%, respectively. The UNIQUAC model correlates the LLE data for the system of apine +-terpineol + water at the temperatures 301, 327 and 353 K with RMSD of 0.756%, 1.314% and 1.6615%, respectively.

The Fine Fuel Moisture Code (FFMC) is a numeric rating of the dampness substance of litter and other restored fine fills. This code is a pointer of the general simplicity of start and the combustibility of fine fue. In this study we observed the rainfall time series as a parameter to get the index of FFMC. The main goal of this study to predict the amount of rainfall in a particular division or state well in advance. We predict the amount of rainfall using past data to generate the parameter of FFMC using SVM model in North Sumatera. Based on the result, the various visualizations of data are observed in Aek Godang, North Sumatera which helps in implementing the approaches for rainfall prediction to evaluate the parameter of fuel moisture code as fire weather index. The analysed individual year rainfall patterns for 2017, 2018, 2019, the approximately close means, noticed less standard deviations.

As a tropical country, Indonesia is situated in Southeast Asia nation has vast forests. Forest fire occur busy vary due to land conditions and forest conditions in drought season. The indicator used mitigated potential forest fire is to study the indicator behavior of the fire weather index (FWI). The data is gathered from the observation station in north Sumatra province, computation and estimation FWI by Canadian Forest Fire Weather Index based on the data gathered. It is found that there is gathered outlier data. to hope will it, it is necessary to conduct classification and predict this of the dataset by machine learning approach using Support Vector Machine Forest Fire (SVM-FF), which is a further development of the previous models, known as the c-SVM and v-SVM. This method includes a balancing parameter by determining the lower and upper limits of a support vector. Furthermore, it allowed the balancing parameter value to be negative. The results showed that the classification of FWI was at low, medium, high, and extreme levels. The low FWI value has an average of 0.5 which is in the 0 to 1 interval. There was an increase in the model's accuracy and performance from its predecessor, which include the c-SVM and v-SVM with respective values of 0.96 and 0.89. Meanwhile, it was observed that with the SVM-FF model, the accuracy was quite better with a value of 0.99, indicating that it is useful as an alternative to classify and predict forest fires.