DESAIN MODEL BASIS DATA OBYEK PARIWISATA PROVINSI JAWA TENGAH STUDI KASUS DI KABUPATEN MAGELANG

Magelang District is implementing the tourism development program that consists of: marketing development, tourism destination development, partnership development, and tourism infrastructure development. Data about tourism in Magelang regency has not been stored correctly according to the rules of database normalization, with redudancy data storage, including the data that stored and informed online. A good information system should be supported by accurate data and stored on a database that has been normalized, so that data can be read by the system or a different program with different goals and views. Based on the analysis of data obtained in Magelang District, there are several the same ways and the same and the different way of storing and displaying information tourism objects. Normalization process conduct on the obtained data until the 3rd normal form to eliminate the partial dependencies and transitive dependencies. The result of the reseach is a database model.

Implementasi Transformasi Haar Wavelet untuk Deteksi Citra Jeruk Nipis yang Busuk

Lime is a fruit that has been widely cultivated and used in Indonesia. Many products use this fruit in the production process. The process of sorting fruit is undeniably a very substantial early process. It is necessary for large-scale be aware of this in term of result and time required for the sorting process. Pattern Recognition is a discipline that focuses on classifying or picturing an object based on characteristics or main attribute of the object. In this research, the author implements Haar Wavelet Transformation method by characteristic extraction based on colour and texture , performs classification using K-Nearest Neighbor (k-NN) to detect indication of rotten lime and the grade of k on k-NN so the accuracy of the result could be acquired. Based on analysis result, Haar Wavelet Transformation method is able to be implemented to detect the indication of rotten lime and most optimal accuracy level of this system reaches the number of 85 percent.

Developing an Automated Student Academic Record Management with Business Intelligence Approach

Student academic records management and assessment are among the vital processes in any higher education institution. These processes must be efficient and systematic. The significant problems of the current system that is holding the student’s academic record have been observed and identified. Based upon the limitations and the challenges on the existing procedures of a manual storing and archiving of the students’ academic records, a centralized students’ academic record management system was proposed. This project primarily aimed to develop a computerized student academic record management system in order to help DMC College Foundation Incorporated (DMCCFI) Philippines improve its performance in the registrar services, specifically in the assessment and evaluation of student records. The newly developed system is integrated with business intelligence. It offers modules such as grade submission, assessment, and student kiosk with security feature. The development model included Rapid Application Development (RAD). The tools used in the development are Windows Server 2008 R2, DevExpress, Microsoft Visual Studio C#, MSSQL, and SmartDraw. Based on the system evaluation, the proposed system is very good with an aggregate mean of 4.55. The result implies that the MIS staff, coordinators and dean strongly agree that the proposed system is highly acceptable. In terms of usability, the proposed system is rated with an aggregate mean of 6.43 described as “Strongly Agree.” It was concluded that the developed system offers the capabilities and functions that can help improve the performance of the registrar services in DMCCFI and is highly recommended for immediate utilization by DMCCFI.

Peranan Kontur dan Slope dalam Pengenalan Keaslian Tanda Tangan Menggunakan Dynamic Time Warping dan Polar Fourier Transform

The writer has seen that so far signatures are just validated manually, so there is possibility to create a system for hand signature recognition. The objective of this research is to improve the method for hand signature recognition using combination method with different characteristic. Contour and slope used for special feature in this research. Contour and slope from image will be applied using Dynamic Time Warping (DTW). Another extraction feature that been used was Polar Fourier Transform (PFT). The method employed for classification are Support Vector Machine (SVM).From the research results, the writer obtains the fact that the combination between the DTW and PFT using SVM classification, provide the better results in verification of an authentic hand signature with the accuracy of 93.23%. it is expected that from this research, the results can be utilized in the process of verification of an authentic hand signature in near future dailylife.

PENGEMBANGAN DAN ANALISIS KOMBINASI RUN LENGTH ENCODING DAN RELATIVE ENCODING UNTUK KOMPRESI CITRA

Data Compression can save some storage space and accelerate data transfer. Among many compression algorithm, Run Length Encoding (RLE) is a simple and fast algorithm. RLE can be used to compress many types of data. However, RLE is not very effective for image lossless compression because there are many little differences between neighboring pixels. This research proposes a new lossless compression algorithm called YRL that improve RLE using the idea of Relative Encoding. YRL can treat the value of neighboring pixels as the same value by saving those little differences / relative value separately. The test done by using various standard image test shows that YRL have an average compression ratio of 75.805% for 24-bit bitmap and 82.237% for 8-bit bitmap while RLE have an average compression ratio of 100.847% for 24-bit bitmap and 97.713% for 8-bit bitmap.

APLIKASI SISTEM PENDUKUNG KEPUTUSAN TANAMAN OBAT HERBAL UNTUK BERBAGAI PENYAKIT DENGAN METODE ROC (RANK ORDER CENTROID) DAN METODE ORESTE BERBASIS MOBILE WEB

Herbal medicinal plant is a traditional medicinal plant that is used to cure a disease. Most of modern people did not know yet the benefits that will be gotten from herbal plants for the health. This research developed a supporting decision application system of herbal medicinal plants for various diseases. ROC (Rank Order Centroid) method was used to count the total number of criteria value and Oreste method was used to rank the alternative herbal medicinal plants with criteria which influence it, namely disease, blood pressure, tall, weight, user’s condition (other diseases), age, kinds of plants, substance and efficacy of plants themselves. Final result of this system was that there were some alternative herbal medicinal plants which were appropriate to user’s disease. In this research, the researcher conducted white box testing by using path base testing to make complex logical estimates to define current action and conducted black box testing by using equivalence partitioning technique which divided domain input, decided testing case by explaining kinds of mistakes. The results of proper test for the system which were done by using questionnaire were gotten 86.75% for testing of functional system, 87% for interface and accessing testing, and 87.33% for testing of advantages system.

IMPLEMENTASI METODE CHAIN CODE UNTUK PENGENALAN RAMBU LALU LINTAS

Traffic sign is needed to give information to users so they can be aware in roads. There are many types of traffic signs and each has many forms and different from each other so users sometimes have difficuty in recognizing traffic signs. In this research, the signs used are signs based on Peraturan Menteri Perhubungan Republik Indonesia Nomor PM 13 Tahun 2014. Modified Chain Code method was implemented for feature extraction process and Euclidean Distance method is used to calculating the similarity. Testing is done with 5 types of tests i.e. resize image, objects truncated, added a few objects to image, added many objects to image and noise spots. The test results showed the accuracy of the image of traffic signs to be recognized is 92.5%.

ANALISIS SENTIMEN PADA TWITTER MAHASISWA MENGGUNAKAN METODE BACKPROPAGATION

In a learning environment, emotional factors influence student motivation. Students emotion have an important role in students' capability to learn. The tendency of the students emotion are not easily recognizable in a short time. Twitter is a popular micro-blogging system especially for students. Students post tweet about activities, experiences, their feelings anywhere, anytime and in real time. Sentiment analysis on twitter produce content sentiment that represents the feelings and emotions of students. Sentiment analysis system was built using backpropagation method at the stage of classification. In this research backpropagation network and the classification results were tested using WEKA with multilayer perceptron classifier. The results of sentiment analysis with 30 student respondents are 33.33% tendency of positive emotions, neutral emotions tendency 53.33% and 13:33% negative motional tendencies. The results are used as reference in providing the appropriate treatment of the students during the process of learning.

PEMBERDAYAAN UMKM BERBASIS TEKNOLOGI INFORMASI DAN KOMUNIKASI KABUPATEN KENDAL MENUJU PASAR GLOBAL

Free trade can not be dammed again, so the impact on local businesses in particular products SME have to be able to compete with foreign products because it is supported by information and communication technology (ICT), which consists of the online market. KKN-PPM FTI UKSW was carried out to community groups businesses incorporated in the SME Kabupaten Kendal, Central Java, was carried out with methods of mentoring and development applications online market. The purpose of this program is to provide ICT field for the empowerment of the perpetrators of the SME. KKN-PPM program results are the SME capable of using ICT in particular basic creative multimedia designer label to product packaging, design content market online, and can make your business, as well as brend is able to manage the online market site independently, so the product SME Kabupaten Kendal as a potential area capable of leading to the global market.

ANALISIS GAUSSIAN DAN EDGE CONNECTION DALAM PENAJAMAN DETEKSI TEPI MENGGUNAKAN METODE CANNY

Edge detection is one of many ways to get information from an image without big data storage needed. In this research, the edge detecting is done by implementing Canny edge detection algorithm. The focus of this research is to analyze the effect of two variables of the first process of Canny, Gaussian filter smoothing, that is size of matrix and variance, to the sharpening of edge detection. The testing is done by changing the size of the matrix and the value of the variance. The results showed that the best matrix size and variance for sharp edge detection is less than 30x30 and 30.