ABSTRAK Untuk menarik minat pendaftar mahasiswa baru memerlukan strategi khusus. Salah satu strategi adalah  dengan melakukan analisa data dengan tujuan mengubah kumpulan data menjadi memiliki nilai bisnis melalui laporan analitik sehingga menghasilkan   informasi yang akan diambil polanya menjadi pengetahuan [Kusrini, 2009]. Teknik klasifikasi merupakan pendekatan fungsi klasifikasi dalam data mining yang digunakan untuk melakukan prediksi atas informasi yang belum diketahui sebelumnya[Larose, 2005]. Pohon keputusan merupakan metode klasifikasi dan prediksi. pada penelitian ini algorithma yang dipakai untuk pembentukan pohon keputusan  dengan  mengunakan algoritma C45[Larose, 2005]. Data yang diproses adalah data mahasiswa baru angkatan 2014 dan angkatan 2015. Hasil penelitian ini menunjukkan bahwa variabel yang paling tinggi pengaruhnya terhadap hasil registrasi mahasiswa adalah Asal Sekolah dan Jenis Kelamin. Rata-rata berasal dari Semarang dengan jurusan SMU dari IPA dan yang berasal dari luar kota rata-rata berasal dari Batang dan Pati.  Dari SMU jurusan  IPS dan berjenis kelamin Laki-laki berasal dari Batang  dan yang berjenis kelamin Perempuan berasal dari Pati.. Accuracy dari pembenukan model ini adalah sebesar 89.33 %  (Good Classification).  ABSTRACT To attract new student applicants requires a special strategy. One strategy is to perform data analysis with the aim of converting the data set to have business value through analytic reports so that the information will be taken into the pattern of knowledge [Kusrini, 2009]. The classification technique is an approximate classification function in data mining used to predict information previously unknown [Larose, 2005]. Decision tree is a method of classification and prediction. in this study the algorithm used for the formation of decision trees using the C45 algorithm [Larose, 2005]. Processed data are new student data of class of 2014 and class of 2015. The result of this research indicates that the variable that has the highest effect on student registration result is School Origin and Gender. The average comes from Semarang with high school majors from IPA and those coming from out of town on average come from Batang and Pati. Of SMU majoring in IPS and Male sex comes from the stem and the female sex is derived from Pati .. Accuracy of this model is 89.33% (Good Classification).

Bamboo can be used in construction planning because based on its properties, the mechanical strength of bamboo has high tensile strength and high compressive strength so that it can be used for soil reinforcement. Bamboo which has good quality will also have good mechanical properties as well because bamboo which has good compressive strength, laboratory results also show that bamboo has good tensile strength as well. Thus, there is a correlation between compressive strength and tensile strength in bamboo which is an environmentally friendly material as a soil strengthening material. The data in this study were using bamboo Apus and Javanese bamboo. Because bamboo is often used in industry and is easily available in Semarang. This study uses a simple linear method (Ordinary Least Squares). Simple linear regression model is one of the regression models that are often used in regression analysis. The dataset divided into 2 part, namely by comparing 60% of training data and 40% of testing data. The result from the data testing showing linier regression (least squares) estimate becomes very sensitive to random errors in the observed target, producing a large variance and the following results are obtained Correlation Coefficient 0.99607873, Mean Squared Error 12. 58799, Variance Score 125.60. The results show that the correlation coefficient is 0.99607873, it’s mean that the linear model is close to number 1 meaning that this model is a good model because the correlation coefficient value is close to 1 so there is a positive relationship between or positive correlation between the compressive and tensile tests.

In any construction design, two things should be taken into account are stability and settlement. In order to achieve target soil stability or soil bearing capacity, earthwork solutions and or ground improvement solutions can be conducted. Some solutions can vary such as using bamboo as a retaining wall or as a foundation. This study aims to determine the compression and tension properties of bamboos which can be used as data for soil reinforcement. Two types of bamboo, bamboo Apus (Gigantochloa Apus) and bamboo Jawa (Gigantochloa Atter) are selected as tested materials. Twenty-four samples from the two bamboos are tested to understand their compressive strength and other thirty for tensile strength. In order to determine the compression (ASTM C39/C39M-09a) and tension (SNI 03-3399-1994) properties of some parts of bamboo, the samples are taken from top, middle, and bottom location. From this experiment, from the two kinds of bamboo, bamboo Apus provides higher strengths (both compressive and tensile strength) than bamboo Jawa. For compressive strength, Bamboo Apus on average reaches 44.36 MPa while bamboo Jawa reaches 25.45 MPa. In tensile strength, on average bamboo Apus reaches183 MPa which is higher than that of bamboo Jawa 140.3 MPa. From this finding, it assures that one type of bamboo can have higher strength than others.

In computer vision tracking and object segmentation is one important step in video processing. Accuracy in object tracking is important in video processing, where accurate object tracking is a thing that continues to be done by many researchers. there are still many problems that are often experienced when tracking objects in terms of lighting, noise up to a high level of error. Many methods can be used in research, one of which is clustering method. Clustering method is a method that is widely used in grouping data, one of which is often used is Kmeans clustering. This method is very flexible, and is able to classify large amounts of data. Besides that, Kmeans is also able to work adeptly and segment the image well. For this study using 5 distance approaches (cambera, chebychef, mahattan, minkowski, Euclidean) distance approach which is expected to improve the results of better accuracy. From the results of the research produced a mahatan distance approach has the best accuracy results with a PNSR value of 16,34399 and the lowest MSE value with a value of 1521,793. Compared to the use of standard models with Euclidean, the approach of high distance accuracy increases

Bamboo is an environmentally friendly material. Many benefits of bamboo that we can get. Indonesia as a bamboo-producing country needs easy techniques to make good classification of bamboo. Bamboo is composed of fibers and fiber adhesives. There are various kinds of bamboo in Indonesia. This study uses digital image processing with fuzzy c means based segmentation to identify bamboo. Segmentation is an important thing in image processing. By using fuzzy c means in segmentation in this study obtained good segmentation results. This study uses 4 types of bamboo, namely Javanese bamboo, Ori bamboo and Petung bamboo and Wulung bamboo. There are 40 images as training images and 12 test images. The results of segmentation show that fuzzy c means produces good segmentation with the number of iterations between 20-23 and time ranging from 0.11 to 0.15. The accuracy of this test reaches 80%.