Cluster Evaluation of Density Based Subspace Clustering

Clustering real world data often faced with curse of dimensionality, where real world data often consist of many dimensions. Multidimensional data clustering evaluation can be done through a density-based approach. Density approaches based on the paradigm introduced by DBSCAN clustering. In this approach, density of each object neighbours with MinPoints will be calculated. Cluster change will occur in accordance with changes in density of each object neighbours. The neighbours of each object typically determined using a distance function, for example the Euclidean distance. In this paper SUBCLU, FIRES and INSCY methods will be applied to clustering 6x1595 dimension synthetic datasets. IO Entropy, F1 Measure, coverage, accurate and time consumption used as evaluation performance parameters. Evaluation results showed SUBCLU method requires considerable time to process subspace clustering; however, its value coverage is better. Meanwhile INSCY method is better for accuracy comparing with two other methods, although consequence time calculation was longer.Comment: 6 pages, 15 figure

The Design of Pre-Processing Multidimensional Data Based on Component Analysis

Increased implementation of new databases related to multidimensional data involving techniques to support efficient query process, create opportunities for more extensive research. Pre-processing is required because of lack of data attribute values, noisy data, errors, inconsistencies or outliers and differences in coding. Several types of pre-processing based on component analysis will be carried out for cleaning, data integration and transformation, as well as to reduce the dimensions. Component analysis can be done by statistical methods, with the aim to separate the various sources of data into a statistical pattern independent. This paper aims to improve the quality of pre-processed data based on component analysis. RapidMiner is used for data pre-processing using FastICA algorithm. Kernel K-mean is used to cluster the pre-processed data and Expectation Maximization (EM) is used to model. The model was tested using wisconsin breast cancer datasets, lung cancer datasets and prostate cancer datasets. The result shows that the performance of the cluster vector value is higher and the processing time is shorter

Measurement of Image Distance Using Only Camera On Object Detection OpenCV

Image processing combine with machine learning is used widely in image recognition, image classification, and image detection. By using camera to detect an object has been done within several article. The other usage of image and object detection is in measurement of distance. Distance measurement is possible by using additional peripheral such as sensor and extra camera. This research is intended to elaborate the usage of single camera in detecting and measuring distance. The distance set between the camera and the object.  In this research, author used a square object with different size and   different distance range. By using one of the known data as a pivot in calculating other image distance, the average error between 4%-7% . These result was achieved by using different  object size. The bigger the size of the object used as reference, the smaller the error percentage of the measurement.&nbsp

A Study on the Application of Solar Panel Technology in Low-Income Residential Housing in Deli Serdang Regency

The need for energy use, especially electrical energy continues to increase from year to year. One of the sectors that consume the largest electrical energy is the household sector which consumes about 27% of the total energy consumption of all sectors. The main energy source in Indonesia at this time still comes from fossil energy, although the government has tried to develop various renewable energy sources for the future. Solar energy is one of the renewable energies that is quite potential for Indonesia considering the level of solar radiation in Indonesia is quite high throughout the year. The selection of subsidized housing as the object of research is due to the existence of clear regulations and the number which also continues to increase every year. Through the collection of physical data on the research location, such as analysis of shadows, roof structure, solar irradiation data, average electric power usage, the average solar energy requirement of the subsidized housing will be obtained. Furthermore, by calculating the economic value, it will be obtained how the description of the possibility of applying solar energy to subsidized housing will be obtained. If possible, the application of solar energy in subsidized housing can help government programs to use renewable energy and reduce the use of fossil energ

PEMBERDAYAAN MASYARAKAT PENGOLAHAN MANGROVE MENJADI PERMEN JELLY DAN SIRUP MANGROVE BERBASIS NILAI JUAL SEBAGAI UPAYA PENINGKATAN PENDAPATAN MASYARAKAT DESA KOTA PARI, KECAMATAN PANTAI CERMIN

Pesisir memiliki peranan sangat penting bagi berbagai organisme yang berada di sekitarnya. Kawasan pesisir memiliki beberapa ekosistem vital seperti ekosistem terumbu karang, ekosistem padang lamun dan ekosistem hutan mangrove. Masyarakat Di Desa Kota Pari Kecamatan Pantai Cermin, Serdang Bedagai tidak dapat memiliki penghasilan lebih karena kreativitas mereka yang kurang dalam membuat produk dari pohon mangrove yang sudah ada. Salah satu potensi mangrove diwilayah pengabdian adalah Buah Pidada, namun buah ini tergolong tidak begitu banyak, karena kurang pemamnfaatannya di Kota Pari. Metode yang dilakukan dalam pengabdian adalah dengan memberikan pengetahuan sekaligus pelatihan kepada masyarakat khusunya Ibu-ibu PKK yang ada Di Desa Kota Pari. Pemanfaatan buah pidada mangrove ini dijadikan sebagai produk olahan makanan ringan berupa permen jelly. Hasil dari pengabdian masyarakat setelah dilakukan pengabdian dengan penyeluhan dan bimbingan teknis mengenai pelatihan pembuatan permen jelly, ibu-ibu PKK Di Desa Kota bahwa peserta memahami materi dan demonstrasi pembuatan permen jelly yang diberikan. Keberhasilan ditunjukkan dengan adanya respon positif dari peserta, dengan mengajukan berbagai pertanyaan dan tanggapan terkait pembuatan pengolahan mangrove pidada menjadi permen jelly yang nantinya siap dikomersilkan sebagai potensi Desa Kota Par

Clustering high dimensional data using subspace and projected clustering algorithms

Problem statement: Clustering has a number of techniques that have been developed in statistics, pattern recognition, data mining, and other fields. Subspace clustering enumerates clusters of objects in all subspaces of a dataset. It tends to produce many over lapping clusters. Approach: Subspace clustering and projected clustering are research areas for clustering in high dimensional spaces. In this research we experiment three clustering oriented algorithms, PROCLUS, P3C and STATPC. Results: In general, PROCLUS performs better in terms of time of calculation and produced the least number of un-clustered data while STATPC outperforms PROCLUS and P3C in the accuracy of both cluster points and relevant attributes found. Conclusions/Recommendations: In this study, we analyze in detail the properties of different data clustering method.Comment: 9 pages, 6 figure

A Comparative Agglomerative Hierarchical Clustering Method to Cluster Implemented Course

There are many clustering methods, such as hierarchical clustering method. Most of the approaches to the clustering of variables encountered in the literature are of hierarchical type. The great majority of hierarchical approaches to the clustering of variables are of agglomerative nature. The agglomerative hierarchical approach to clustering starts with each observation as its own cluster and then continually groups the observations into increasingly larger groups. Higher Learning Institution (HLI) provides training to introduce final-year students to the real working environment. In this research will use Euclidean single linkage and complete linkage. MATLAB and HCE 3.5 software will used to train data and cluster course implemented during industrial training. This study indicates that different method will create a different number of clusters.Comment: 6 pages, 10 figures, published on Journal of Computing, Volume 2, Issue 12, December 201

Exploring the Efficacy of Inquiry-Based Learning for Human Respiratory System: Students' Achievement at High School Setting

The current research has primary objective that is to assess the effect of implementing the Inquiry-Based Learning Model in enhancing students' academic performance in the field of Science at SMA Smart Indonesia. The Inquiry-Based Learning Model promotes proactive student engagement in exploring, gathering, and interpreting information through independent investigation. The study utilized a quasi-experimental design encompassing pre-test and post-test phases. The participants were selected randomly via a simple random sampling technique. The acquired data underwent analysis using the N-Gain method (T-test). The outcomes revealed a noticeable improvement in the academic performance of students in the experimental group who were exposed to the Inquiry-Based Learning Model, particularly in the context of the human respiratory system. Furthermore, the null hypothesis (H0) was invalidated, as was proven by the 2-tailed Significance value of 0.000 that was smaller than 0.05. This discovery underscores the substantial positive impact of applying the Inquiry-Based Learning Model on enhancing students' academic achievements when compared to conventional teaching methods employed in the control group. In conclusion, this study highlights the significant potential of integrating the Inquiry-Based Learning Model into the Natural Science curriculum at the secondary school level, which could potentially elevate the standard of education and overall student learning accomplishments