A Framework for Remote Monitoring System

Remote monitoring system becomes an important facility to support observation activities for various natural disasters. In many incidents of natural disaster such as volcano eruptions, the available monitoring systems installed closely to disaster area were damaged due to extreme condition raised by the event. The temperature of disaster site could suddenly increase to hundred degrees of Celsius, drowned in a water flood or even trapped in a toxic heating gas. Therefore, it is important to have observation facility that is installed far away from disaster area. This research is an exploratory study to develop the framework for remote monitoring system. It includes hardware requirement and algorithm definition that cover system lenses and a set of image processing algorithm. The framework delivers a promising preliminary result towards the effort for remote monitoring system development

Analisa Kualitas Citra Digital Hasil Akuisisi Jarak Jauh

The research is motivated by a number of natural phenomenons which allow monitoring only from a distance such as the occurrence of many natural disasters as well as the life of flora and fauna in the nature. Meanwhile the progress of the research on remote monitoring has proved the the quality of remote object presentation is low. Therefore it is necessary to identify the characteristic of a digital image obtained from remote monitoring i.e. it is accomplished using histogram and frequency comparison against the image obtained from a closed distance acquisition. The research shows that the image obtained from remote monitoring hold a shorter distribution of pixel value compared to the image obtained from a closed distance. And comparison in the frequency domain shows that the image obtained from remote monitoring presents fewer high frequencies, thus its presentation in the space domain looks dull

The evaluation of higher education policy to drive university entrepreneurial activities in information technology learning

This study discusses the role of university and industry in Indonesia’s higher education system, particularly in learning information technology and the related fields. Three data sources were used to collect information on learning practices, i.e., the higher education policies representing the government’s perspective, the knowledge capitalization practices representing the industry readiness to act as a joint provider of knowledge and skill with the university, and the perspectives of human learner as the subject of learning processes. The study proposes two-stage evaluation on higher education practices that consists of policy analysis and the evaluation of learning practices based on the model of learning system. The former is to map the higher education policy to the spectrum of university entrepreneurial activities, while the latter is the survey on learning practices participated by the industry, students, and alumni. Policy analysis identifies the blank spot on the activities of consulting, spin-off firm formation, and the creation of a technology park. The evaluation of learning practices shows that the university still becomes the dominant actors in the transfer of knowledge and skill, except for the fields of entrepreneurship and project management which the industry excels. These results indicate that university contributes primarily in growing the internal capacity of human resource, while the industry contribute in shaping the professional life. This study suggests that the practice of higher education in Indonesia requires a more aggressive strategy in triple helix relations to enable the achievement of knowledge society and knowledge economy by strengthening the whole spectrum of university entrepreneurial activities

Cost Effective Approach for Spatial Modeling

The paper presents an effort to standardize cost effective to support the development of spatial modeling. It is motivated by the increasing role of both cost effective and spatial modeling to contribute on society development worldwide. Therefore the future of spatial modeling would focus on minimizing cost and required time for model generation, in which cost effective become the only reliable approach to achieve these objectives. Considering that spatial modeling commonly consists of data acquisition, digitations process and model development, hence the characteristic of cost effective to minimize any required resources for system development is required to be presented in each stage. It means the method being utilized in each stage must comply with the objective of cost effective, thus method selection takes a vital role in the development process. The work has presented various strategies consisting of different methods being employed for model development in which each carries its own benefits and flaws. Finally it is important to consider available resources to meet with method selection in order to enable wise implementation of spatial modeling

The behaviour of rank correlation coefficients for incomplete data

This paper presents the analysis to disclose the behaviour of rank correlation coefficients under the complete and incomplete data condition. The main concern of this research is to deal with the missing data by preserving the originality of data pair rather than experiencing data deletion or imputation. The paper introduces the variability function that is developed for each correlation coefficient in order to disclose the mean and the variance for every possible data sequences. The comparisons between Kendall, Spearman, and the absolute distance measure for index ranking demonstrate the use of variability function under both the complete and incomplete data, in which it becomes a useful tool to describe the coefficient’s mechanism to proceed with a set of possible data sequences. The analysis proves that Kendall coefficient becomes the better method compared to Spearman and the absolute distant measure due to threefold, i.e. the ability to preserve the zero mean of variability distribution in complete data, the ability to survive from the missing data, and the ability to gain a higher rate of convergence in incomplete condition. Meanwhile, Spearman fails to preserve the original data pair under the incomplete condition due to direct measurement of rank distances

The evaluation of entropy-based algorithm towards the production of closed-loop edge

This research concerns with the common problem of edge detection that suffers from producing a disjointed and incomplete edge leading to misdetection of visual object. The entropy-based algorithm has a potential to solve this problem by classifying the pixel belonging to which objects in an image. Hence, the paper aims to evaluate the performance of entropy-based algorithm to produce the closed-loop edge representing the formation of object boundary. The research utilizes the concept of entropy to sense the uncertainty of pixel membership to the existing objects in order to classify pixel as the edge or object. Six entropy-based algorithms are evaluated, i.e. the optimum entropy based on Shannon formula, the optimum of relative-entropy based on Kullback-Leibler divergence, the maximum of optimum entropy neighbour, the minimum of optimum relative-entropy neighbour, the thinning of optimum entropy neighbour, and the thinning of optimum relative-entropy neighbour. The experiment is held to compare the developed algorithms against Canny as a benchmark by employing five performance parameters, i.e., the average number of detected objects, the average number of detected edge pixels, the average size of detected objects, the ratio of the number of edge pixel per object, and the average of ten biggest size. The experiment shows that the entropy-based algorithms significantly improve the production of closed-loop edge, and the optimum of relative-entropy neighbour based on Kullback-Leibler divergence becomes the most desired approach among others due to the production of bigger closed-loop edge in the average. This finding suggests that the entropy-based algorithm becomes the best choice to support edge-based segmentation. The effectiveness of entropy in segmentation task is addressed for further research

A Framework for Remote Monitoring System

Remote monitoring system becomes an important facility to support observation activities for various natural disasters. In many incidents of natural disaster such as volcano eruptions, the available monitoring systems installed closely to disaster area were damaged due to extreme condition raised by the event. The temperature of disaster site could suddenly increase to hundred degrees of Celsius, drowned in a water flood or even trapped in a toxic heating gas. Therefore it is important to have observation facility that is installed far away from disaster area. This research is an exploratory study to develop the framework for remote monitoring system. It includes hardware requirement and algorithm definition that cover system lenses and a set of image processing algorithm. The framework delivers a promising preliminary result towards the effort for remote monitoring system development

Segmentasi Objek Terrestrial Menggunakan Modified Watershed Transform

Penelitian ini bertujuan untuk mensupport pengembangan model kota secara spatial yaitu dengan cara meretrieve obyek-obyek yang terkandung dalam citra satelit secara otomatis. Target yang dituju oleh penelitian ini adalah didapatkannya dan dilokalisirnya obyek jalan yang terkandung dalam citra satelit. Hal ini dilakukan menggunakan pendekatan segmentasi berbasis watershed transform. Beberapa modifikasi pada tahap preprocessing dan post processing telah dilakukan untuk melengkapi proses segmentasi utama berbasis watershed transform. Hasil ujicoba menunjukkan bahwa metode yang dikembangkan dapat secara otomatis meretrieve obyek jalan namun belum menunjukkan hasil yang sempurna. Oleh karena itu perlu dilakukan pengembangan lanjutan serta ukuran quantitative untuk memvalidasi hasil yang telah didapatkan

Sistem informasi manajemen kesantrian di PP Daruttauhid Malang

Sistem Informasi Manajemen Kesantrian merupakan sistem manajemen madrasah terpadu yang diaplikasikan di Pondok Pesantren Daruttauhid Kota Malang. Salah satu implementasi Sistem Informasi Manajemen Kesantrian adalah sistem pembelajaran dan manajemen halaqah dengan menggunakan pendekatan ICT. Implementasi Sistem Informasi Manajemen Kesantrian menjadi salah satu model pembelajaran yang dianggap paling tepat untuk mengatasi cara belajar di masa pandemi covid 19. Perubahan paradigma belajar dan pembelajaran di masa Pandemi Coronavirus Disease 2019 (Covid-19) tidak dapat dihindari. Pola pembelajaran yang selama ini lebih banyak menekankan pada proses di kelas dengan tatap muka (face to face) yang diyakini paling efektif,di masa pandemic Covid 19 yang terjadi sejak awal 2020 ini, telah mengakibatkan disrupsi tersendiri di semua lini kehidupan, tidak terkecuali pembelajaran di lingkungan madrasah. Upaya pemerintah untuk menekan penularan Covid-19 dengan meniadakan kerumunan (social distancing) dan menjaga jarak (physical distancing), memaksa sekitar 82.418 madrasah di Nusantara.yang melayani 9.245.248 siswa di seluruh Indonesia dengan jumlah guru 780.652 melakukan proses pembelajaran jarak jauh menggunakan elearning (Kemenag, 2020). Untuk mengembangkan kegiatan pengembangan Sistem Informasi Manajemen Kesantrian dilakukan kegiatan Community Development

Sistem informasi manajemen kesantrian di PP Daruttauhid Malang

Sistem Informasi Manajemen Kesantrian merupakan sistem manajemen madrasah terpadu yang diaplikasikan di Pondok Pesantren Daruttauhid Kota Malang. Salah satu implementasi Sistem Informasi Manajemen Kesantrian adalah sistem pembelajaran dan manajemen halaqah dengan menggunakan pendekatan ICT. Implementasi Sistem Informasi Manajemen Kesantrian menjadi salah satu model pembelajaran yang dianggap paling tepat untuk mengatasi cara belajar di masa pandemi covid 19. Perubahan paradigma belajar dan pembelajaran di masa Pandemi Coronavirus Disease 2019 (Covid-19) tidak dapat dihindari. Pola pembelajaran yang selama ini lebih banyak menekankan pada proses di kelas dengan tatap muka (face to face) yang diyakini paling efektif,di masa pandemic Covid 19 yang terjadi sejak awal 2020 ini, telah mengakibatkan disrupsi tersendiri di semua lini kehidupan, tidak terkecuali pembelajaran di lingkungan madrasah. Upaya pemerintah untuk menekan penularan Covid-19 dengan meniadakan kerumunan (social distancing) dan menjaga jarak (physical distancing), memaksa sekitar 82.418 madrasah di Nusantara.yang melayani 9.245.248 siswa di seluruh Indonesia dengan jumlah guru 780.652 melakukan proses pembelajaran jarak jauh menggunakan elearning (Kemenag, 2020). Untuk mengembangkan kegiatan pengembangan Sistem Informasi Manajemen Kesantrian dilakukan kegiatan Community Development