Judul: Development of a Data Warehouse Model for Online  Analytical Processing Applications for Karhutla Hotspot Data
Abstrak: Hotspot merupakan salah satu indikator untuk mengidentifikasi terjadinya kebakaran hutan dan lahan (karhutla). Spatial data warehouse hotspot diperlukan untuk membuka peluang dalam melakukan analisis yang lebih mendalam terhadap data hotspot, serta memfasilitasi pengambilan keputusan berbasis spatial yang lebih baik dalam konteks penanggulangan karhutla. Penelitian ini bertujuan membangun modul database untuk mengelola data hotspot yang bersumber dari website SiPongi, membangun spatial data warehouse pada sistem Spatial OLAP untuk Data Hotspot, dan membangun modul extract, transform, dan load (ETL). Metode penelitian meliputi identifikasi fitur dan atribut yang akan dilakukan pada pengembangan modul database hotspot, pembangunan spatial data warehouse, dan pengembangan modul ETL. Tahap terakhir adalah pengujian dengan menggunakan metode pengujian black box. Penelitian menghasilkan spatial data warehouse hotspot dengan menunjukkan bahwa data warehouse dapat melakukan operasi OLAP dengan benar sesuai dengan kebutuhan sistem., Hotspots are an indicator to identify forest and land fires (karhutla). Spatial data warehouse hotspots are needed to open up opportunities to carry out more in depth analysis of hotspot data, as well as to facilitate better spatial-based decision making in the context of forest and land fire prevention. This study aims to build a database module to manage hotspot data sourced from the SiPongi website, build a spatial data warehouse on the Spatial OLAP system for Hotspot Data, and build an extract, transform, and load (ETL) module. The research steps include identification of features and attributes that will be carried out in the development of the hotspot database module, the development of a spatial data warehouse, and the development of the ETL module. Finally, testing is carried out using the black box testing method. The study succeeded in producing a spatial data warehouse hotspot. The data warehouse can provide OLAP operations correctly according to system requirements.
Keyword: data warehouse, extract, transform dan load (ETL), spatial online  analytical processing (SOLAP)

Judul: Pengembangan Modul Update Data pada Sistem Spatial Data Warehouse Hotspot
Abstrak: The spatial on-line analytical processing (SOLAP) was developed to support hotspots monitoring. The system is able to perform SOLAP analysis and provide the visualization of hotspot distribution. However, this system has not been able to update the hotspots data into a data warehouse. This research aimed to develop a data updating module. This system was built in Java programming language and has a graphical user interface (GUI). The data source used by this system was the result of satellite imagery in the form of a text file, which contains information of hotspots owned by Directorate of Forest Fire Control. Extraction was done to retrieve hotspots information in the text file and make the schematic adjustments in order to be stored in the data warehouse. Refers to the concept of extraction, transformation, and loading (ETL), the system is able to map the data from the data source into the data warehouse, and can process multiple text files.
Keyword: spatial, SOLAP, hotspot, forest fires, ETL, data warehouse

Judul: Insecticidal Activity of Essential Oils Leaves of Cinnamomum spp. (Lauraceae) against Crocidolomia pavonana and Their Phytotoxicity on Broccoli Seedlings
Abstrak: Essential oils from leaves of 13 species of Cinnamomum were tested for their insecticidal activity on the cabbage head caterpillar Crocidolomia pavonana with leaf immerse method. The results showed that the treatment with 1% (w/v) essential oils leaves of C. celebicum, C. multiflorum, C. sintoc, and C. verum caused 21.45, 93.65, 60.30, and 76.10% mortality, respectively. Based on the results of phytotoxicity and insecticidal activity tests, C. multiflorum oil was further tested at 6 concentration levels. In all treatments, larval mortality has occurred at 24 hours after treatment (HAT) and increased at 48 HAT. LC50 of C. multiflorum oil at 24 and 48 HAT was 0.504 and 0.396%, respectively. The treatment with C. multiflorum oil at ≤0.31% did not inhibit the development of C. pavonana larvae. Determination of the chemical constituents of Cinnamomum oils were carried out by gas chromatography-mass spectrometry (GCMS). Totally, 345 compounds were identified. Methyleugenol constituted the main component (49.4%) of leaf essential oil of C. multiflorum and was assumed to be responsible for the insecticidal activity of the oil against C. pavonana larvae. LC50 of pure methyleugenol obtained at 0.365% (48 HAT) and 0.363% (72 HAT). The results showed that C. multiflorum was more effective with LC50 value equivalent to methyleugenol content of 0.32% (24 HAT) and 0.24% (48 HAT).
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