Judul: Pembangunan Spatiotemporal Data Model pada Tipe Data Vektor dengan Konsep Event-based Spatiotemporal Data Model (ESTDM)
Abstrak: Spatiotemporal data are spatial data with well-defined spatial, area, and location information, as well as temporal attribute (time). Various types of changes to the spatiotemporal data require a data model to store this information. This research constructed a data model for spatiotemporal data with event-based spatiotemporal data model (ESTDM) concept that can store the cause of spatiotemporal data changes, type of changes, and action of changes conducted by spatial objects. The used data were land surface area in Indonesia in 1994 and 2001 in the form of polygon vector data. The data were processed by the ESTDM concept in order to produce an appropriate data model that can provide the necessary information with spatiotemporal query analysis. There were eight spatiotemporal queries that were used to analyze the object changes, in the form of contain, overlap, and coveredby. It was found that the application of event-based spatiotemporal data model concept on the polygon data type requires a more diverse type of data in terms of spatial changes and longer observation time. Other spatiotemporal queries may be used to improve the proposed data model.
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Judul: Spatiotemporal Data Model Development on Hotspot Data with an Event-based Spatiotemporal Data Model (ESTDM) Concept
Abstrak: Hotspot data that has been existed all this time is still in the form of usual spatial data which is not enough to keep temporal information and information about how a hotspot evolved. There are so many disadvantages in keeping the hotspot data. Therefore a data model that can keep enough information to represent the hotspot evolution is needed, and also can handle the lack of keeping the previous hotspot data. An Event-based Spatiotemporal Data Model (ESTDM) concept is propose to overcome this problem. Appearance and disappearance process that occurs on hotspot will be used as base for spatiotemporal data model development on hotspot data. This research aims to implement an Event-based Spatiotemporal Data Model (ESTDM) concept into PostgreSQL. As a result, we can get the informations about spatial information and temporal information about geographical information changes to represent hotspot evolution from spatiotemporal query such as show hotspot that reappear after experience disappearance before. These queries make analyze a hotspot easier. The result of these queries can be visualized in a Indonesian map then with histories about period of appearance and disappearance of hotspot.
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Judul: Inhibisi Biosintesis Kolesterol Oleh Campuran Ekstrak Flavonoid Berbasis Daun Jabon Merah (Anthocephalus Macrophyllus) In Vitro
Abstrak: Anthocephalus macrophyllus yang dikenal dengan nama jabon merah mulai dikembangkan sebagai tumbuhan herbal dan telah dilaporkan memiliki daya inhibisi terhadap aktivitas enzim HMG-KoA reduktase, namun belum ada informasi ilmiah mengenai campuran ekstrak flavonoid berbasis daun jabon merah dalam menghambat aktivitas enzim tersebut. Penelitian ini bertujuan menguji potensi campuran ekstrak flavonoid berbasis daun jabon merah dalam menghambat biosintesis kolesterol in vitro. Enzim HMG-KoA reduktase (EC 1.1.1.34) merupakan enzim kunci yang meregulasi tahap awal biosintesis kolesterol. Penghambatan aktivitas enzim tersebut diukur dengan spektrofotometer pada panjang gelombang 340 nm menggunakan kit enzim HMG-KoA reduktase (No. CS1090) dari Sigma Aldrich. Hasil menunjukkan penghambatan aktivitas enzim terbesar terjadi pada ekstrak formula D sebesar 25%. Penghambatan tersebut masih lebih rendah daripada standar flavonoid rutin (60.17%) dan kuersetin (41.10%), tetapi sama baiknya dengan pravastatin komersial (18.64%) sebagai obat antikolesterol. Oleh karena itu, ekstrak formula D berpotensi untuk dikembangkan sebagai obat antikolesterol.
Keyword: Anthocephalus macrophyllus, antikolesterol, flavonoid, Guazuma ulmifolia, HMG-KoA reduktase