Judul: Latent Semantic Indexing PadaSistem Temu Kembali Dokumen Bahasa Indonesia
Abstrak: Pengindeksan semantik laten merupakan salah satu metode yang berhasil diterapkan pada sistem temu kembali informasi dengan menggunakan dokumen berbahasa Indonesia. Metode yang digunakan adalah dengan memanfaatkan struktur tingkat tinggi implisit dalam asosiasi istilah dengan dokumen (struktur semantik) untuk meningkatkan deteksi dokumen relevan berdasarkan istilah yang ditemukan dalam kueri dalam bahasa Indonesia. Mesin yang dievaluasi menggunakan dokumen pertanian dan dokumen tanaman obat kemudian dibandingkan hasil penyimpanan matriks yang dihasilkan menggunakan Singular Value Decomposition (SVD) dan Semi Discrete Decomposition (SDD). Kemudian nilai k optimum akan ditentukan setelah diperoleh nilai relevan tertinggi pada nilai k tersebut.
Keyword: Information Retrieval, Singular Value Decomposition (SVD), Semi Discrete Decomposition (SDD)

Judul: Pengindeksan Ontologi Dokumen Bahasa Indonesia Menggunakan Latent Semantic Analysis
Abstrak: Ontology is a collection of concepts that can be applied to the information retrieval system that is able to represent knowledge of a document in a specific domain, so that ontology is considered to improve the performance of information retrieval systems. Therefore the construction of ontology concept must be able to solve semantic problem in corpus. This research proposes ontology indexing of document Bahasa Indonesia using latent semantic analysis. Latent semantic analysis (LSA) is a theory and method which can be considered to solve the problem of semantic words in the corpus by extracting and representing contextual usage meaning of the word by using statistical method. In this research, ontology which has been constructed is applied to the information retrieval systems and evaluated using 20 pairs of queries. As the result of this experiment a recall value of 96.5% and average precision value of 83.4% were obtained.
Keyword: 

Judul: Bioelectricity Production from Citrobacter freundii GBH253 and Chlorella pyrenoidosa on Microbial Fuel Cell Anode with Different Carbon Sources
Abstrak: Microbial Fuel Cell (MFC) development has significantly increased from various aspects to get higher and more stable electricity. Developing MFC on microorganism aspect is very important because it plays a crucial role in the MFC system. C. freundii GBH253 is one of the potential exoelectrogen bacterium that could be developed for the MFC system. Integrating C. freundii GBH253 and electricity-producing microalgae, such as C. pyrenoidosa, in the anode of MFC could get more stable and higher electricity. In this study, C. freundii GBH253 and C. pyrenoidosa were coupled to produce electricity from different substrates. C. freundii GBH253 and C. pyrenoidosa were tested on three different media types before being tested on MFC. They were also examined for the co-cultivation test to determine the symbiotic relationship between the two microorganisms. The MFC test was conducted using the Randomized Block Design Factorial and the Tukey test to see significant differences from each treatment. The parameters observed in this study were voltage, power density, Chemical Oxygen Demand (COD), Coulombic Efficiency (CE), pH, and volatile fatty acid (VFA). C. freundii GBH253 cannot grow on microalgae medium, while C. pyrenoidosa could grow on bacterial medium and a mixture of bacterium and microalgae media. The bacterium gained benefit from co-culture with microalgae. In the MFC test, electricity was generated in all treatments, which bacterium + microalgae with acetate treatment could generate power density up to 211,97 mW/m2 and the most stable compared to others. Production of electricity in bacterium-microalgae combination dominated by the bacterium; hence, microalgae still help bacterium by producing electricity and raised the COD value. The pH value of all treatments was higher than the initial pH. Acetate and phenol were VFA produced in all treatments, whereas butyric acid and propionic acid were found in some treatments. Pearson correlation showed that some VFA highly correlated with power density.
Keyword: Chlorella pyrenoidosa, Substrate, Microbial Fuel Cell, Electricity Producing Microalgae, Volatile Fatty Acid, Citrobacter freundii