Judul: Penerapan Metode Rule-Based Dengan Unsupervised  Learning Untuk Pelabelan Dokumen Berbahasa  Indonesia
Abstrak: Penelitian ini menerapkan metode Rule-based dengan Unsupervised Learning untuk pelabelan dokumen teks berbahasa Indonesia. Metode Rule-based menggunakan pola kata untuk menentukan label dari kata yang tidak diketahui. Pola diperoleh melalui proses pembelajaran otomatis dan diurutkan berdasarkan frekuensi kemunculan. Pelabelan kata yang ambigu atau tidak diketahui labelnya dilakukan dengan cara melihat pola kata sekitar dan mengambil pola kata dengan frekuensi kemunculan terbesar. Penambahan metode pengujian jenis imbuhan pada sistem diharapkan dapat meningkatkan pengenalan label pada dokumen. Penelitian menggunakan 102 dokumen teks yang terdiri dari 305.989 token untuk proses pelatihan dan menghasilkan 7.706 rule. Basis data rule yang diperoleh dari proses pembelajaran dan basis data perubahan jenis kata berdasarkan imbuhan digunakan untuk proses pengujian sistem. Pengujian menggunakan 52 dokumen teks yang terdiri dari 131.719 token. Pengujian menghasilkan 97,82 % token yang berhasil dikenali . Pengujian manual terhadap 3 dokumen yang terdiri dari 431 token menghasilkan tingkat kebenaran 85,85%.
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Judul: Named entity tagging untuk dokumen berbahasa Indonesia menggunakan metode berbasis aturan
Abstrak: The main objective of this research is to implement named entity tagging in Indonesian documents. Rule-based method is used for this research. This method uses various rules to identify words or phrase to know if that words or phrase can be classified as named entity. Named entity form obtained from the named entity tagging can be classified in six forms, there are <NAME>, <ORGANIZATION>, <LOCATION>, <CURRENCY>, <DATE>, <TIME>, and <NUMBER> to identify the name of people, organizations, places, currency, date, time, and number. In addition of using rules, dictionary is also used to identify named entity <NAME>, <ORGANIZATION>, and <LOCATION>. The evaluation is done by using 91 document samples from a total of 1.000 documents. Evaluation is based on rules and performance of the system. Evaluation based on the rule is done by comparing the result from the manual test with the result from the system test. The results of the evaluation can identify the accuracy level of the system. There are 3.599 named entities classificated from the total 3.641 named entities in 91 documents. There are 99 unclassified named entities, 87 wrong classified named entities. Entities are classified consist of 514 NAME named entities, 576 ORGANIZATION named entities, 1.376 LOCATION named entities, 117 CURRENCY named entities, 341 DATE named entities, 4 TIME named entities, and 680 NUMBER named entities. From this evaluation, it can be concluded that the more documents are analyzed, the better level of identification can be found. In the evaluation of system performance, evaluation is done by the time and the number of words, and by the time and the many of named entities. From this evaluation, it also concluded that the number of words and the many of named entities contained in the document is very influential on the time required in the process of named entity tagging.
Keyword: Information Retrieval, Question Answering, Document Preprocessing, Named Entity Tagging, Named Entity Recognition, Rule-Based

Judul: Growth, Concentration Chlorophyll-a, and Structure of Macroalgae Gracilaria edulis in the Culture Media Containing Copper
Abstrak: The physiological responses (specific growth rate, concentration of chlorophyll-a, morphological and anatomical structure of the vegetative cells) of the marine macroalga Gracilaria edulis at the different concentrations of copper (0.01 as control, 0.04, 0.06 and 0,5 ppm) delivered continuously for 28 days under controlled laboratory conditions were investigated. Result showed that the degree of copper toxicity depends on both factor the concentration and exposure time. Copper concentration and day of exposure decreased significantly the specific growth rate (SGR) of the Gracilaria edulis but only 0,5 ppm Cu decreased the chlorophyll-a content when compared to control. Of the various physiological end points measured, growth proved to be the most sensitive response than chlorophyll-a with reductions in specific growth rate (SGR). The reason for this could be related to a greater sensitivity of the enzymes involved in growth than those related to chlorophyll-a or a greater energy needs to maintain cellular integrity and metabolic processes under sublethal Cu stress. In all cases, the main effect on vegetative cells were structure changes in cortex and subcortex cells, compared to control, macroalgae exposed to copper showed depigmentation and blending in the lateral branches, heavy staining of the cell wall and severe damage of cell membrane, while the mucilage and the cell walls was densely fibrillar, thick and heavily stained, the cortex cell was clearly vacuolated, the presence of endophytic on the cell wall and endophytic spores in the mucilage. The presence vacuoles should be related to a metal immobilization mechanism, minimizing the Cu toxicity for cells. The epiphytic bacteria can act as a biofilter diminishing the availability of Cu for macroalgae accumulation.
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