Knowledge management (KM) is an important thing to store or possess existing knowledge. The difficulty of getting knowledge that has actually been known for a long time about special planning for new information is to repair a certain position, in this case the container that contains several private universities in Palembang. The lecturer can only find out how the system discusses in the college, and many other knowledge that must be discussed by the new lecturer. Therefore the Knowledge Management System (KMS) will be built using the Inukshuk Model to become a means for existing knowledge, while the algorithm for searching knowledge stored in KMS is the Levenshtein Algorithm. The selection of the Levenshtein algorithm itself which uses this algorithm measures the relationship between strings (words to words, words to sentences and sentences to sentences) by calculating the edit distance, so that it will produce a high level of acquisition. The result is a KMS that is important for private universities to store and manage knowledge web-based services to make it easier for today's users to use many internet networks.
This research conducted classification testing on the study case of student graduation prediction in a university. It aims to assist the university in maintaining academic development and in finding solutions for improving timely graduation. This study combined two methods, i.e., Naive Bayes and Particle Swarm Optimization, to produce a better level of accuracy. The Naive Bayes method is a statistical classification method used to predict a student's graduation in this study. That will be further enhanced using the Particle Swarm Optimization method to produce a better level of accuracy. There are 10 (ten) samples in this study randomly selected from the alumni data of UIGM students in 2011-2014. From the test results, this research resulted in an accuracy value of 90% from the Naive Bayes algorithm testing, after testing the Naive Bayes with Particle Swarm Optimization, which produced an accuracy value of 100%. The conclusion obtained from the results is the Naive Bayes method has a higher accuracy value if combined with Particle Swarm Optimization. Thus the university can more easily predict whether or not the students graduate on time for the upcoming graduation period. The results of this test prove that to predict student graduation using the Naive Bayes method with Particle Swarm Optimization is appropriate.
ABSTRAKPraktikum indikator asam basa alami biasanya dilakukan dengan mengekstrak bahan alam dengan pelarut tertentu, menguji ekstrak dengan berbagai macam larutan asam, basa dan netral, mencatat perubahan warnanya, menyimpulkan dan pada akhirnya hasil ekstrak dibuang. Pembuatan indikator asam basa alami yang tahan lama diperlukan guna mengurangi pembuangan bahan yang berlebihan. Penelitian ini dirancang untuk menghasilkan indikator asam basa alami dari ekstrak pucuk daun pucuk merah (PDPM). Ektraksi PDPM dilakukan dengan metode maserasi menggunakan pelarut etanol 95% selama 13 jam. Hasil ekstraksi PDPM (larutan indikator PDPM) selanjutnya digunakan untuk membuat kertas indikator PDPM dengan merendam kertas saring didalam larutan indikator, dikeringkan pada suhu ruang (tanpa sinar matahari). Kedua indikator diuji perubahan warnanya pada larutan pH 1-13. Uji ketahanan dan performa kedua indikator juga diuji hingga 6 hari. Absorbansi larutan indikator PDPM diukur pada panjang gelombang 300-400 nm menggunakan spektrofotometer UV-Vis. Hasil penelitian menunjukkan bahwa larutan dan kertas indikator PDPM dapat digunakan sebagai indikator asam basa, bahkan dapat menentukan kisaran pH dari suatu larutan. Perubahan warna indikator PDPM dari pH asam ke pH basa adalah merah muda-hijau pudar-hijau lumut-cokelat. Kedua indikator menunjukan performa yang baik pada perubahan warnanya di dalam larutan pH 1-13 hingga hari keenam penyimpanan. Jadi ekstrak etanol PDPM dapat dijadikan bahan dasar pembuat indikator asam basa alami. Kata kunci: Pucuk Merah, Syzygium oleana, indikator alami, asam basa ABSTRACTExperiment on natural acid-base indicators is usually done by extracting the natural sources with certain solvent, testing the extract with acid, base and neutral solutions, observing the color changes, making conclusion and discharging the remaining extract at the end of the experiment. Production of long-lasting natural acid-base indicator is needed to reduce the discharged of chemicals excessively. This research was carried out to produce natural acid-base indicator from extract of shoot leaves of Syzygium oleana (SLS). The extraction was done by maceration technique using ethanol 95% for 13 h. The extract of SLS (SLS indicator solution) is
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