Judul: Analisis Beban Tangan pada Layout Keyboard QWERTY Berdasarkan Letter Frequency pada Dokumen Skripsi Mahasiswa FMIPA IPB
Abstrak: Papan ketik atau keyboard merupakan perangkat masukan pada komputer. Salah satu yang umum digunakan yaitu keyboard dengan layout QWERTY. Penempatan karakter alfabet pada layout keyboard disusun berdasarkan letter frequency. Penempatan karakter alfabet akan berpengaruh pada beban tangan saat mengetik. Beban tangan yang tidak seimbang antara tangan kanan dan kiri akan mengakibatkan rasa tidak nyaman bahkan cedera pada tangan. Penelitian ini bertujuan untuk mengetahui perbandingan beban tangan antara tangan kanan dan kiri berdasarkan letter frequency, mengetahui pengelompokan karakter alfabet dengan letter frequency tinggi pada tangan kanan dan kiri, serta mengetahui tebaran hotspot karakter alfabet pada layout keyboard QWERTY berdasarkan letter frequency pada dokumen skripsi mahasiswa Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA) Institut Pertanian Bogor (IPB). Metode yang digunakan yaitu cluster analysis dan hotspot analysis dengan teknik penarikan contoh menggunakan stratified sampling. Hasil analisis beban tangan diperoleh nilai selisih persentase beban tangan pada Strata 1, 2, dan 3 bernilai negatif menunjukkan beban tangan kiri lebih besar dibandingkan beban tangan kanan. Jumlah gerombol optimum yang terbentuk pada Strata 1, 2, dan 3 sebanyak 4 gerombol. Penggerombolan karakter alfabet dengan letter frequency tinggi pada tangan kanan dan kiri relatif seimbang. Teridentifikasi adanya hotspot pada taraf nyata 5%., Keyboard is an input device on the computer. One of the commonly used is a keyboard with a QWERTY layout. The placement of alphabetic characters on the keyboard layout is arranged based on the letter frequency. The placement of alphabetic characters will affect the hand load when typing on the keyboard. An unbalanced hand load between the right and left hands will cause discomfort and even injury to the hand. This study aims to determine the comparison of the hand load between the right and left hands based on letter frequency, to determine the grouping of alphabetic characters with high letter frequency on the right and left hands, and to find out the distribution of alphabetic character hotspot on the QWERTY keyboard layout based on letter frequency on student undergraduate thesis document of Faculty of Mathematics and Natural Sciences (FMIPA) IPB University (IPB). The methods used in this research are cluster analysis and hotspot analysis with sampling technique using stratified sampling. The result of the hand load analysis obtained the value of the difference in the percentage of hand load in Strata 1, 2, and 3 negative values showed that the left hand load is greater than the right hand load. The optimum number of clusters formed in Strata 1, 2, and 3 is 4 clusters. The clusters of alphabetic characters with high letter frequency on the right and left hand are relatively balanced. It is identified that there are hotspot at a significance level of 5%.
Keyword: analisis gerombol, analisis hotspot, frekuensi huruf, papan ketik qwerty, penarikan contoh berlapis, cluster analysis, hotspot analysis, letter frequency, qwerty keyboard, stratified sampling

Judul: Analisis penekanan kunci dinamik untuk verifikasi biometrik berbasis jaringan syaraf tiruan propagasi balik
Abstrak: ARIF BUDIMAN. Dynamic keystroke analysis for biometric verification based on artificial neural network backpropagation. Under the direction of SUGI GURITMAN and HERU T. NATALISA. Biometric keystroke analysis studies the typing pattern of human behavior. Literature journals show a good prospect for a verification system and commonly use static method (where training data is similar with the verification data). This research uses dynamic analysis method. The data will be analyzed into certain dominant character pairs so that it is possible for training data to be different than the verification data (using random data display). The dominant character pairs were obtained from preliminary research which was conducted to specifically analyze 756 words in the Indonesian language. It is based on left-right finger movement. The character pairs are an, ng, la, en, ka while the cluster of close character pairs are (ng,ba,ma,na,nd), (an,am,ab), (su,au,ay,gu,di,du,di,ai), (pa,is,ia,ya,ua,us), and (ri,ti,ru,tu,ro,to,ep). The system prototype uses three variables, namely duration (d), interkey (i) and total time (T). Each variable has its own separated Artificial Neural network (ANN) by pre-processing input into five fuzzy classes (SC, C, S, L, SL). The training algorithm is backpropagation and uses two types of training models: A (crispy) and B (ambiguity). The training data were obtained by statistical analysis (mean, median, modus, standard deviation, minimum, maximum) and from fuzzy class pattern complementary data for each character pairs. The research was conducted to study the effect of keyboard layout on False Rejection Rate (FRR) percentage, the effect of data re-taken on % FRR, the effect of ANN verification test on the responses to the new exclusive data (which had never been included in training process). It also studies the effects of identification tests in terms of False Acceptance Rate (FAR) percentage on ANN training model A and B, and the effect of overall response in % FRR on intrusion detection. The conclusions are that model A gives lower % FRR and higher % FAR than model B while model B has a more flexible value of the decision threshold to be used as fuzzy output model in future research. The system stability is affected significantly by keyboard layout and environment conditions during typing. However, the data re-take process carried out more than 56 days afterwards still gave consistent results. ANN has the capability to recognize exclusive data with relatively lower % FRR results. Intrusion can be detected easily by spotting the existence of the % FRR spike. This model has a good capability for Biometric keystroke verification with dynamic text typing but still requires more research for Biometric identification.
Keyword: 

Judul: Hydroxyapatite-Chitosan Composite Coating on Stainless Steel 316 to Improve Corrosion Resistance
Abstrak: Metals that were used in bone implantation should have good corrosion resistance that were not easily corroded when implanted into the body. Metal corrosion resistance of stainless steel 316 can be enhanced through the metal coating by hydroxyapatite-chitosan composite with composition ratio of hydroxyapatite (gram) and chitosan 3% (mL) 0.2:0, 0.2:0.1, 0.2:0.5, 0.2:1.0, and 0.2:1.5. Besides improving the corrosion resistance of metal, the presence of chitosan also maintain the position of hydroxyapatite on metal surfaces. Corrosion resistance increases with increasing amount of chitosan added and the best composition of hydroxyapatite-chitosan composite was 0.2:1.0.
Keyword: