: Mata Kuliah Pilihan Konsentrasi
Semester II : Mata Kuliah Pilihan Konsentrasi
A. Konsentrasi Statistika Sosial (15 SKS)
No . Kode MK
Mata Kuliah
SKS
1 D20O.208 Sampling Survey 3-0
2 D20O.206 Structural Equation Modelling 3-0
3 D20O.210 Statistika Nonparametrik 3-0
4 D20O.207 Analisis Data Deret Waktu 3-0
5 D20O.209 Analisis Data Kategori 3-0
B. Konsentrasi Statistika Bisnis dan Industri (15 SKS)
No . Kode MK
Mata Kuliah
SKS
1 D20O.208 Sampling Survey 3-0
2 D20O.206 Structural Equation Modelling 3-0
3 D20O.210 Statistika Nonparametrik 3-0
4 D20O.207 Analisis Data Deret Waktu 3-0
5 D20O.209 Analisis Data Kategori 3-0
C. Konsentrasi Statistika Aktuaria (12 SKS)
No . Kode MK
Mata Kuliah
SKS
1 D20O.213 Matematika Aktuaria 1 3-0
2 D20O.214 Matematika Aktuaria 2 3-0
3 D20O.212 Matematika Keuangan 3-0
4 D20O.215 Survival Analysis 3-0
D. Konsentrasi Statistika Biomedis (15 SKS)
No . Kode MK
Mata Kuliah
SKS
1 D20O.216 Epidemologi 3-0
2 D20O.217 Survival Analysis 3-0
3 D20O.211 Desain Eksperimen 3-0
4 D20O.218 Clinical Trials 3-0
5 D20O.209 Analisis Data Kualitatif 3-0
Semester III
A. Konsentrasi Statistika Sosial (10 SKS)
No . Kode MK
Mata Kuliah
SKS
1 D20O.120 Data Mining And Competitive Intellegence 3-0
2 D20O.123 Seminar 1-0
3 D20O.124 Tesis 6-0
B. Konsentrasi Statistika Bisnis Industri (10 SKS)
No . Kode MK
Mata Kuliah
SKS
1 D20O.120 Data Mining And Competitive Intellegence 3-0
2 D20O.123 Seminar 1-0
3 D20O.124 Tesis 6-0
C. Konsentrasi Statistika Aktaria (13 SKS)
No . Kode MK
Mata Kuliah
SKS
1 D20O.121 Teori Risiko 3-0
2 D20O.122 Pension Plan 3-0
3 D20O.123 Seminar 1-0
4 D20O.124 Tesis 6-0
D. Konsentrasi Statistika Biomedis (10 SKS)
No . Kode MK
Mata Kuliah
SKS
1 D20O.125 Statistika Bioinformatika 3-0
2 D20O.123 Seminar 1-0
3 D20O.124 Tesis 6-0
Daftar dan Deskripsi Mata Kuliah D20O.101 Teori Statistika
Multivariat, Inferensi Vektor Mean
Populasi (Manova), Perbandingan Pendahuluan (Gambaran umum contoh
3(3-0) SKS
Beberapa Vektor Mean Populasi aplikasi penaksiran parameter dari
(Manova), Analisis Regresi Multivariat, sekumpulan data: mortalitas/survey),
Analisis Diskriminan, Analisis Conjoint, Metode Momen dan Metode Kuadrat
Korelasi Kanonik, Analisis Komponen Terkecil untuk menaksir parameter,
Utama, Analisis Faktor, Analisis Kluster, Metode Kemungkinan Maksimum
Analisis Korespondensi, Multidimen- untuk menaksir parameter, Metode Ex-
sional Scaling, Penanganan Data Hilang pectation Maximization (EM) untuk
(Missing data).
menaksir parameter, Sifat penaksir : Tak bias, varians minimum, Statistik
Pustaka:
cukup, Konsisten, dan contoh
1. Sharma, S. (1995). Applied Multivariate aplikasinya, Informasi Fisher, Batas
Techniques,Wiley, New York. Bawah Cramer Rao, Taksiran Interval,
2. Johnson and Winchern (2007), Applied Strategi Perumusan Hipotesis, Uji
Multivariate Statistics, Pearson Educa- Statistik, Kekeliruan Tipe I dan Tipe II,
tion, New York. Kuasa Uji, Derajat Kepercayaan, Uji
Paling Kuasa Seragam, Uji Likelihood
D20O.103 Analisis Regresi
Ratio Test, Uji Generalized Likelihood
3(3-0) SKS
Ratio Test, Inferensi Parameter Populasi Simple Linear Regression (Linear Re- gression with One Predictor dan Infer-
Pustaka: ence in Regression Analysis), Multiple
1. Hogg, R.V. McKean, J dan Craig, A.T. Linear Regression (Multiple Regression (2013), Introduction to Mathematical Sta-
1 dan Multiple Regression 2), Building tistics (7th Edition), Pearson, New Jer-
the Regression Model I, (Diagnostic 1 sey
dan Remedial Measures), Building the
2. Rice., J. A. (2007), Mathematical Statis- Regression Model II, (Selection of Pre- tics and Data Analysis, Edisi Ke-3,
dictor Variables dan Diagnostic 2). Duxbury Press, Belmont.
Pustaka:
D20O.102 Analisis Data Multivariat
1. Applied Linear Statistical Models, Netter
3(3-0) SKS
et.al (1996).
Pendahuluan, Peragaan Grafik, Normal
2. Classical and Modern Regression with Multivariat, Distribusi Sampling
Application, Myers, R.H. (1990).
D20O.104Proses Stokastik
(MCMC), Algoritma Metropolis-Hasting
dalam MCMC, Gibbs Sampling dalam Markov Chains (Transition Prob. Matri-
3(3-0) SKS
MCMC, Monitoring Konvergensi MCMC ces, First Step Analysis, Functional of
Random, Walk and Success Runs, The
Pustaka:
Long Run Behavior). Process Poisson
1. Rizzo, Maria L. (2008) Statistical Com- (The Poisson Process and the Uniform
puting With R, Chapman & Hall, New Distribution, Compound Poisson Pro-
York.
cesses, Non-Stationary Poisson Pro-
2. Albert, Jim. (2009) Bayesian Computing cesses).
With R., Springer., New York. ContinuousTime Markov Chains (Pure
3. Givens, Geof H., Hoeting, Jennifer A. Birth / Pure Death Processes, Birth and
(2013) Computational Statistics. Jon Death Processes, Birth and Death Pro-
Wiley & Sons, New Jersey. cesses with Absorbing States, Finite
State Continuous Time Markov Chains)
D20O.206 Structural Equation
Renewal Phenomena (Definition and
Modelling
Some examples of Renewal Processes,
3(3-0) SKS
The Poisson Process Viewed as a Re- Motivasi, sejarah, dan ruang, newal Processes).
lingkupStructural Equation Modeling, Konsep dan model kausalitas, Model
Pustaka: umum persamaan structural, Estimasi,
1. Karlin, S., Howard M. Taylor, (1998), An Inferensi dan evaluasi, Mx, Model-model Introduction to Stochastic Modeling, Third
khusus, Model untuk multigroup, Model Edition, Academic Press, New York,
dengan struktur rata-rata, Analisis untuk
2. Sheldon Ross, (1983), Stochastic Pro- data Non-normal data. cesses, Second Edition, John Wiley & Sons, Inc., New York.
Pustaka:
1. Bollen, K.A. (1989), Structural Equations
D20O.105 Komputasi Statistik
with Latent Variables, John Wiley &
Sons, New York. Membangkitkan Variabel Acak, Integrasi
3(3-0) SKS
2. Jöreskog, K. &Sörbom, D. (1996), Numerik, Metode Optimasi, Algoritma
LISREL 8: User's Reference Guide, Sci- EM Metode Jackknife, Metode Bootstrap
entific Software International, Chicago. dalam Penaksiran Parameter, Metode
3. Neale, M.C., Boker, S.M., Xie, G., Bootstrap dalam Analisis Data, Metode
&Maes, H.H. (2003) Mx: Statistical Mod- Integrasi Monte Carlo, Metode Monte
eling, Department of Psychiatric - VCU, Carlo dalam Penaksiran, Metode Monte
Richmond.
Carlo dalam Pengujian Hipotesis,
4. Jöreskog, K. &Sörbom, D. (1979), Ad- Metode Marcov Chain Monte Carlo
vanced in Factor Analysis and Structural
Equation Models, Abt Books, Massachu-
5. Nina Golyandina,Vladimir Nekrutkin & setts.
Anatoly A.Zhigljavsky (2001), Analisys of
5. Byrne, B.M. (1998) Structural Equation Time Series Structure, SSA and Related Modeling with LISREL, PRELIS, and
Techniques, Chapman & Hall. SIMPLIS: Basic Concepts, Applications, and Programming, Lawrence Erlbaum,
D20O.208 Sampling Survey
London.
(3-0) SKS
6. Kline, R.B. (2005) Principles and Prac- Populasi dan Sampel, Tipe-tipe Sam- tice of Structural Equation Modeling, 2nd
pling, Sampling Acak Sederhana, Sam- ed., the Guilford Press, New York.
pling Sistematis, Sampling Acak
7. Maruyama, G.M. (1998) Basic of Struc- Stratifikasi, Sampling Cluster. tural Equation Modeling, SAGE, London.
Pustaka:
D20O.207 Analisis Data Deret Waktu
1. Cochran, William G. (1977) Sampling
Techniques. John Wilwy & Sons, New Pemodelan ARIMA, Pemodelan
(3-0) SKS
York.
Intervensi, Pemodelan Dengan Metode
2. Scheeaffer, Richard L., Mendenhall, Wil- Singular, Spectrum Analysis (SSA),
liam, Ott, Lyman, (1990) Elementary Analisis Spektral, Pemodelan Fungsi
Survey Sampling, Duxburry Press, Cali- Transfer, Pemodelan Vektor Autoregresi,
fornia.
Pemodelan Nonlinear (Threshold
3. Lohr, Sharon l. (1999), Sampling Design Autoregresi).
and Analysis, Duxburry Press, Califor- nia.
Pustaka:
4. Chaudhuri, Arijit, Stenger, Horst (2005)
1. Bovas,A & Ledolter,J (2005),"Statistical Survey Sampling: Theory and Methods. Methods for forecasting", John Wiley &
Chapman Hall / CRC, London. sons, New Jersey, Canada.
2. Cryer,J & Chan, K-S ( 2008), " Time Se-
D20O.210 Statistika Nonparametrik
ries Analysis With Applications in R",
3(3-0)SKS
Springer, New York,USA. Masalah Dua Sampel Berpasangan,
3. Makridakis,Wheelwright,McGee (1999), Masalah Dua Sampel Saling Bebas, Metode
Regresi Parametrik (ekspektasi Peramalan,Binarupa Aksara, Jakarta,
Dan
Aplikasi
bersyarat, kurva regresi, bootstrap), Indonesia.
Regresi Nonparametrik (data binomial,
4. W. W. S. Wei , (2006) , Time Series smoothing, bandwidth window, Kernel Analysis : Univariate and Multivariate
Fitting distribusi Methods , Redwod City , Addison-
W eighting),
(Kolmogorov Smirnov). Wesley Pub. Co, Inc.
Pustaka: ing process, lemma Ito, rumus Black-
1. Higgins, J.J. (2004) Introduction to Mod- Scholes, persamaan diferensial parsial ern Statistical Nonparametrics, Duxbury
Black-Scholes, penentuan harga aset Press, California
dengan model binomial, dari model bi-
2. Gibbons,J.D. (2010), Nonparametric Sta- nomial ke rumus Black-Scholes. tistical Inference, Chapman and Hall, London.
Pustaka:
1. Kellison G. Stephen, The Theory of Inter-
D20O.211 Desain Eksperimen
est, Georgia State 2nd Ed. , Irwin
McGraw-Hill, 1991. Konsep Dasar Desain Eksperimen,
3 (3-0)SKS
2. Bodie, Z. dkk. Investment 4th Ed., Irwin Konsep dasar desain satu faktor dengan
McGraw-Hill, 1999. analisis varians, Model-model Faktorial
3. Hull, J.C., Options, Futures and Other tanpa interaksi dan model faktorial
Derivatives 5th Ed., Prentice Hall, 2002. dengan interaksi, Model Faktorial 2k,
4. Radcliffe, R. C., Investment 5th Ed., Faktorial 3k, Faktorial Tersarang, Split
Addison Wesley Longman Inc., 1998. Plot,Topik Khusus (Analisis Kovarians,
5. Stampfli J. dan Goodman V., The Math- Permukaan Respon).
ematics of Finance, Modelling and Hedg- ing, Brooks/Cole, 2001.
Pustaka:
6. Panjer Harry H., Financial Economics:
1. Montgomery Douglas C. Design and with Applications to investments, Insur- Analysis of Experiments, third ed., John
ance, and Pension, The Actuarial Foun- Wiley & Sons, 1991.
dation, 1998.
2. Box Hunter, Statistics for Experimenter,
7. Baxter, Rennie, Financial Calculus, Univ. John Wiley & Sons, 1995
Press, Cambridge, 1997.
3. Park,S.H.(1996). Robust Design and
8. Ross, S.M., An Introduction to Math- Analysis for Quality Engineering,
ematical Finance, Options and Other Springer, New York.
Topics, Cambridge, University Press, 1999.
D20O.212 Matematika Keuangan
3 (3-0) SKS
D20O.213 Statistika Quality Control
Dasar-dasar investasi, teori portofolio,
3(3-0) SKS
model-model keseimbangan, market Quality Management, Statistical Quality model: single-period market model, the
Control I (Basic Consept of Statistical law of one price, put-call parity, Wiener
Quality), Statistical Quality Control II process (brownian motion), representasi
(Control Charts), Statistical Quality Con- random walk dari brownian motion, gen-
trol III (Acceptance Sampling), Total Qual- eralized brownian motion: Ito process,
ity Management, Six Sigma. geometric brownian motion, mean revert-
Pustaka:
D20O.120 Data Mining & Competitive
1. Montgomery, D.C. (2009), Introduction to
Intelligence3
Statistical Quality Control, Sixth Edition.
(3-0) SKS
John Wiley & Sons, New York. Konteks data mining, metodologi,
2. Lenz, H.J. dan Wilrich, P.T. (2004), Fron- teknik-teknik dan algoritma, memilih tiers in Statistical Quality Control.
sumber-sumber data, membangun Physica_Verlag, Berlin.
model-model prediktif, mempersiapkan
3. Rosander AC (1985). Applications of lingkungan data mining, kasus-kasus, Quality Control in the Service
konsep dan metodologi competitive in- Industries.Marcel Dekker,New York.
telligent, kasus competitive intelligent.
4. Ryan, T.P. (1989), Statistical Methods for Quality Improvement. John Wiley &
Pustaka:
Sons., New York.
1. Giudici P., Figini S., Applied data min-
5. Taguchi, G., Elsayed, E.E., dan Hsiang, ing. John Willey & Sons. 2009. T.C. (1989), Quality Engineering in Pro-
2. Nisbet R., Elder J., Miner G., Handbook duction Systems. McGraw-Hill,
of statistical analysis & data mining ap- Singapura
plication. Elsevier. 2009.
Pengampu dan Dosen Program Studi
1. Prof. Dr. Budi Nurani Ruchjana, MS
2. Prof. Dr. Sutawanir Darwis
3. Septiadi Padmadisastra, Ph.D
4. Dr. Jadi Suprijadi, DEA
5. Dr. Lienda Noviyanti, M.Si.
6. Dr. Toni Toharudin, M.Sc
7. Gandhi Pawitan, Ph.D
8. Dr. Suwanda
9. Dr. Nusar Hajarisman, M.Si
10. Dr. Yudhie Andriyana, M.Sc
11. Gatot Riwi Setyanto, S.Si, M.Si
12. Achmad Bachrudin, Drs.,MS
13. Enny Supartini, Dra., MS.
14. Yusep Suparman, M.Sc
15. Zulhanif, S.Si, M.Sc
16. Bertho Tantular, S.Si, M.Si
17. Gumgum Darmawan, S.Si, M.Si
18. Budhi Handoko, S.Si, M.Si
19. I Gede Nyoman Mindra Jaya, S.Si, M.Si
20. Titi Purwandari, S.Si, MS.