Romi Km 01 Introduction Sep2015

7/21/2019 Romi Km 01 Introduction Sep2015

http://slidepdf.com/reader/full/romi-km-01-introduction-sep2015 1/70



Romi Satria Wahono

• SD Sompok Semarang (1987)

• SMPN 8 Semarang (1990)

• SM !ar"na N"#antara Magelang (

199$)

• %&'ng M&'ng and Ph&D in Sotware 'ngineering romSaitama *ni+er#it, -apan (199./00.)*ni+er#iti !eknikal Mala,#ia Melaka (01.)

• Re#earh 2ntere#t#3 Sotware 'ngineering andMahine 4earning

• 5o"nder dan Koordinator 2lm"Komp"ter&6om

• Peneliti 42P2 (00./007)

• 5o"nder dan 6' P! %rainmati# 6ipta 2normatika

2



!etook#

3



6ontent#

1.Introduction

1&1 What and Wh, Knowledge Management1& !,pe# o Knowledge1&$ Knowledge !ran#ormation

2.Foundations

&1 Knowledge Management 2nra#tr"t"re& Knowledge Management Mehani#m&$ Knowledge Management !ehnologie#

3. Solutions$&1 Knowledge Management Proe##e#$& Knowledge Management S,#tem#

4. Systems

.&1 Knowledge ppliation S,#tem#

.& Knowledge 6apt"re S,#tem#

.&$ Knowledge Sharing S,#tem#

.&. Knowledge Di#o+er, S,#tem#

5.Assessment

:&1 rgani;ational 2mpat# o KnowledgeManagement:& !,pe o Knowledge Management##e##ment

4



1& 2ntrod"tion

1&1 What and Wh, Knowledge Management

1& !,pe o Knowledge

1&$ Knowledge !ran#ormation

1&. Knowledge Management Sol"tion# and5o"ndation# 5



1&1 What and Wh, KnowledgeManagement

6





Dimana kar Ma#alahn,a=

• Ketika pegawai meninggalkanper"#ahaan pengetah"anmerekap"n ik"t pergi >

• Mereka dan organi#a#i (ompan,)

tidak mengelola pengetah"ann,adengan aik #ehingga tran#erpengetah"an tidak ter<adi

8



Karena it" >

• rgani#a#i perl" mengelolapengetah"an anggotan,a "nt"k3

• Mengetah"i kek"atan (dan penempatan)#el"r"h SDM

• Pengg"naan kemali pengetah"an ,ang#"dah ada (ditem"kan) tidak perl"meng"lang pro#e# kegagalan

• Memperepat pro#e# peniptaan

pengetah"an ar" dari pengetah"an ,angada

• Men<aga pergerakan organi#a#i tetap #tailme#kip"n ter<adi ar"# kel"ar/ma#"k SDM

• Kon#ep ,ang "tama adalah #etiap9



Knowledge Management

Salah #at" aang ilm" mana<emen,ang ok"# ke peningkatanpengetah"an integra#i dan

pengg"naan,a di organi#a#i

(Mark M#'ro)$

*nowe,e Mana,ement -onsorti"m&

10



Knowledge Management

Knowledge management an e de?ned a#perorming the ati+itie# in+ol+ed indi#o+ering apt"ring #haring and

appl,ing knowledge #o a# to enhane in ao#t/e@eti+e a#hion the impat oknowledge on the "nitA# goal ahie+ement&

(e#erraernane$ 2010&

11



6ontoh M"dah KnowledgeManagement

Mailinglist dengan TemTroubleshooting P

Member !ertanya tentaSuatu Masalah

Member "ain Men#a$ab

!erdasar Pengalaman

Member "ain Men#a$ab

!erdasar !u%u &ang 'ibaca

Moderator Merang%um%anPertanyaan dan (a$aban

)dalam bentu% FA*+5B3 5reC"entl, #kedB"e#tion

12





5ore# Dri+ing KnowledgeManagement

• 2nrea#ing Domain 6ompleit,3 2ntria, o internal eternal proe##e# inrea#ed ompetition andthe rapid ad+anement o tehnolog, allontri"te to inrea#ing ompleit,

• elerating Market Eolatilit,3 !he pae o hangeor +olatilit, within eah market domain ha#inrea#ed rapidl, in the pa#t deade

• 2nten#i?ed Speed o Re#pon#i+ene##3 !he timereC"ired to take ation a#ed "pon #"tle hange#within and aro## domain# i# derea#ing

• Dimini#hing 2ndi+id"al 'periene3 Figh emplo,eet"rno+er rate# ha+e re#"lted in indi+id"al# withdei#ion/making a"thorit, ha+ing le## ten"re

within their organi;ation# than e+er eore14



!he 2mportane oKnowledge Management

• KM i# important or organi;ation# thatontin"all, ae down#i;ing or a hight"rno+er perentage d"e to the nat"re o

the ind"#tr,

• !oda,A# dei#ion maker ae# thepre##"re to make etter and a#ter

dei#ion# in an en+ironmentharateri;ed , a high domainompleit, and market +olatilit, e+en inlight o

• 4ak o eperiene t,piall, rom thedei#ion/maker15



1& !,pe o Knowledge

16



Delarati+e +# Proed"ral

1& Delarati+e knowledge (#"#tanti+eknowledge) o"#e# on elie# ao"trelation#hip# among +ariale# (knowwhat )• Propo#ition# epeted orrelation# or

orm"la#

• 'ample3 !he e@et that the C"alit, o eahomponent wo"ld ha+e on the ?nal prod"t

& Proed"ral knowledge o"#e# on elie#relating #eC"ene# o #tep# or ation# to

de#ired (or "nde#ired) o"tome# (knowhow 17



!ait +# 'pliit

1& 'pliit Knowledge3 pengetah"an ,angtert"li# terar#ip ter#ear (etakma"p"n elektronik) dan i#a #eagaiahan pemela<aran (reeren#e) "nt"k

orang lain

& !ait Knowledge3 pengetah"an ,ang

erent"k know/how pengalaman #killpemahaman ma"p"n r"le# o th"m

Gpengetah"an kita <a"h leih an,akdari ada an kita eritakanH Mihael18



Ieneral +# Spei?

1& Ieneral knowledge i# po##e##ed , alarge n"mer o indi+id"al# and an etran#erred ea#il, aro## indi+id"al#• 'ample3 Knowledge ao"t the r"le# o

a#eall

& Spei? knowledge i# po##e##ed , a+er, limited n"mer o indi+id"al# andi# epen#i+e to tran#er& 6an e di+idedinto ontet"all, #pei? and tehniall,#pei?

• 'ample3 !he oah ha# the knowledgeneeded to ?lter rom the hao# o the ame19



20



21



Knowledge Ei#"ali;ation

• *nt"k <eni# knowledge ,ang deklarati tool+i#"ali#a#i pengetah"an ,ang #aat ini an,akdig"nakan adalah MindMap ,angdikemangkan !on, %";an

• 6ara merangk"m ,ang kreati eekti danmemetakan pikiran/pikiran kita #eara menarikdan m"dah

• 6ara mengemangkan kegiatan erpikir ke

#egala arah (di+ergen) menangkap eragaipikiran dalam eragai #"d"t

• lat erpikir organi#a#ional ,ang eekti

• 6ara term"dah "nt"k menempatkan inorma#i

ke dalam otak dan mengamil inorma#i it"ketika di"t"hkan22



23



24



25



26



27



4atihan

• %erikan eerapa ontoh "nt"k#em"a <eni# knowledge ,angterdapat pada organi#a#i tempat

ada eker<a• Sa<ikan dalam ent"k mindmap

28



%"#ine## Proe## ModelingNotation (%PMN)

• %PMN i# a graphi notation that de#rie#the logi o the #tep# in a %"#ine## Proe##

• !hi# notation ha# een e#peiall, de#igned

to oordinate the #eC"ene o proe##e# andme##age# that Jow etween partiipant# odi@erent ati+itie#

• 2t wa# de+eloped , the organi;ation %PM2nitiati+e made , the <et ManagementIro"p (MI)

• !hi# mean# great po##iilitie# or %PMN toeome the #tandard lang"age regarding"#ine## proe##e# like *M4 whih ha#eome the #tandard or #otware modeling29



%PMN Pro#e# Penent"an%ea#i#wa

Pro#e# penent"an ea#i#wa di *ni+er#ita#S"ka %ela<ar3

1& Pro#e# dim"lai dari dmini#tra#i "ni+er#ita#meng"m"mkan lowongan ea#i#wa

mengg"nakan eragai media

& Maha#i#wa melak"kan pendataran danmengirimkan dok"men per#,aratan

$& Komite *ni+er#ita# melak"kan #elek#i (#elek#ipro?le dan #elek#i wawanara)

.& Peng"m"man ha#il penerimaan ea#i#wa akandi#earkan oleh admini#tra#i "ni+er#ita#

melal"i email dan papan peng"m"man30



Pro#e# Penent"an %ea#i#wa

31



Meng"m"mkan 4owongan%ea#i#wa

32



33



34



35



4atihan

• Dari MindMap ,ang #eel"mn,a#"dah digamarkan

• Iamarkan #at" pro#e"ra

knowe,e ,ang #iatn,a ta#it ,angterdapat pada organi#a#i tempatada eker<a

• Iamarkan dengan mengg"nakandiagram %PMN

36

4 ti K l d



4oation o Knowledge(Re#er+oir#)

37



4atihan

• %erda#arkan knowledge re#er+oir#,ang ada di "k" kemangkanKnowledge Re#er+oir# ,ang tepat

"nt"k organi#a#i tempat kitaeker<a

• !empatkan knowledge ,ang #"dahkita detek#i pada latihan#eel"mn,a ke KnowledgeRe#er+oir# ,ang tepat

• Sa<ikan dalam ent"k mindmap

38



1&$ Knowledge !ran#ormation

39

D i D t



Darimana Datangn,aPengetah"an=

Data

40

M i M d k i



Man"#ia Memprod"k#iData

Man"#ia memprod"k#ieragam data ,ang <"mlahdan "k"rann,a #angat e#ar

• #tronomi• %i#ni#

• Kedokteran

• 'konomi

• lahraga• 6"aa

• 5inanial

• >

41



Pert"m"han Data

Astronomi• Sloan Digital Sk, S"r+e,

• New Meio 000

• 1.0!% o+er 10 ,ear#

• 4arge S,nopti S"r+e, !ele#ope• 6hile 01

• Will aC"ire 1.0!% e+er, ?+e da,#

!iologi dan ,edo%teran• '"ropean %ioinormati# 2n#tit"te ('%2)

• 0P% o data (genomi data do"le# in #i;e eah ,ear)

• #ingle #eC"ened h"man genome an e aro"nd 1.0I% in#i;e

kilo,te (%!) 10$

mega,te(M!)

10

giga,te(-!)

109

tera,te(T!)

101

peta,te(P!)

101

:

ea,te(!)

101

8

;etta,te(/!)

101

,otta,te( &!)

10

.

42

P h K lt d



Per"ahan K"lt"r danPerilak"

(3nsi,ht$ i, !ata4rens

or Meia$ 2015&43

kilo,te (%!) 10$



Datangn,a !#"nami Data

• Moile 'letroni# market• :% moile phone# in "#e in 010

• 1:0M talet# wa# #old in 01 (2D6)

• 00M i# gloal noteook# #hipment# in 01 (Digitime# Re#earh)

• We and Soial Network# generate# amo"nt odata

• Ioogle proe##e# 100 P% per da, $ million #er+er#

• 5aeook ha# $00 P% o "#er data per da,• Lo"t"e ha# 1000P% +ideo #torage

• $: !%# data olleted , the *S 4irar, o 6ongre##

• 1: o"t o 17 #etor# in the *S ha+e more data #tored per ompan,than the *S 4irar, o 6ongre##

kilo,te (%!) 10

mega,te(M!)

10

giga,te(-!)

109

tera,te(T!)

101

peta,te(P!)

101

:

ea,te

(!)

101

8

;etta,te(/!)

10

1

,otta,te( &!)

10

.

44



Makna dan Nilai Data

• Memiliki data e#ar artin,a3Pintar= Ka,a= %i<ak= Kek"a#aan=

!2DK

• Data adalah entita# ,ang tidak memiliki artime#kip"n kem"ngkinan memiliki nilai

• Data i# the new oil& Data i# <"#t like r"de& 2tA#+al"ale "t i "nre?ned it annot reall, e "#ed (-ie"m7)&

• We are drowning in data "t #tar+ing or knowledge(ohn ais7ett$ Me,atrens$ 1988&

45

Data 2norma#i



Data / 2norma#i Pengetah"an

46

Data 2norma#i




• !idak memawa arti mer"pakank"mp"lan dari akta/akta tentang#"at" ke<adian

• S"at" atatan ter#tr"kt"r dari #"at"tran#ak#i

• Mer"pakan materi penting dalam

mement"k inorma#i

• 2norma#i adalah kompila#i dari data47

Data 2norma#i




Data Kehadiran Pegawai

N2P !I4 D!NI P*4NI

110$ 0O1O00. 0730 1:3.0

11. 0O1O00. 073.: 1:3$$

11: 0O1O00. 073:1 1300

117$ 0O1O00. 08300 1:31:

1180 0O1O00. 07301 13$1118$ 0O1O00. 073.9 17300

48

Data 2norma#i




2norma#i k"m"la#i %"lanan Kehadiran

Pegawai

N2P Ma#"k lpa 6"ti Sakit !elat

110$

11. 18 11: 10 1 11

117$ 1 : :

1180 10 1

49

Data 2norma#i




2norma#i Kondi#i Kehadiran Mingg"an

Pegawai

Senin

Selasa

0abu ,amis

(umat

Terlambat

1 5

Pulangeat

1 1 1

Iin 3 1 4

Ala 1 2 2

50




• Ia"ngan dari #"at" pengalaman nilaiinorma#i kontek#t"al dan <"ga pandanganpakar ,ang memerikan #"at" ramework"nt"k menge+al"a#i dan meniptakan

pengalaman ar" dan inorma#i(4homas . !aenport$ a"ren#e r"sak )

• %i#a er"pa #ol"#i pemeahan #"at"ma#alah pet"n<"k #"at" peker<aan dan inii#a ditingkatkan nilain,a dipela<ari dan <"ga

i#a dia<arkan kepada ,ang lain

51

Data 2norma#i



Data / 2norma#i Pengetah"an• Pengetah"antentang keia#aanpegawai dalam <am

datangOp"lang ker<a

• Pengetah"antentang agaimanameningkatkan

kehadiran pegawai52

Data 2norma#i



Data / 2norma#i Pengetah"an / Kei<akan

• Kei<akan penataan <am ker<akar,awan kh"#"# "nt"k hari#enin dan <"mat

• Perat"ran <am ker<a3• Fari Senin dim"lai <am 10300

• Fari -"mat diakhiri <am 1.300

• Si#a <am ker<a dikompen#a#i kehari lain

53

Knowledge 6reating



Knowledge/6reating6ompan,=

• Pengetah"an adalah #at"/#at"n,ak"ni ke"ngg"lan kompetiti

• Per"#ahaan ,ang #"k#e# mamp"

"nt"k3• Seara kon#i#ten mengha#ilkan

pengetah"an ar"

• Men,earkann,a ke dalam per"#ahaan

• Mengimplementa#ikan dalam teknologiata" prod"k ar"(3k";iro onaka$ 1995&

54

S"e## Stor,3 Mat#"#hita 'letri



S"e## Stor,3 Mat#"#hita 'letri(198:)

• Mengemangkan me#in pem"at roti• Fa#il *<ioa3 k"lit l"ar roti go#ong dalamn,a

ma#ih mentah +ol"me dan #"h" ,ang tidaktepat d#

• Pengemang #otware (2k"ko !anaka)akhirn,a memp"n,ai ide magang kepem"at roti ternama di #aka

2nternational Fotel• Pengetah"an ,ang didapat dit"li# dalam

ent"k tahapan dan al"r ker<a pro#e#pem"atan roti

• Diimplementa#ikan ke me#in pem"at roti55



Knowledge Spiral

56

Tacit

Tacit Tacit

Explicit

Explicit

ExplicitExplicit

Tacit

Field

Building

Linking Explicit

Knowledge

Dialogue

Learning by Doing

Socialization Externalization

CombinationInternalization



'+ol"tion o Siene#• %eore 1003 'mpirial #iene

• 100/19:0#3 !heoretial #iene

• 'ah di#ipline ha# grown a theoreti#a omponent

• !heoretial model# moti+ate eperiment# and generali;e "nder#tanding

• 19:0#/1990#3 6omp"tational #iene

• Mo#t di#ipline# ha+e grown a third #omp"tationa ranh (e&g&empirial theoretial and omp"tational eolog, or ph,#i# or

ling"i#ti#&)

• 6omp"tational Siene traditionall, meant #im"lation& 2t grew o"t o o"r

inailit, to ?nd lo#ed/orm #ol"tion# or omple mathematial model#

•1990/now3 Data #iene• !he ailit, to eonomiall, #tore and manage peta,te# o data online

• !he 2nternet make# all the#e arhi+e# "ni+er#all, ae##ile

• Data mining i# a ma<or new hallenge

im <ra) an Ae= Saa)$ 4he Wor Wie 4ees#ope:

An Ar#het)pe or >nine S#ien#e$ -omm. A-M$ %5(11&: 505%$ o. 2002

57



Dari Data ke Pengetah"an

• Data har"# kita olah men<adipengetah"an #"pa,a i#a ermanaatagi man"#ia

• Dengan pengetah"anter#e"t man"#ia dapat3

• Melak"kan e#tima#i dan predik#iapa ,ang ter<adi di depan

• Melak"kan anali#i# tentanga#o#ia#i korela#i danpengelompokan antar data dan atri"t

• Memant" pengamilan kep"t"#an danpem"atan kei<akan

58

Mining dari Data ke



Mining dari Data kePengetah"an

59



Para Pei#ni# Pengetah"an

•*er / the worldA# large#t tai ompan,own# no +ehile#

• Ioogle / worldA# large#t mediaOad+erti#ingompan, reate# no ontent

• liaa / the mo#t +al"ale retailer ha#

no in+entor,• irn / the worldA# large#t

aommodation pro+ider own# no reale#tate

• Io<ek / per"#ahaan angk"tan "m"m

tanpa memiliki kendaraan• Iroeria per"#ahaan pen<"al #a,"r dan

daging di pa#ar tanpa p"n,a toko danarang dagangan

60

Predik#i 6alon 4egi#lati DK2



Predik#i 6alon 4egi#lati DK2 -akarta

61

Predik#i Kel"l"#an



Predik#i Kel"l"#anMaha#i#wa

62



4atihan

• %"at li#t data/data apa #a<a ,angada di tempat kita eker<a

• 4ak"kan anali#i# knowledge apa

,ang i#a diang"n dari data/datater#e"t

• Sa<ikan dalam ent"k MindMap

63



1&. Knowledge

Management (KM)Sol"tion# and 5o"ndation#

64

KM 5o"ndation# and



KM 5o"ndation# andSol"tion#

• Knowledge management depend# on tworoad a#pet#3

1& KM 5o"ndation# (7roaer and more on,term)

& KM Sol"tion (spe#i?# in nat"re)

• KM #ol"tion# reer to the wa,# in whih#pei? a#pet# o KM (di#o+er, apt"re#haring and appliation o knowledge) ane aompli#hed

•. 2nl"de KM proe##e# and KM #,#tem#

• KM o"ndation# are the roadorgani;ational a#pet# that #"pport KM inthe #hort/ and long/term

•. 2nl"de KM inra#tr"t"re KM mehani#m# and65

KM 5o"ndation# and




66

KM 5o"ndation# and




KM Processes

KM Mechanisms

KM Infrastructure

KM Technologies

Organization

Culture

Analogies and metaphors

Brainstorming retreats

On-the-o! training

"ace-to-face meetings

Apprenticeships

#mplo$ee rotation%earning !$ o!ser&ation

'.

IT

Infrastructure

Common

Kno(ledge

#)ternalizationCom!ination *outines+ocialization #)change ,irectionInternalization

Kno(ledge

Capture

Kno(ledge

+haring

Kno(ledge

Application

,ecision support s$stems

e!-!ased discussion groups

*epositories of !est practices

Artificial intelligence s$stems

Case-!ased reasoning

roup(aree! pages

'

Ph$sical

#n&ironment

Organization

+tructure

Kno(ledge

,isco&er$

KM +$stems

Kno(ledge

Capture+$stems

Kno(ledge

+haring+$stems

Kno(ledge

Application+$stems

Kno(ledge

,isco&er$+$stems

67

KM Proe##e# Mehani#m



KM Proe##e# Mehani#mand !ehnologie#

68

K l d S i l



Knowledge Spiral

69

Tacit

Tacit Tacit

Explicit

Explicit

ExplicitExplicit

Tacit

Field

Building

Linking Explicit

Knowledge

Dialogue

Learning by Doing

Socialization Externalization

CombinationInternalization

R i



Reeren#i

1& Peter Dr"ker !he age o #oialtran#ormation 4he Atanti# Month) 7.(:)199.

& 2k"<iro Nonaka and Firotaka !ake"hi !he

Knowledge 6reating 6ompan, >=orniersit) ress 199:

$& Kimi; Dalkir and -a, 4ieowit; KnowledgeManagement in !heor, and Pratie 4he M34

ress 011.& 2rma %eerra/5ernande; and Ra<i+ Saherwal

Knowledge Management3 S,#tem# andProe##e# M.'. Sharpe$ 3n#. 010

Documents

Romi Km 01 Introduction Sep2015