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Pengaruh Intellectual Capital terhadap Kinerja Perusahaan (Studi Empiris pada Perusahaan Sektor Keuangan yang Terdaftar di BEI Periode 2011-2013)

2015· article· id· W1494502303 sur OpenAlex
Andika Yos Sudarso

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Notice bibliographique

RevueJurnal Ilmiah Universitas Bakrie · 2015
Typearticle
Langueid
DomaineBusiness, Management and Accounting
ThématiqueIntellectual Capital and Performance Analysis
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBusiness
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Penelitian ini bertujuan untuk memperoleh bukti empiris mengenai pengaruh Intellectual Capital terhadap kinerja perusahaan sektor keuangan di Bursa Efek Indonesia (BEI). Intellctual Capital dalam penelitian ini menggunakan model Pulic ( Value Added Intellectual Capital – VAIC TM ) yang mengukur tiga komponen Intellectual Capital, yaitu capital employed, human capital dan structural capital , serta Tingkat Pertumbuhan Intellctual Capital (ROGIC). Kinerja perusahaan dalam penelitian ini diukur dengan Return on Equity (ROE) dan Net Profit Margin (NPM). Sampel dipilih dengan metode purposive sampling setiap tahun selama tahun 2011 sampai dengan tahun 2013 sehingga diperoleh 153 sampel. Hipotesis pada penelitian ini diuji dengan analisis regresi linier berganda. Hasil penelitian ini menunjukkan bahwa capital employed terbukti berpengaruh positif terhadap kinerja keuangan yang diproksikan oleh ROE, namun tidak berpengaruh terhadap NPM. Human capital terbukti berpengaruh positif terhadap kinerja perusahaan, baik ROE maupun NPM. Structural capital juga terbukti berpengaruh positif terhadap kinerja perusahaan. Sedangkan, ROGIC terbukti tidak berpengaruh terhadap kinerja perusahaan. Pengungkapan Intellectual Capital yang masih rendah dan belum adanya standar terkait pengukuran dan pengungkapan Intellectual Capital di Indonesia menyebabkan masyarakat atau investor belum mampu membuat penilaian yang tepat atas ROGIC. Kata Kunci:  Intellectual Capital , Value Added Intellectual Capital (VAIC TM ), Capital Employed, Human Capital, Structural Capital , Rate of Growth of Intellctual Capital (ROGIC) . Return on Equity (ROE), Net Profit Margin (NPM). The study aims to obtain empirical evidence about the impact of Intellectual Capital on company’s performance of the financial sector in Indonesia Stock Market. Intellectual Capital in this study using Pulic Model ( Value Added Intellectual Capital – VAIC TM ) that measures three components of Intellectual Capital: capital employed, human capital and structural capital , and also Rate of Growth of Intellctual Capital (ROGIC). Company’s performance in this study is measured by Return on Equity (ROE) and Net Profit Margin (NPM) . Samples were selected by purposive sampling method using yearly data during 2011 to 2013 in order to obtain 153 samples. The hypothesis in this study were tested by multiple linear regression method. The results show that the capital employed have positive impact on company’s performance on ROE, but have no impact  on NPM. Human capital have positive impact on the company’s performance, both ROE and NPM. Structural capital also have positive impact on company’s performance. While ROGIC have no impact on company’s performance. Disclosure of Intellectual Capital is still low and there is no standard of measurement and disclosures related to Intellectual Capital in Indonesia caused the community or the investors have not been able to make a proper assessment on ROGIC Key Words: Intellectual Capital , Value Added Intellectual Capital (VAIC TM ), Capital Employed, Human Capital, Structural Capital , Rate of Growth of Intellctual Capital (ROGIC) . Return on Equity (ROE), Net Profit Margin (NPM) DAFTAR PUSTAKA Ali-Ali, N. (2003). Comprehensive Intellectual Capital Management (Step-by-Step). Canada: John Wiley and Sons, Inc. Alexandri, M.B. (2008). Manajemen Keuangan Bisnis . Bandung: Alfabeta. Ashari, P.B.S. (2005). Analisis Statistic dengan Microsoft exel dan SPSS. Jakarta: Salemba Empat. Azhar, Susanto. (2007). Sistem Informasi Akuntansi. Jakarta: T. Lingga Jaya. Barney, J.B. (1991). Firm resources and sustainable competitive advantage; Jurnal of Management , Vol 17 No 1, pp 99-120. Bollen, L., Vergauwen, P., & Schineders, S. (2005). Linking Intellectual Capital and Intellectual Property to Company Performance. Management Decision , Vol 43, No.9, pp 1161-1185. Bontis, N. (1998). Intellectual Capital : an Explaratory Study that Develops Measures and Models. Management Decision . Vol 36, No. 2, pp 63-76. Bontis, N., Willian, C.C.K., & Stanlet, R. (2000). Intellectual Capital and Business Performance in Malaysian Industries. Journal of Intellectual Capital , Vol.1, No. 1, pp 85-100. Bukh, P.N. (2005). Disclosure of Information on Intellectual Capital in Danish IPO Prospectuses. Accounting Auditing & Accountability Journal, Vol. 18 No. 6, pp 713-732. Cohen, S., & Kaimenakis, N. (2007). Intellectual Capital and Corporate Performance in Knowledge-Intensive SMEs, The Learning Organization. Vol 14, No.3, pp 241-262. Deegan, C. (2004). Financial Accounting Theory . Sydney: Mc Graw-Hill Book Company. European Commission (2000b). Towards a European Research Area, Communication from the Commission to the Council, the European Parliament, the Social Council, the Economic and Social Committee of the Regions. Mimeo: Author. El-Bannany. (2008). A study of determinants of intellectual capital performance in banks: the UK case. Journal of Intellectual Capital, Vol. 9, No. 3, pp 487-498. Fajarini, S.W., Indah., & Firmansyah, R. (2012). Pengaruh Intellectual Capital Terhadap Kinerja Keuangan Perusahaan (Studi Empiris Perusahaan LQ45). Jurnal Dinamika Akuntansi , Vol. 4, No.1, pp 1-12. Firer, S., & Williams, S.M. (2003). Intellectual capital and traditional measures of corporate performance. Journal of Intellectual Capital , Vol.4, No. 3, pp 348-360. Ghozali, I. (2006). Analisis Multivariate dengan Program SPSS . Semarang: Badan Penerbit Universitas Diponegoro. Ghozali, I. (2009). Aplikasi Analisis Multivariate Dengan Program SPSS (4th ed). Semarang: Penerbit Universitas Diponegoro. Ghozali, I., & Chariri, (2007). Teori Akuntansi . Semarang: Badan Penerbit Undip. Gitman, Lawrence, J., & Chad, J.Z. (2012). Principle of Management Finance . England: Publisher Pearson. Hong, P.T., Plowman, D. & Hancock, P. (2007). Intellectual Capital and Financial Returns of Companies. Journal of Intellectual Capital . Vol. 8, No.1, pp 76-95. Husnan, S.  (2002). Dasar-dasar Teori Portofolio dan Analisis Sekuritas (2nd ed). Yogyakarta: UPP-AMP YKPN. Husnan, S., & Pudjiastutik, E. (2002). Dasar-dasar Manajemen Keuangan. Yogyakarta: UPP-AMP YKPN. Kuryanto, B., & Safruddin, M. (2008). Pengaruh Modal Intelektual terhadap Kinerja Perusahaan. Makalah Disampaikan dalam Simposium Nasional Akuntansi XI , Pontianak: 23 - 24 Juli 2008. Universitas Tanjung Pura Pontianak. Mar, B., & Chatzkel, J. (2004). Intellectual Capital at the Crossroads: managing, measuring and reporting of IC. Journal of Intellectual Capital , Vol. 5, No. 2, pp 224-239. Margaretha, F., & Rakhman, A. (2006). Analisis Pengaruh Intellectual Capital terhadap Market Value dan Financial Performance Perusahaan dengan Metode Value Added Intellectual Capital. Jurnal Bisnis dan Akuntansi , Vol. 8, No. 2. Priyatno, D. (2012). Cara kilat belajar Analisa Data dengan SPSS 20 . Yogyakarta: ANDI. Pulic, A. (1998). Measuring the Performance of Intellectual Potential in Knowledge Economy. Paper presented at the 2nd McMaster Word Congress on Measuring and Managing Intellectual Capital by the Austrian Team for Intellectual Potential . Rehman, Wasim ul, et al . (2011). Intellectual Capital Performance and Its Impact on Corporate Performance: An Empirical Evidence from Modaraba Sector of Pakistan. Australian Journal of Business and Management Research , Vol. I, No.5, pp 8-16. Riahi, B.A. (2003). Intellectual Capital and Firm Performance of US Multinational Firms: A Study of the Resource Based and Stakeholder Views. Journal of Intellectual Capital. Vol. 4, No. 2, pp 215-226. Sawarjuwono, T., & Agustine, P.K. (2003). Intellectual Capital: Perlakuan, Pengukuran dan Pelaporan (Sebuah Library Research). Jurnal Akuntansi dan Keuangan , Vol. 5, No. 1, pp 31-51. Sekaran, U., & Bougie, R. (2010). Research Methods for Business 5 th edition: A Skill Building Approach. United Kingdom: John Wiley & Sons Ltd. Seleim, A., & Khalil, O. (2007). Pengetahuan Management and Organizationa Performance in the Egyptian Software Firms. International Journal of Pengetahuan Management , Vol. 3. No. 4, pp 37-66. Solikhah, B., Rohman, A., & Meiranto, W. (2010). Implikasi Intellectual Capital Performance, Growth dan Market Value; Studi Empiris dengan Pendekatan Simplistic Specification. Simposium Nasional Akuntansi XIII Purwokerto, pp 1-29. Subramanyam, K.R., & Wild, John J. (2009). Financial Statement Analysis (10 th ed). Singapore: McGraw-Hill Education (Asia). Stephen, A., Ross, R.W., & Westerfield, J.J. (2005). Corporate Finance (7th ed). Canada: The MCA Praw-Hill. Sveiby, K.E. (2001). A Knowledge Theory of The Firm to Guide in Strategy Formulation. Journal of Intellectual Capital , Vol.2, pp 344-358. Syamsuddin, L. (2001). Manajemen Keuangan Perusahaan. Jakarta: PT. Raja Grafindo Persada. Tan, H.P., Plowman, D., & Hancock, P. (2007). Intellectual Capital and Financial Returns of companies. Journal of Intellectual Capital , Vol.8, No.1, pp 76-95. Ulum, I., Gozhali, I., & Chariri, A. (2008). “ Intellectual Capital dan Kinerja Keuangan Perusahaan: Suatu Analisis dengan Pendekatan Partial Least Squares” . Simposium Nasional Akuntansi XI . Pontianak: 23 - 24 Juli 2008, Universitas Tanjung Pura Pontianak. Ulum, I. (2009). Intellectual Capital : Konsep dan Kajian Empiris). Yogyakarta: Graha Ilmu. Wiradinata, & Siregar. (2011). Pengaruh Modal Intelektual Terhadap Kinerja Keuangan Pada Perusahaan Sektor Keuangan Yang Terdaftar Di Bursa Efek Indonesia. Jurnal Akuntansi & Manajemen , Vol. 22, No. 2, pp 107-124. Yuniasih, N. W., Wirama, D.G.,  & Badera, I.D.N. (2010). Eksplorasi kinerja pasar perusahaan: Kajian berdasarkan modal intelektual. Simposium Nasional Akuntansi 13 , Purwokerto .

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Études des sciences et des technologies, Communication savante, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,057
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0020,002
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0020,002
Études des sciences et des technologies0,0020,001
Communication savante0,0020,005
Science ouverte0,0020,002
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0200,015

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,024
Tête enseignante GPT0,219
Écart entre enseignants0,195 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle