Abstract

Inequality of regional development is a global problem and faced by many countries, including Indonesia. Various attempts were made to reduce inequality in the region, one of them is by analyzing the imbalance with appropriate methods that can be used as a basis for policy making prioritization of future development. Klassen methods typically used to analyze the inequality of the region according to the indicators Gross Regional Domestic Product (GRDP). However, the division of the region inequality using Klassen deemed too rigid, given the existence of a possible relationship between the regions and in each of the groups formed by Klassen. This research aims to develop a new approach that can be used to analyze the inequality of development of the region. Aggromerative cluster hierarchical cluster technique modified with Klassen named Modified Agglomerative Hierarchical Clustering with Klassen (MHACK). The results shows that the use of algorithms MHACK, besides being able to classify the area into four main clusters, are also capable of forming the new group hierarchy for each region in each of the main cluster. Cophenet distance coefficient showed that MHACK algorithm has 0.9950 for Quadrant I, and 0.9154 for Quadrant II. In addition, the city of Magelang is indicated as an advanced and rapidly growing region with a poor value of GRDP, while Cilacap, Kudus, Boyolali, Brebes and Wonogiri indicated as a potential and growing region but has the worst value of GRDP.

References

• Williamson, J.G., 1965, “Regional Inequality and the Process of National Development: A Description of the Patterns, Source: Economic Development and Cultural Change”, Vol. 13, No. 4, Part 2 (Jul., 1965), pp. 184
• Akita, T., 2003, “Decomposing regional income inequality in China and Indonesia using two-stage nested Theil decomposition method”, The Annals of Regional Science, Vol. 37, pp. 55–77
• Kuncoro, M., and Idris, A.N., 2010, “Mengapa Terjadi Growth Without Development Di Provinsi Kalimantan Timur”, Jurnal Ekonomi Pembangunan, Volume 11, No. 2, Hal. 172 - 190, Desember
• Badrudin, R., 2012, “Pengembangan Ekonomi Lokal Kabupaten/Kota Provinsi Daerah Istimewa Yogyakarta Menggunakan Tipologi Klassen dan Location Quotient”, Jurnal JRMB, Vol. 7, No. 1, Juni
• Barika, 2012, “Analisis Ketimpangan Pembangunan Wilayah Kabupaten/Kota Di Provinsi Bengkulu Tahun 2005 – 2009”, Jurnal Ekonomi Dan Perencanaan Pembangunan, Volume :04 No. 03, Januari-Juni 2012
• Witten H, Ian dan Frank, Eibe, 2005, “Data Mining : Practical Machine Learning Tools and Techniques”, United Kingdom (UK) : ELSEVIER.
• Sembiring, R.W., Zain, J.M., and Embong, A., 2010, “Comparative Agglomerative Hierarchical Clustering Method to Cluster Implemented Course”, Journal Of Computing, Volume 2, Issue 12.
• Saad, F.H., Mohamed, O.I.E., and Al-Qutaish, R.E., 2012, “Comparison Of Hierarchical Agglomerative Algorithms For Clustering Medical Documents”, International Journal of Software Engineering and Applications (IJSEA), Vol.3, No.3.
• Krishnaiah, V.V. J.R., Sekar, D.V.C., and Rao, K.R.H., 2012, “Data Analysis of Bio-Medical Data Mining using Enhanced Hierarchical Agglomerative Clustering”, International Journal of Engineering and Innovative Technology (IJEIT), Volume 2, Issue 3.
• Murray, G.C., Lin, J., and Chowdhury, A., 2006, “Identification of User Sessions with Hierarchical Agglomerative Clustering”, Proceedings of the 2006 Annual Meeting of the American Society for Information Science and Technology, Texas.
• Patidar, G., Singh, A., and Singh, D., 2013, “An Approach for Document Clustering using Agglomerative Clustering and Hebbian-type Neural Network”, International Journal of Computer Applications, Volume 75– No.9
• Marinova-Boncheva, V., 2008, “Using The Agglomerative Method of Hierarchical Clustering As A Data Mining Tool In Capital Market”, International Journal "Information Theories & Applications" Vol.15.
• Poledníková, E., 2014, “Comparing Regions´ Ranking by MCDM methods: the Case of Visegrad Countries”. WSEAS TRANSACTIONS on BUSINESS and ECONOMICS, Volume 11, 2014, pp. 496 – 507
• Kronthaler, F., 2003, A Study of the Competitiveness of Regions based on a Cluster Analysis: The Example of East Germany. Laporan Penelitian Institute for Economic Research Halle (IWH)
• Jaba, E., Ionescu, A.M., Iatu, Corneliu and Balan, C.B. 2009. “The Evaluation Of The Regional Profile Of The Economic Development In Romania”. Analele Ştiintifice Ale Universitătii „Alexandru Ioan Cuza” Din Iaşi. Tomul LVI ŞtiinŃe Economice 2009
• Vincze, M., and Mezei, E., 2011, “The increase of rural development measures efficiency at the micro-regions level by cluster analysis: A Romanian case study”. Eastern Journal Of European Studies, Volume 2, Issue 1, June 2011
• Nosova, O., 2013. “The Innovation Development in Ukraine: Problems and Development Perspectives”. International Journal Of Innovation And Business Strategy. Vol. 02/August 2013
• Vydrová, H. V., and Novotná, Z., 2012. “Evaluation Of Disparities In Living Standards Of Regions Of The Czech Republic”. Acta Universitatis Agriculturae Et Silviculturae Mendelianae Brunensis. Volume LX 42, Number 4.