Clustering studies, especially on the hierarchical agglomerative cluster (HAC) have proliferated over the recent years. Many studies used several HAC techniques to identify the proximity of one object of a data with another objects to find correlations between both for specific needs. Some studies in regional economics field utilizied this technique for to identify gaps of development by observing the proximity of achievements of development among regions. But there have been a few discussion related to identifying potential sectors owned in certain regions regarding using this technique. This research was conducted to develop a hybrid algorithm between HAC with Location Quotient (LQ) for potential sectors owned by a certain region. Data on sector of PDRB / GDRP in 31 regencies in Central Java province in 2012 are used to test the developed algorithms. The result showed that 279 of Sector Data of PDRB / GDRP were divided into two main group, i.e. the cluster LQ > 1 reaches as many as 125 Sector data from different regencies (as a potential sectors of a region). The remaining 154 sector data were classified into into cluster LQ <1(as a non-potential sectors of a region).
Regional development classification is one way to look at differences in levels of development outcomes. Some frequently used methods are the shift share, Gain index, the Iindex Williamson and Klassen typology. The development of science in the field of data mining, offers a new way for regional development data classification. This study discusses how the decision tree is used to classify the level of development based on indicators of regional gross domestic product (GDP). GDP Data Central Java and Banten used in this study. Before the data is entered into the decision tree forming algorithm, both the provincial GDP data are classified using Klassen typology. Three decision tree algorithms, namely J48, NBTRee and REPTree tested in this study using cross-validation evaluation, then selected one of the best performing algorithms. The results show that the J48 has a better accuracy rate which is equal to 85.18% compared to the algorithm NBTRee and REPTree. Testing the model is done to the six districts / municipalities in the province of Banten, and shows that there are two districts / cities are still at the development of the status quadrant relatively underdeveloped regions, namely Kota Tangerang and Kabupaten Tangerang. As for the Central Java Province, Kendal, Magelang, Pemalang, Rembang, Semarang and Wonosobo are an area with a quadrant of development also on the status of the region is relatively underdeveloped. Classification model that has been developed is able to classify the level of development fast and easy to enter data directly into the decision tree is formed. This study can be used as an alternative decision support for policy makers in order to determine the future direction of development. General TermsMachine intelligence, data mining and decision support systems.
Nowadays, agricultural field is experiencing problems related to climate change that result in the changing patterns in cropping season, especially for paddy and coarse grains, pulses roots and Tuber (CGPRT/Palawija) crops. The cropping patterns of rice and CGPRT crops highly depend on the availability of rainfall throughout the year. The changing and shifting of the rainy season result in the changing cropping seasons. It is important to find out the cropping patterns of paddy and CGPRT crops based on monthly rainfall pattern in every area. The Oldeman's method which is usually used in the classification of of cropping patterns of paddy and CGPRT crops is considered less able to determine the cropping patterns because it requires to see the rainfall data throughout the year. This research proposes an alternative solution to determine the cropping pattern of paddy and CGPRT crops based on the pattern of rainfall in the area using decision tree approach. There were three algorithms, namely, J48, RandomTree and REPTree, tested to determine the best algorithm used in the process of the classification of the cropping pattern in the area. The results showed that J48 algorithm has a higher classification accuracy than RandomTree and REPTree for 48%, 42.67% and 38.67%, respectively. Meanwhile, the results of data testing into the decision tree rule indicate that most of the areas in DKI Jakarta are suggested to apply the cropping pattern of 1 paddy cropping and 1 CGRPT cropping (1 PS + 1 PL). While in Banten, there are three cropping patterns that can be applied, they are; 1 paddy cropping and 1 CGPRT cropping (1 PS + 1 PL), 3 short-period paddy croppings or 2 paddy croppings and 1 CGPRT cropping (3 short-period PS or 2 PS + 1 PL) and 2 paddy croppings and 1 CGPRT cropping (2 PS + 1 PL).
The identification of regional development gaps is an effort to see how far the development conducted in every District in a Province. By seeing the gaps occurred, it is expected that the Policymakers are able to determine which region that will be prioritized for future development. Along with the regional gaps, the identification in Gross Regional Domestic Product (GRDP) sector is also an effort to identify the achievement in the development in certain fields seen from the potential GRDP owned by a District. There are two approaches that are often used to identify the regional development gaps and potential sector, Klassen Typology and Location Quotient (LQ), respectively. In fact, the results of the identification using these methods have not been able to show the proximity of the development gaps between a District to another yet in a same cluster. These methods only cluster the regions and GRDP sectors in a firm cluster based on their own parameter values. This research develops a new approach that combines the Klassen, LQ and hierarchical agglomerative clustering (HAC) into a new method named multi view hierarchical agglomerative clustering (MVHAC). The data of GRDP sectors of 23 Districts in West Java province were tested by using Klassen, LQ, HAC and MVHAC and were then compared. The results show that MVHAC is able to accommodate the ability of the three previous methods into a unity, even to clearly visualize the proximity of the development gaps between the regions and GRDP sectors owned. MVHAC clusters 23 districts into 3 main clusters, they are; Cluster 1 (Quadrant 1) consists of 5 Districts as the members, Cluster 2 (Quadrant 2) consists of 12 Districts and Cluster 3 (Quadrant 4) consists of 6 Districts.
Minyak goreng merupakan kebutuhan sehari sehari yang digunakan oleh ibu rumah tangga untuk keperluan memasak, namun masyarakat belum menyadari bahwa minyak goreng yang sudah tidak digunakan dapat dimanfaatkan menjadi produk rumah tangga, dimana jumlah minyak jelantah (minyak bekas) tanpa disadari jumlah melimpah, sehingga dengan permasalahan yang ada, maka minyak jelantah tersebut dapat berubah pemanfaatan menjadi sabun pencuci lantai berbahan dasar limbah minyak jelantah. Banyak minyak Jelantah (minyak bekas) tidak digunakan atas pemanfaatan yang ada, sehingga dapat memanfaatkan limbah minyak jelantah tersebut menjadi produk rumah tangga seperti sabun pencuci lantai. Disatu sisi, pada umumnya masyarakat belum produktif secara ekonomi,sulit menumbuhkan jiwa berwirausaha untuk menciptakan lapangan pekerjaan. Pada umumnya masyarakat masih beranggapan bahwa bekerja pada suatu perusahaan merupakan hal yang sangat luar biasa, sehingga dengan paradigma masyarakat beranggapan bekerja disuatu perusahaan, merupakan suatu hal yang luar biasa, maka banyak sekali terjadi penggangguran. Tanpa disadari dampak dari pengangguran sangat terasa, dimana banyak terjadi tindakan kriminal yang terjadi pada lingkungan, sehingga untuk mengatasi hal tersebut, dilakukan seperti pemberdayaan masyarakat untuk kemanadiran perekonomian masyarakat berbasis pelatihan, pelatihan pelatihan itu dilakukan proses mendeversifikasi minyak jelantah menjadi produk rumah tangga, seperti superpell. Sehingga dengan pelatihan pelatihan yang diberikan ke masyarakat diharapkan masyarakat dapat lebih produktif secara ekonomi meliputi segi produksi dan manajemen usaha, selain itu dapat membantu menciptakan ketentraman, dan kenyamanan dalam kehidupan masyarakat dan dapat meningkatkan keterampilan berpikir sofskill dan hardskill, metode yang akan digunakan dalam pencapaian tujuan tersebut dengan memberikan pelatihan pendidikan kewirausahaan, mendorong home industri, dan membantu dalam hal pemasaran produk . Sehingga dapat meningkatkan taraf hidup masyarakat dan dapat meciptakan lapangan pekerjaan, sehingga kehidupan masyarakat menjadi lebih baik.
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