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ANALISIS PERUBAHAN SRUKTUR EKONOMI KOTA BANDUNG MELALUI MODEL INPUT OUTPUT Yanti, Teti Sofia; Sunendiari, Siti
EKSPANSI Vol 8, No 2 (2016)
Publisher : Politeknik Negeri Bandung

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Abstract: Implementation of the development done in a particular region is basically a series of implementation process of development planning. Development of Bandung as an integral part of regional and national development is basically an integrative process both at the level of planning, implementation and control on an ongoing basis in order to realize the welfare of society. For the purposes of planning and evaluation of the outcomes of development that is comprehensive both national and regional scale, a model for regional development planning approach can implement the model input output analysis. The use of Multiplier Product Matrix (MPM) to the Table Input Output in 2003 and 2008 illustrate economic structure of the city of Bandung has experienced a change. In 2008, the trade sector has grown very conspicuous compared with other sectors. Trade and road transport sector has increased significantly. Thus the development priorities and investment Bandung should be directed at trade and road transport sector, since both sectors can be a driving force and a strong appeal for the growth of other sectors. Keywords: Power Distribution, Degree of Sensitivity, Multiplier Product Matrix, Input-output Analysis

ANALISIS PERUBAHAN SRUKTUR EKONOMI KOTA BANDUNG MELALUI MODEL INPUT OUTPUT Teti Sofia Yanti; Siti Sunendiari
Ekspansi: Jurnal Ekonomi, Keuangan, Perbankan, dan Akuntansi Vol 8 No 2 (2016)
Publisher : Jurusan Akuntansi Politeknik Negeri Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35313/ekspansi.v8i2.113

Abstract: Implementation of the development done in a particular region is basically a series of implementation process of development planning. Development of Bandung as an integral part of regional and national development is basically an integrative process both at the level of planning, implementation and control on an ongoing basis in order to realize the welfare of society. For the purposes of planning and evaluation of the outcomes of development that is comprehensive both national and regional scale, a model for regional development planning approach can implement the model input output analysis. The use of Multiplier Product Matrix (MPM) to the Table Input Output in 2003 and 2008 illustrate economic structure of the city of Bandung has experienced a change. In 2008, the trade sector has grown very conspicuous compared with other sectors. Trade and road transport sector has increased significantly. Thus the development priorities and investment Bandung should be directed at trade and road transport sector, since both sectors can be a driving force and a strong appeal for the growth of other sectors. Keywords: Power Distribution, Degree of Sensitivity, Multiplier Product Matrix, Input-output Analysis

Penerapan dan Perbandingan Tiga Metode Analisis Pohon Keputusan pada Klasifikasi Penderita Kanker Payudara Jody Alwin irawadi; Siti Sunendiari
Jurnal Riset Statistika Volume 1, No. 1, Juli 2021, Jurnal Riset Statistika (JRS)
Publisher : UPT Publikasi Ilmiah Unisba

Abstract. Today there is a considerable amount of work dealing with decision trees, especially in survival analysis (Ibrahim et al, 2008). Cases classified as survival analysis, like cancer patients. This study discusses the application of data mining which is to obtain diagnostic results. The classification technique uses information obtained from medical records of breast cancer patients in Yugoslavia. A method for answering these problems through decision tree analysis using the CHAID, Exhaustive CHAID and CART methods. Empirically aiming to compare performance of three decision tree classification methods so that the best method is obtained. It was concluded that best method used in applying to the classification of breast cancer sufferers was the CART method because it was able to get the most significant variables at most four, namely inv-node, tumor size, deg-malig and breast parts. Then it has a total accuracy rate with highest value of 84.9 percent and has a total error rate with lowest value of 15.1 percent. Abstrak. Dewasa ini ada cukup banyak pekerjaan yang berurusan dengan pohon keputusan, terutama dalam analisis survival (Ibrahim dkk, 2008). Kasus yang tergolong analisis survival seperti penderita penyakit kanker. Penelitian ini membahas mengenai penerapan data mining yang digunakan untuk mendapatkan hasil diagnostik. Pendekatan teknik klasifikasi dengan menggunakan informasi yang diperoleh pada rekam medis data penderita kanker payudara di Yugoslavia. Salah satu metode untuk menjawab permasalahan tersebut melalui analisis pohon keputusan dengan metode CHAID, Exhaustive CHAID dan CART. Secara empiris bertujuan untuk membandingkan kinerja tiga metode pengklasifikasi pohon keputusan agar didapatkan metode manakah yang terbaik. Maka disimpulkan bahwa metode terbaik yang digunakan dalam penerapan pada klasifikasi penderita kanker payudara adalah metode CART sebab mampu mendapatkan variabel signifikan yang paling banyak ada empat, yakni inv-node, ukuran tumor, deg-malig dan bagian payudara. Kemudian memiliki tingkat akurasi total dengan nilai tertinggi sebesar 84.9 persen dan memiliki total tingkat kesalahan dengan nilai yang terendah sebesar 15.1 persen.

Peramalan Jumlah Penumpang Kereta Api Menggunakan Metode Arima dan Grey System Theory Ria Susilawati; Siti Sunendiari
Jurnal Riset Statistika Volume 2, No. 1, Juli 2022, Jurnal Riset Statistika (JRS)
Publisher : UPT Publikasi Ilmiah Unisba

Abstract. Quantitative forecasting methods are divided into three types, its time series methods, causal methods, and combination methods of time series and causal methods (Makridakis, 1999). The time series method is a method that predicts the future based on the past value of a variable or past errors. One of the time series methods that is being developed and commonly used is the ARIMA method. Although the calculation process is quite complex, the ARIMA method will give better results than other forecasting methods, because this method does not ignore time series rules such as stationary testing, parameter estimation, and diagnostic testing. Unlike the ARIMA method, Grey System Theory does not require all historical data, but only requires a minimum of four historical data and in the same interval. In this study, we will discuss the Forecasting of the Number of Railway Passengers in the Java Region (Jabodetabek and Non Jabodetabek) using the ARIMA Method and Grey System Theory. From the modeling that has been done, it is found that the GM model (1,1) is the most suitable model to be used to predict the number of train passengers in the Java region. Abstrak. Metode peramalan kuantitatif dibagi menjadi tiga jenis, yaitu metode deret waktu, metode kausal, dan metode kombinasi metode deret waktu dan metode kausal (Makridakis, 1999). Metode deret waktu adalah sebuah metode yang memperkirakan masa depan berdasarkan nilai masa lalu dari suatu variabel atau kesalahan masa lalu. Salah satu metode deret waktu yang sedang berkembang dan umum digunakan adalah metode ARIMA. Meskipun proses perhitungannya cukup kompleks, metode ARIMA akan memberikan hasil yang lebih baik dari metode-metode peramalan lainnya, karena metode ini tidak mengabaikan kaidah-kaidah pada deret waktu seperti pengujian stasioner, penaksiran parameter, dan pemeriksaan diagnostik. Berbeda dengan metode ARIMA, Grey System Theory tidak memerlukan seluruh data historis, namun hanya membutuhkan minimal empat data historis dan dalam interval yang sama. Dalam penelitian ini akan dibahas Peramalan Jumlah Penumpang Kereta Api Wilayah Jawa (Jabodetabek dan Non Jabodetabek) menggunakan Metode ARIMA dan Grey System Theory. Dari pemodelan yang telah dilakukan diperoleh hasil bahwa model GM (1,1) menjadi model yang paling cocok digunakan untuk meramalkan jumlah penumpang kereta api wilayah Jawa.

Kasus Multiproduk dan Multivariabel Toko Kain Avtex Menggunakan Diagram Kontrol Short-Run Vega Rochwani Putri; Siti Sunendiari
Bandung Conference Series: Statistics Vol. 1 No. 1 (2021): Bandung Conference Series: Statistics
Publisher : UNISBA Press

Abstract. A method for quality control that can provide an overview of the ongoing process by taking samples for analysis using statistical techniques so that variability in the process can be reduced is called Statistica Process Control (SPC), which has the aim of quickly detecting the presence of the cause of cases of shifting a process. so that improvements can be made to the process before too many processes are not in accordance with running standards. The design and implementation of a production must be observed sequentially from the state of the mass product for this to be effective. In short production run (Short Production Run) usually do not have sufficient data sufficient to carry out SPC using classical diagrams due to different products. To find out whether the process is controlled or not, it is presented in the Short-Run Control Diagram for X and R. In making a short-run control diagram R and X for multi-products that are measured are one item. Then determine the Upper Control Limit (UCL) and Lower Control Limit (LCL). Short-Run R and X Kontrol control diagrams for multiproduct and multivariable are discussed in this thesis. The data used are pieces of cordura and shabet fabrics at the AVTEX Fabric Store. Abstrak. Metode untuk mengendalikan kualitas yang dapat memberikan gambaran tentang proses yang sedang berjalan dengan mengambil sampel untuk dianalisa dengan menggunakan tehnik statistik sehingga variabilitas dalam proses dapat dikurangi disebut Statistica Proses Control (SPC), yang memiliki tujuan untuk mendeteksi secara cepat kehadiran penyebab kasus dari pergeseran suatu proses sehingga dapat dilakukan perbaikan terhadap proses tersebut sebelum terlalu banyak proses yang tidak sesuai dengan standar berjalan. Rancang dan implementasikan suatu produksi harus diamati berurutan dari kondisi produk massal agar hal ini dapat efektif. Pada produksi jangka pendek (ShortProduction Run) biasanya tidak memiliki data yang cukup memadai untuk melaksanakan SPC dengan menggunakan diagram klasik karena produk yang berbeda. Untuk mengetahui proses terkendali atau tidak maka disajikan pada Diagram KontrolShort-Run untuk X ̅ dan R. Dalam membuat diagram kontrol short-run R dan X ̅ untuk multiproduk yang diukur adalah satu item. Kemudian ditentukan Upper Control Limit ( UCL) dan Lower Control Limit ( LCL). Diagram KontrolShort-Run R dan X ̅ untuk multiproduk dan multivariabel dibahas dalam skripsi ini. Data yang digunakan yaitu potongan kain cordura dan shabet di Toko Kain AVTEX.

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