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All Journal Signifikan : Jurnal Ilmu Ekonomi Media Statistika Jurnal Sains dan Seni ITS IPTEK Journal of Proceedings Series International Journal of Advances in Intelligent Informatics Jurnal Ekonomi Pembangunan: Kajian Masalah Ekonomi dan Pembangunan Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Jurnal Aplikasi Statistika & Komputasi Statistik Inferensi Madaniya Proceeding ISETH (International Summit on Science, Technology, and Humanity) Bulletin of Applied Mathematics and Mathematics Education Aceh International Journal of Science and Technology Eduvest - Journal of Universal Studies
Dedy Dwi Prastyo
Department Of Statistics, Institut Teknologi Sepuluh Nopember
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Regression Models for Spatial Data: An Example from Gross Domestic Regional Bruto in Province Central Java Karim, Abdul; Faturohman, Akhmad; Suhartono, Suhartono; Prastyo, Dedy Dwi; Manfaat, Budi
Jurnal Ekonomi Pembangunan: Kajian Masalah Ekonomi dan Pembangunan Vol 18, No 2 (2017): JEP 2017
Publisher : Universitas Muhammdaiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jep.v18i2.4660

Abstract

The important role of a regions transportation infrastructure strongly affects the economic growth of the region and tends to affect the surrounding areas. The effect is called spillover effect. The aim of the research was to recognize the direct effect and spillover effect (indirect) of transportation infrastructure on the economic growth in Central Java. To identify the spillover effects, it is necessary to recognize the different characteristics of each region which have the implications on the various transportation infrastructures at each region in Central Java. Therefore, the spatial modeling was conducted. In this study, the spatial modeling employed was Spatial Durbin Error Model (SDEM). The SDEM is another form of Spatial Error Model (SEM). It does not allow for lag effects of endogenous variables, but it allows for spatial error and spatial lag on exogenous variables in which it simplifies the interpretations on direct effects and spillover effect. According to SDEM estimates, the transportation infrastructures at the districts/municipalities in Central Java had no significant effect on the outputs at each region where the infrastructures were located and their neighboring districts/cities
Hybrid SSA-TSR-ARIMA for water demand forecasting Suhartono Suhartono; Salafiyah Isnawati; Novi Ajeng Salehah; Dedy Dwi Prastyo; Heri Kuswanto; Muhammad Hisyam Lee
International Journal of Advances in Intelligent Informatics Vol 4, No 3 (2018): November 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v4i3.275

Abstract

Water supply management effectively becomes challenging due to the human population and their needs have been growing rapidly. The aim of this research is to propose hybrid methods based on Singular Spectrum Analysis (SSA) decomposition, Time Series Regression (TSR), and Automatic Autoregressive Integrated Moving Average (ARIMA), known as hybrid SSA-TSR-ARIMA, for water demand forecasting. Monthly water demand data frequently contain trend and seasonal patterns. In this research, two groups of different hybrid methods were developed and proposed, i.e. hybrid methods for individual SSA components and for aggregate SSA components. TSR was used for modeling aggregate trend component and Automatic ARIMA for modeling aggregate seasonal and noise components separately. Firstly, simulation study was conducted for evaluating the performance of the proposed methods. Then, the best hybrid method was applied to real data sample. The simulation showed that hybrid SSA-TSR-ARIMA for aggregate components yielded more accurate forecast than other hybrid methods. Moreover, the comparison of forecast accuracy in real data also showed that hybrid SSA-TSR-ARIMA for aggregate components could improve the forecast accuracy of ARIMA model and yielded better forecast than other hybrid methods. In general, it could be concluded that the hybrid model tends to give more accurate forecast than the individual methods. Thus, this research in line with the third result of the M3 competition that stated the accuracy of hybrid method outperformed, on average, the individual methods being combined and did very well in comparison to other methods.
Regression Models for Spatial Data: An Example from Gross Domestic Regional Bruto in Province Central Java Abdul Karim; Akhmad Faturohman; Suhartono Suhartono; Dedy Dwi Prastyo; Budi Manfaat
Jurnal Ekonomi Pembangunan: Kajian Masalah Ekonomi dan Pembangunan Vol 18, No 2 (2017): JEP 2017
Publisher : Muhammadiyah University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jep.v18i2.4660

Abstract

The important role of a region's transportation infrastructure strongly affects the economic growth of the region and tends to affect the surrounding areas. The effect is called spillover effect. The aim of the research was to recognize the direct effect and spillover effect (indirect) of transportation infrastructure on the economic growth in Central Java. To identify the spillover effects, it is necessary to recognize the different characteristics of each region which have the implications on the various transportation infrastructures at each region in Central Java. Therefore, the spatial modeling was conducted. In this study, the spatial modeling employed was Spatial Durbin Error Model (SDEM). The SDEM is another form of Spatial Error Model (SEM). It does not allow for lag effects of endogenous variables, but it allows for spatial error and spatial lag on exogenous variables in which it simplifies the interpretations on direct effects and spillover effect. According to SDEM estimates, the transportation infrastructures at the districts/municipalities in Central Java had no significant effect on the outputs at each region where the infrastructures were located and their neighboring districts/cities
Number of Foreign Tourist Arrival Forecasting Using Percentile Error Bootstrap Based on VARIMA Model Hidayatul Khusna; Muhammad Ahsan; Dedy Dwi Prastyo
IPTEK Journal of Proceedings Series No 2 (2017): The 2nd Internasional Seminar on Science and Technology (ISST) 2016
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (839.994 KB) | DOI: 10.12962/j23546026.y2017i2.3270

Abstract

Forecasting number of foreign tourist arrivals is important to improve the policies in the tourism sector. Better accuracy of forecast would help the government and investor to make operational, tactical, and strategic decisions. Data used in this research are monthly number of foreign tourist arrivals taken from Indonesia Central Bureau of Statistics. Multivariate forecasting at Soekarno-Hatta, Juanda, and Adi Sumarmo arrival gates was conducted using VARIMA ([12],1,0) (0,1,0)12 model. However, the longer step ahead to forecast, the larger variance error of corresponding models. As a result, the prediction interval become wider. This research computed the prediction interval using percentile error bootstrap based on VARIMA models that produced more precise forecast.
The Performance of Ramsey Test, White Test and Terasvirta Test in Detecting Nonlinearity Hendri Prabowo; Suhartono Suhartono; Dedy Dwi Prastyo
Inferensi Vol 3, No 1 (2020): Inferensi
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v3i1.6876

Abstract

The objective of this research is to compare Ramsey test, White test and Terasvirta test in the identification of nonlinearity. Ramsey test is a test based on the regression specification error test. While White test and Terasvirta test are based on neural network models. The difference between White test and Terasvirta test is in determining its weight, White test based on random sampling, while Terasvirta test based on Taylor expansion. Simulation studies are carried out with various scenarios in each test by generating linear models, linear models with outliers and nonlinear models. The results of the simulation study showed that Terasvirta test had better power than Ramsey test and White test in detecting nonlinearity. Terasvirta test is also more sensitive to the presence of outliers in linear models.
Analisis Likuiditas Saham Sektor Perbankan di BEI Menggunakan Analisis Intervensi dan Autoregressive Conditional Duration Luh Putu Shintya Handayani; Dedy Dwi Prastyo
Inferensi Vol 3, No 1 (2020): Inferensi
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v3i1.6881

Abstract

Tax Amnesty merupakan Undang-Undang yang menjadi isu hangat 2016  dan berakhir pada Maret 2017. Kebijakan Tax Amnesty mengharuskan pihak bank menjadi pihak penerima dana repatriasi. Terkait hal itu, berdasarkan isu ekonomi finansial 2015 hingga 2016 terdapat saham bank yang selalu diburu oleh investor karena saham yang likuid. Saham perbankan yang paling dipertimbangkan untuk diperdagangkan yaitu Bank Central Asia (BBCA), Bank Mandiri (BMRI), Bank Rakyat Indonesia (BBRI), dan Bank Negara Indonesia (BBNI) karena masuk dalam kelompok saham LQ45. Tujuan penelitian ini adalah mengetahui gambaran data volume, mengetahui efek adanya intervensi akibat Tax Amnesty, dan mendapat kesimpulan mengenai likuiditas saham sebelum dan selama Tax Amnesty dari model ACD. Model ACD merupakan model alternatif lain di luar intervensi. Analisis intervensi yang dilakukan menunjukkan bahwa terdapat efek intervensi diberlakukannya Tax Amnesty pada volume saham perusahaan BMRI dan BBNI, namun tidak pada BBCA dan BBRI. Model intervensi yang terbentuk belum memenuhi distribusi normal. Model ACD menghasilkan bahwa volume transaksi lebih likuid dilihat dari durasi yang tinggi pada periode Tax Amnesty. Durasi menunjukkan kejadian volume transaksi yang rendah, jadi bila nilai durasi tinggi maka volume transaksi rendah jarang terjadi. Hanya saja, pada saham BBRI tidak dapat dibandingkan sebelum Tax Amnesty dan setelah Tax Amnesty karena data tidak terdapat efek ACD dilihat dari parameter konstanta saja yang signifikan dalam model.
FUZZY MODELING APPROACH AND GLOBAL OPTIMIZATION FOR DUAL RESPONSE SURFACE Dedy Dwi Prastyo; Muhammad Sjahid Akbar; Bambang Widjanorko Otok
Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Vol. 9 No. 2 (2007): DECEMBER 2007
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (220.088 KB) | DOI: 10.9744/jti.9.2.102-111

Abstract

Dual Response Surface (DRS) with Lagrange multiplier is one of the most familiar classical multi response surface methods. Classical DRS optimization doesn't concern about the quality characteristic of responses. In this paper, fuzzy approach is proposed for modeling DRS and quality characteristic of response simultaneously. The proposed method represented the object's quality characteristic physically. The proposed method is applied to composite carbon drilling process and resulting nonlinear function that to be determined its optimal point. Many optimization methods fail to reach global optimum point because the non linear function is multimodal. Therefore, we used genetic algorithm for finding the global optimum point.
KINERJA ECONOMIZER PADA BOILER Muhammad Sjahid Akbar; Fredi Suryadi; Dedy Dwi Prastyo
Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Vol. 11 No. 1 (2009): JUNE 2009
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (260.399 KB) | DOI: 10.9744/jti.11.1.72-81

Abstract

This paper employed the dual response approach for case of Multivariate Robust Parameter Design (MRPD) which is developed by Del Castillo and Miro Quesada. MRPD method can be applied for any design of experiment. The optimization in this method uses minimizing variance function with restriction on mean function. In this paper, MRPD is applied to the case of optimization of heat transfer efectivity and operational cost at economizer. Those two responses are optimized by setting the level of control factors; diametre of tube hole, transversal spacing, and fin nearness. Temperature of feedwater is hold as a noise factor. Optimization is calculated by fmincon in MATLAB 7.0. The optimal condition for heat tranfer efectivity is 77.17% and operational cost is 30.58 kW. The optimal condition is attained at diametre of tube hole 1.5 inch, transversal spacing 3.5 inch, and fin density 3 fin/inch. Abstract in Bahasa Indonesia: Penelitian ini menggunakan metode pendekatan dual response terhadap kasus Multivariate Robust Parameter Design (MRPD) yang dikembangkan oleh Del Castillo dan Miro Quesada. Metode MRPD tidak mensyaratkan jenis rancangan percobaan yang dapat digunakan dalam proses optimasi, yang dilakukan dengan meminimalkan fungsi varians terhadap kendala fungsi rerata. Pada penelitian ini, metode MRPD diterapkan untuk kasus pencarian nilai optimal respon yaitu efektifitas perpindahan panas dan biaya operasi pada economizer. Optimasi kedua respon dilakukan dengan cara mengoptimalkan level faktor kontrol diameter luar tubing, transversal spacing, dan kerapatan fin. Temperatur feedwater berlaku sebagai faktor noise. Optimasi dilakukan dengan bantuan fmincon pada MATLAB 7.0 yang menghasilkan kondisi optimum untuk efektifitas perpindahan panas sebesar 77,17% dan biaya operasi sebesar 30,58 kW. Kondisi tersebut dicapai pada saat level diameter luar tubing sebesar 1,5 inci, transversal spacing sebesar 3,5 inci, dan kerapatan fin sebesar 3 fin/inci. Kata kunci: Economizer, dual response, Multivariate Robust Parameter Design
Hybrid ARIMAX-NN Model for Forecasting Inflation Santi Eksiandayani; S Suhartono; Dedy Dwi Prastyo
Proceeding ISETH (International Summit on Science, Technology, and Humanity) 2015: Proceeding ISETH (International Conference on Science, Technology, and Humanity)
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Inflation became an important component in the economy as an indicator of the increase in prices of goods and services. In addition to general inflation, there are also seven groups of inflation categorized based on expenditure. Inflation particularly in Indonesia is influenced by internal and external factors. These factors may effect inflation not only at a single point of time, but also at certain periods. Money supply is one factor strongly considered to influence inflation. Consequently, it is important to forecast inflation by involving money supply as input series. The effect of money supply on inflation was analyzed in this study. This research focused on hybrid method which is the combination between Autoregressive Integrated Moving Average with Exogenous Factor (ARIMAX) and Neural Network (NN). The resultsof hybrid method were compared to individual forecasting method, i.e. ARIMA and ARIMAX. The result indicated that hybrid ARIMAX-NN provided precise inflation prediction compared to ARIMA or ARIMAX method. Hybrid model can be an effective and efficient way to improve forecasting.
Analisis Perangkingan Perguruan Tinggi Negeri Berbadan Hukum (PTN-BH) di Indonesia Berdasarkan Indikator Publikasi Penelitian pada Lembaga Internasional Era Ardhya Pramesti; Setiawan Setiawan; Dedy Dwi Prastyo
Jurnal Sains dan Seni ITS Vol 11, No 3 (2022)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM), ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j23373520.v11i3.77007

Abstract

Pemerintah menargetkan PTN-BH untuk masuk dalam rangking 500 perguruan tinggi terbaik dunia. Salah satu hal yang menjadi pertimbangan dalam perangkingan perguruan tinggi secara internasional adalah indikator publikasi penelitian pada Scopus maupun Google Scholar. Oleh karena itu pada penelitian ini, dilakukan evaluasi terhadap kondisi eksisting publikasi penelitian terindeks Scopus dan Google Scholar seluruh PTN-BH menggunakan pemodelan faktor-faktor yang mempengaruhi jumlah sitasi dan indeks-h publikasi dengan regresi kuantil rekursif. Regresi kuantil digunakan sebagai alternatif metode untuk menangani distribusi data yang tidak seragam dan pemodelan rekursif digunakan karena adanya hubungan searah antara jumlah sitasi dan indeks-h publikasi. Dari hasil analisis regresi kuantil rekursif tersebut didapatkan kesimpulan bahwa jurnal Scopus Q1 memberikan dampak yang paling tinggi terhadap pertambahan jumlah sitasi Scopus di seluruh PTN-BH pada semua jenis kuantil dan jumlah publikasi jurnal Q1 (X2) yang sama memberikan pengaruh yang berbeda terhadap pertambahan indeks-h Scopus, yaitu 0,253 untuk kuantil 0,1, 0,382 untuk kuantil 0,5, serta 0,352 untuk kuantil 0,9.
Co-Authors A. Tuti Rumiati Abdul Karim Abdul Karim Adatul Mukarohmah Affandy*, Nur Azizah Ahsan, Muhammad Akhmad Faturohman Bambang Widjanorko Otok Bambang Widjanorko Otok Budi Manfaat budi manfaat, budi Danny Hermawan Adiwibowo Data Iranata dwi purwanto Era Ardhya Pramesti Erma Oktania Permatasari Faturohman, Akhmad Fithriasari, Kartika Forestryani, Veniola Fredi Suryadi Fredi Suryadi Hendri Prabowo Heri Kuswanto Hidayatul Khusna Husna Miratin Nuroini Ismaini Zain Luh Putu Shintya Handayani Maharsi, Rengganis Woro Maulana, Mahendra Andiek Muhammad Hisyam Lee Muhammad Sjahid Akbar Nadjadji Anwar Novi Ajeng Salehah Prandipa, Rayza Pusaka, Semerdanta Rhifda Zukhrufi Rizki Nanda Savera Roosyidah, Nila Ayu Nur S Suhartono Salafiyah Isnawati Santi Eksiandayani Santi Puteri Rahayu Saputra, Wisnowan Hendy Setiawan Setiawan Setiawan Setiawan Shofi Andari Suhartono Suhartono Suhartono Suhartono Suhartono Suhartono Supriyatna, Putu Krishnanda Veniola Forestryani Vita Ratnasari Wardoyo, Wasis Wibawati Wibawati Widhianingsih, Tintrim Dwi Ary Yusop, Zulkifli