Articles

KOMPUTASI METODE SAW DAN TOPSIS MENGGUNAKAN GUI MATLAB UNTUK PEMILIHAN JENIS OBJEK WISATA TERBAIK (STUDI KASUS : PESONA WISATA JAWA TENGAH) Sari, Rima Nurlita; Santoso, Rukun; Yasin, Hasbi
Jurnal Gaussian Vol 5, No 2 (2016): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Multi-Attribute Decision Making (MADM) is a method of decision-making to establish the best alternative from a number of alternatives based on certain criteria. Some of the methods that can be used to solve MADM problems are Simple Additive Weighting (SAW) Method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). SAW works by finding the sum of the weighted performance rating for each alternative in all criteria. While TOPSIS uses the principle that the alternative selected must have the shortest distance from the positive ideal solution and the farthest from the negative ideal solution. Both of these methods were applied in making the selection of the best tourist attractions in Central Java. There are 15 tourist attractions and 7 criteria: location, infrastructure, beauty, atmosphere, tourist interest, promotion, and cost. This primary research employed a questionnaire that passed the questionnaire testing, namely its validity and reliability test. The result of this study shows that the best type of tourism according to the government is temple tour. While water sports tourism is favored by tourism observers. As for college students, the preferred tourist destination is religious tourism. This study also produced a GUI Matlab programming application that can help users in performing data processing using SAW and TOPSIS to select the best attraction in Central Java. Keywords: MADM, SAW, TOPSIS, GUI, tourism
IDENTIFIKASI BREAKPOINT DAN PEMODELAN AUTOREGRESSIVE STRUCTURAL CHANGE PADA DATA RUNTUN WAKTU (STUDI KASUS INDEKS HARGA KONSUMEN UMUM KOTA SEMARANG TAHUN 1994 – 2010) Mamuroh, Mamuroh; Sudarno, Sudarno; Yasin, Hasbi
Jurnal Gaussian Vol 3, No 1 (2014): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Perubahan Indeks Harga Konsumen (IHK) merupakan  indikator ekonomi makro yang cukup penting untuk memberikan gambaran tentang laju inflasi suatu daerah/wilayah serta pola konsumsi masyarakat. IHK Umum Kota Semarang dalam kurun waktu tahun 1994-2010  terlihat mengalami kenaikan terus menerus. Plot data menunjukkan IHK bergerak naik perlahan sebelum bulan Januari 1998 dan setelahnya IHK meningkat secara curam. Untuk mengetahui apakah dalam  kurun waktu tersebut terdapat perubahan struktur pola data dan untuk mengetahui titik-titik patah (breakpoints / titik perubahan struktur)  yang terjadi pada IHK maka perlu dilakukan uji perubahan struktur, hal ini dilakukan dengan pendekatan autoregressive structural change. Hasil penelitian menunjukkan terjadi perubahan struktur dengan titik patah pada t=47 yaitu Januari 1998 bertepatan dengan krisis moneter 1998 dan t=79 yaitu September 2000 bertepatan dengan kenaikan tarif angkutan per 1 September 2000, sehingga data memiliki 3 segmen model. Metode ini sesuai untuk mengidentifikasi titik-titik patah IHK serta dapat digunakan untuk memodelkan IHK Umum Kota Semarang tahun 1994-2010. 
PROYEKSI DATA PRODUK DOMESTIK BRUTO (PDB) DAN FOREIGN DIRECT INVESTMENT (FDI) MENGGUNAKAN VECTOR AUTOREGRESSIVE (VAR) Satria, Indra; Yasin, Hasbi; Suparti, Suparti
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Gross Domestic Product (GDP) and Foreign Direct Investment (FDI) is an economic instrument that has an attachment and often used for economic development of a country. To predict these two variables there are several methods that can be used, one of which is a method of Vector Autoregressive (VAR). VAR method has some assumptions that the data to be foreseen must have an attachment, stationary in the mean and variance and the resulting error must meet the test of independence and normal distribution. In the early stages of identification done by considering the value of AIC as a determinant of the optimal lag value, which in this case lag 4 who came out as the optimal lag. Granger causality test as an attachment test between variable and Augmented Dickey Fuller test (ADF) as a stationary test. In the parameter estimation phase used Ordinary Least Square method (OLS) to determine the values of the parameters to be used as a model. After getting the model it is necessary to do verification on condition that the residuals must comply with the independence test and multivariate normal test. With a second fulfillment verification test is carried out projections for the next 5 years with a value of R-Square 64% to GDP and 48% for the variable FDI Keywords: FDI, GDP, VAR, causality, independency, multivariate normal, R-Square
PENERAPAN METODE ORDINARY KRIGING PADA PENDUGAAN KADAR NO2 DI UDARA (STUDI KASUS: PENCEMARAN UDARA DI KOTA SEMARANG) Rozalia, Gera; Yasin, Hasbi; Ispriyanti, Dwi
Jurnal Gaussian Vol 5, No 1 (2016): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Air pollution must be addressed. Nitrogen Dioxide is one of the important factors in air pollution. To determine concentration level of the pollutant ?Badan Lingkungan Hidup Kota Semarang? already take measurements  at several  points.  However,  because of  blocked  considerable cost, is  not  much  point to do measurements. In this study, will be used Ordinary Kriging method to estimate at some points in Semarang. In  this  methode will compare the value of  the eksperimental semivariogram  with  some theoretical semivariogram models (spherical, eksponensial, and gaussian) to get the best model that will be used in the estimation. In this study, estimate the concentration of Nitrogen Dioxide in the air in a number of village in Semarang. Based on analysis we found the best model is spherical model with Nitrogen Dioxide produces estimates is the highest in Sub Gebangsari and Nitrogen Dioxide lowest in Sub Patemon. Keywords: Ordinary Kriging, Semivariogram, Nitrogen Dioxide.
ANALISIS FAKTOR-FAKTOR TINGKAT KEMISKINAN DI KABUPATEN WONOSOBO DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED REGRESSION Permana, Maulana Taufan; Yasin, Hasbi; Rusgiyono, Agus
Jurnal Gaussian Vol 2, No 1 (2013): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Poverty reduction is the main priority in development strategies in Indonesia, but during this computation is modeled as a function of the poor global regression. That is, the value of the regression coefficient applies to all geographic regions. In reality each region has different characteristics according to the geographical location, therefore Geographically Weighted Regression models are developed (GWR). GWR model is used to consider the element of geography or location as the weighting in estimating the model parameters. In the model GWR model parameter estimation is obtained by using Weighted Least Square (WLS) is to give a different weighting at each location. This study discusses the factors that affect the level of poverty in the District Wonosobo. The results of testing the suitability of the model shows that there is no spatial factors influence the level of poverty in the District Wonosobo. Based on research, there are 3 variables thought to affect the level of household poverty in Wonosobo district, percentage of the number of families that have slums, percentage number of families severely malnourished, percentage of the number of families who have agricultural land. These variables have a similar effect in each district.Keywords: Poverty, Geographically Weighted Regression, Weighted Least Square, Wonosobo
OPTIMALISASI PARAMETER TEKNIK PENGELASAN FLUX CORED ARC WELDING (FCAW) MENGGUNAKAN METODE TAGUCHI MULTIRESPON PCR-TOPSIS Kusumawardani, Meilia; Mustafid, Mustafid; Yasin, Hasbi
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Multi response optimization case has encountered in industrial. Multirespon Taguchi TOPSIS PCR method is used to determine the optimal combination of factors/level and calculate the optimum performance for each response. Purpose of Taguchi method is to reduce the variability, and theory Process Capability Ratio (PCR) shows the process situation in which the parts produced are good or defective. Then Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) to determine the optimal combination multi response case. The case study using the technique of Flux Cored Arc Welding welding (FCAW) using characteristic larger is better. Performance optimal conditions for factor Welding  current at 280 ampere and factor Electrode stickout at 21 mm. Then optimal performance conditions for each responses are hardness=481.145 and deposition rate=3.813. These results have a higher value when compared with the initial conditions. So the case results meet the characteristics of larger is better. Keywords : Taguchi Method, PCR, TOPSIS, FCAW
ANALISIS SISTEM ANTREAN PELAYANAN DI KANTOR PERTANAHAN KOTA SEMARANG Tambunan, Lenti Agustina Lianasari; Sugito, Sugito; Yasin, Hasbi
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Kantor Pertanahan Kota Semarang in charge of the land with an area of 373.70 km2 coverage, every day crowded with visitors who want to take care of the land petition. However, the high number of applicants who must be served not proportional to the number of care facilities available to the applicant should enter the waiting list queue or experiencing situation. This situation occurs in almost all counters, namely Counter 1 Land Information, Counter 2 Registration, Counter 3 Payment, and Counter 4 Product Delivery. Therefore, the required analysis is based on the model line system in accordance with the conditions of service which can then be used to address the issue queue. Based on the analysis, the model system is the best line in counter 1 land information (M/M/1): (GD/?/?). Counter 2 registration which is divided into 7 sub-counters have a model (M/M/2): (GD/?/?) to sub counters 2A, 2B, 2C, 2E/F, 2G, 2H, and the model (M/M/4): (GD/?/?) to sub counter 2D. Counter 3 payment (M/M/2): (GD/?/?). Counter 4 is the product delivery (M/M/2): (GD/?/?).Keywords :  Queuing system, Service, Arrivals
PEMILIHAN CLUSTER OPTIMUM PADA FUZZY C-MEANS (STUDI KASUS: PENGELOMPOKAN KABUPATEN/KOTA DI PROVINSI JAWA TENGAH BERDASARKAN INDIKATOR INDEKS PEMBANGUNAN MANUSIA) Purnamasari, Sarita Budiyani; Yasin, Hasbi; Wuryandari, Triastuti
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Cluster analysis is a process of separating the objects into groups, so that the objects that belong to the same group are similar to each other and different from the other objects in another group. One method of clustering is Fuzzy C-Means (FCM). FCM is used because each data in a cluster determined by a degree of membership that have value between 0 and 1. This research use two kinds of distance, Manhattan and Euclidean. To determine the proper distance in clustering district / city in Central Java based on indicators of Human Development Index (HDI), we have to calculate the ratio of the standard deviation, where the smaller value indicates a better clustering. While the optimum number of groups obtained from the minimum value of Xie Beni. Variables that used in this research are the indicators of HDI in 2012 for district / city in Central Java, consists of: Life Expectancy Value (years), Literacy Rate (percent), Average Length of School (years), and Purchasing Power Parity (thousands rupiah). The results from this research are the distance that gives a better quality is Euclidean and the optimum cluster given when the number of cluster is five with the smallest value of Xie Beni is 0,50778.
OPTIMASI VALUE AT RISK PADA REKSA DANA DENGAN METODE HISTORICAL SIMULATION DAN APLIKASINYA MENGGUNAKAN GUI MATLAB Monica, Christa; Tarno, Tarno; Yasin, Hasbi
Jurnal Gaussian Vol 5, No 2 (2016): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Value at Risk (VaR) is a method used to measure financial risk within a firm or investment portfolio over a specific time period at certain confidence interval level. Historical Simulation is used in this research to compute VaR of stock mutual fund at 5% confidence interval level, with one day time period and Rp 100.000.000,00 startup investment fund. Historical Simulation ia a non parametric method where the formula doesn?t require any asumption. Portfolio optimization is done by calculating the weight of allocation fund for each asset in the portfolio using Mean Variance Efficient Portfolio (MVEP) method. The data in this research are divided into four mutual fund asset. To make VaR become easier for people to understand, an application is made using GUI in Matlab. The smallest risk value for single investment asset is obtained by Valbury Equity I stock mutual fund and the smallest risk value for two-asset portfolio is obtained by the combination assets of Pacific Equity Fund and Valbury Equity I. Meanwhile for three-asset portfolio, the combination assets of Pacific Equity Fund, Valbury Equity I, and Millenium Equity Prima Plus have the smallest risk value. The test result of VaR with Basel Rules shows that the usage of VaR is legitimate to measure loses potency in mutual fund investment.Keywords: Value at Risk (VaR), Historical Simulation, Mutual Fund, Risk.
PREDIKSI DATA HARGA SAHAM HARIAN MENGGUNAKAN FEED FORWARD NEURAL NETWORKS (FFNN) DENGAN PELATIHAN ALGORITMA GENETIKA (STUDI KASUS PADA HARGA SAHAM HARIAN PT. XL AXIATA TBK) Sari, Ira Puspita; Wuryandari, Triastuti; Yasin, Hasbi
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Artificial neural network (ANN) or Neural Network (NN) is an information processing system that has characteristics similar to biological neural networks. One of the ANN models have network is quite simple and can be applied to time series data prediction is Feed Forward Neural Networks (FFNN). In general, FFNN trained using Backpropagation algorithm to obtain weights, but performance will decrease and trapped in a local minimum when applied to data that have great complexity like financial data. The solution to this problem is to train FFNN using Genetic Algorithm (GA). GA is a search algorithm that is based on the mechanism of natural selection and genetics to determine the global optimum. Training FFNN using GA is a good solution but the problem is how to understand the workings of FFNN training using the GA, the determination of the combination of the probability of crossover (), number of populations, number of generations, and the size of the tournament (k) on the AG to produce predictive value approaching actual value. One possible option is to use the technique of trial-end-error by experimenting for some combination of these four parameters. Of the 64 times the application of the AG test results to train FFNN models on daily stock price data PT. XL Axiata Tbk obtained results are sufficiently accurate predictions indicated by the proximity of the target to the output of the crossover probability () 0.8, a population of 50, the number of generations 20000 and tournament size of 4 produces the testing RMSE 107.4769.  
Co-Authors Abdul Hoyyi Agus Rusgiyono Ahmat Dhani Riau Bahtiyar Alan Prahutama Aldila Abid Awali Alfiyatun Rohmaniyah Alvita Rachma Devi Alvitiani, Siska Amanda Lucky Berlian Andriyani, Mega Fitria Andriyani, Mega Fitria Arief Rachman Hakim Bakar, Sakhinah Abu Basyiruddin, Adi Waridi Budi Warsito Cakra Kurniawan Catra Aditya Wisnu Aji Christa Monica, Christa Danang Chandra Pradana, Danang Chandra Dani Al Mahkya Darwanto Darwanto David Yuliandar Depy Veronica, Depy Dewi Setya Kusumawardani Di Asih I Maruddani Diah Safitri Dody Apriliawan Dwi Hasti Ratnasari Dwi Ispriyanti Eko Siswanto Erfan Sofha, Erfan Faizia, Tsania Fiqria Devi Ariyani Firda Shintia Dewi Gera Rozalia, Gera Hanien Nia H Shega Hari Susanta Nugraha Hasimah, Inas Ilham Indra Bakti Al-Irsyad, Ilham Indra Bakti Indra Satria, Indra Ira Puspita Sari Ishlahul Kamal, Ishlahul Ispriyansti, Dwi Johan Adi Wicaksana, Johan Adi Kadi Mey Ismail Khusnul Yeni Widiyanti Kurniawan, Isma Dwi Laily Nadhifah Lenti Agustina Lianasari Tambunan Lina Irawati Lutfia Septiningrum, Lutfia Mamuroh Mamuroh Mas'ad, Mas'ad Maulana Taufan Permana Meilia Kusumawardani, Meilia Meutuah, Siti Maulina Moch. Abdul Mukid Mochammad Abdul Mukid, Mochammad Abdul Mubyarjati, Dhea Kurnia Muh Najib Hilmi MUHAMMAD HARIS Muhammad Hilman Rizki Abdullah, Muhammad Hilman Rizki Muhammad Mujahid Muryanto Muryanto, Muryanto Mustafid Mustafid Novian Trianggara, Novian Novika Pratnyaningrum Nur Indah Yuli Astuti, Nur Indah Yuli Nurhayati, Ika Chandra Nurmalita Sari, Nurmalita Nursihan Nursihan, Nursihan Putri Aulia Netra, Putri Aulia Putri Aulia Wahyuningsih Ragil Saputra Rahafattri Ariya Fauzannissa, Rahafattri Ariya Rahma Kurnia Widyawati Rahma Nurfiani Pradita, Rahma Nurfiani Ramadhan, Setyoko Prismanu Restu Dewi Kusumo Astuti Rezzy Eko Caraka Riama Oktaviani Samosir, Riama Oktaviani Rifkhatussa'diyah, Ely Fitria Rifki Adi Pamungkas, Rifki Adi Rima Nurlita Sari, Rima Nurlita Risqiyanti, Via Rita Rahmawati Rizky Amanda Rose Debora Julianisa, Rose Debora Rukun Santoso Saepudin, Yunus Safitri Daruyani Sari, Ajeng Arum Sarita Budiyani Purnamasari Sudarno Sudarno Sugito Sugito Suparti Suparti Syaifudin Karyadi, Syaifudin Tahmid, Muhammad Tarno Tarno Tatik Widiharih Tiani Wahyu Utami Tika Dhiyani Mirawati Triastuti Wuryandari Vita Dwi Rachmawati Wawan Sugiarto, Wawan Wayaning Apsari Wulandari, Heni Dwi Yuciana Wilandari Yudha Subakti, Yudha Zulfa Wahyu Mardika, Zulfa Wahyu