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All Journal Media Statistika Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang

Tatik Widiharih

Departemen Statistika, Fakultas Sains Dan Matematika, Universitas Diponegoro

Author-ID : 2977112

Decision Sciences, Operations Research & Management Other

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PEMODELAN METODE BROWN’S DOUBLE EXPONENTIAL SMOOTHING (B-DES) DAN BROWN’S WEIGHTED EXPONENTIAL MOVING AVERAGE (B-WEMA) MENGGUNAKAN OPTIMASI LEVENBERG-MARQUARDT PADA JUMLAH WISATAWAN DI JAWA TENGAH Dilla Retno Deswita; Abdul Hoyyi; Tatik Widiharih
Jurnal Gaussian Vol 9, No 3 (2020): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v9i3.27956

The tourism sector is one of the national development priority sectors because it contributes to foreign exchange earnings, the development of business areas, and the absorption of investment and labor. In 2018 the tourism sector will become the second largest foreign exchange earner after oil palm. Foreign exchange contributed by the tourism sector in 2018 was US $ 19.29 billion, an increase of 15.4%. The increase in contributions was driven by an increase in the number of foreign tourist arrivals by 12.58%, domestic tourists by 12.37%, and from investment. Therefore it is necessary to study the forecasting of the number of tourists after seeing the great potential generated from the tourism sector. The data forecast is data on the number of tourists in Central Java, both foreign and domestic data. Both data shows the tendency of an upward trend pattern. So that both data can be analyzed using B-DESmethods (Brown's Double Exponential Smoothing) and B-WEMA (Brown's Weighted Exponential Moving Average)that are optimized with LM (Levenberg-Marquardt). Both methods are able to analyze trend patterned data without assumptions making it easier in the analysis process. In addition, the two methods in previous studies were able to produce a small forecasting accuracy. The MAPE (Mean Absolute Percentage Error) value out sample is used to compare the forecasting results of the two methods. The results of the implementation of LM optimization on the data of the number of domestic tourists obtained the optimal parameter value of the B-DES method is 0.21944386 with MAPE out sample 16.26516% and B-WEMA method is 0.219441 with MAPE out sample 16.26515%. While the data on the number of foreign tourists obtained the optimal parameter value of the B-DES method was 0.26213368 with the MAPE out of the sample 23.61278% and the B-WEMA method was 0.26213367 with the MAPE out the sample 23.61278%. This means that both methods have a good level of forecasting accuracy in the data on the number of domestic tourists and an adequate level of accuracy in the data on the number of foreign tourists. Keywords : B-DES, B-WEMA, Levenberg-Marquardt, Tourists in Central Java

ANALISIS KLASTER METODE WARD DAN AVERAGE LINKAGE DENGAN VALIDASI DUNN INDEX DAN KOEFISIEN KORELASI COPHENETIC (Studi Kasus: Kecelakaan Lalu Lintas Berdasarkan Jenis Kendaraan Tiap Kabupaten/Kota di Jawa Tengah Tahun 2018) Sisca Indah Pratiwi; Tatik Widiharih; Arief Rachman Hakim
Jurnal Gaussian Vol 8, No 4 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.8.4.486-495

Based on Central Java Regional Police data, traffic accidents from 2017 to 2018 increased from 17.522 to 19.016 or 8,54 percent. To reduce the number of traffic accidents in Central Java, the initial step was carried out by grouping districts/cities that had the same accident level characteristics based on vehicle type with cluster analysis. The ward and average linkage method is a hierarchical cluster analysis method. ward method can maximize cluster homogeneity. While the average linkage method can generate clusters with small cluster variants. In this study using a measure of squared euclidean distance to measure the similarity between pairs of objects. To determine the quality of clustering results, the validation dunn index and cophenetic coefficients corelation are used. Based on the results of the clustering, the optimal number of clusters is obtained at q = 5 for the average linkage method with the results of validation dunn index = 0,08571196 and the rcoph = 0,687458. Keywords: Accidents, Cluster Analysis, Ward Method, Average linkage, Squared Euclidean Distance, Dunn Index, Cophenetic Correlation Coefficient

PENERAPAN STRUCTURAL EQUATION MODELLING (SEM) UNTUK MENGANALISIS FAKTOR – FAKTOR YANG MEMPENGARUHI KINERJA BISNIS (STUDI KASUS KAFE DI KECAMATAN TEMBALANG DAN KECAMATAN BANYUMANIK PADA JANUARI 2019) Ade Irma Pramudita; Tatik Widiharih; Rukun Santoso
Jurnal Gaussian Vol 9, No 2 (2020): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

This research is done to examine the effect of quality of service and product attractiveness toward business strategies based on service in order to improving business performance. The sample of this study were Cafe owners in Tembalang Subdistrict and Banyumanik Subdistrict, total are 116 respondents. In this Final Project, the processing of Structural Equation Modeling (SEM) is AMOS software. The results of the analysis show that service quality has a positive effect on business strategies based on service to improving business performance. The most significant factor that affecting business performance is quality of service. Quality of service is important in the performance of a café business. Cafe owners must always pay attention to the quality of café service to customers, because the quality of service is the main consideration for customers to visit cafes.

GRAFIK PENGENDALI MULTIVARIATE EXPONENTIALLY WEIGHTED MOVING COVARIANCE MATRIX (MEWMC) PADA DATA SAMPEL ZAT KANDUNGAN BATU BARA (Studi Kasus : PT Bukit Asam (Persero) Tbk. Tahun 2016) Sensiani Sensiani; Tatik Widiharih; Rita Rahmawati
Jurnal Gaussian Vol 9, No 1 (2020): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The progress of industrial business in the midst of global competition increased rapidly. A businessman should have special treatment for their products to compete of market quality. The quality of product is an important factor in choosing a product or service, particularly for the costumers. In technological development, the factors of failure in the product can be minimized by Statistical Quality Control. Besides to reducing diversity in product characteristics, statistical quality control can increase business income. The data source of this research is sekunder sample data of coal products of PT Bukit Asam (Persero) Tbk. with seven variables, the variables is Total Moisture (TM), Inherent Moisture (IM), Ash Content (ASH), Volatile Matter (VM), Fixed Carbon (FC), Total Sulfur (TS), and Calorific Value (CV). The analytical method is the controlling chart of Multivariate Exponentially Weighted Moving Covariance Matrix (MEWMC) which is one of the multivariate charts that serves to detect small shift in covariance matrix and the development of Multivariate Exponentially Weighted Moving Average (MEWMA) charts. Based on the results of the analysis, the MEWMA control chart is statistically controlled with a weighting value λ=0,2 while the MEWMC chart with λ=0,2 is not controlled statistically and detected small shift in covariance matrix . In a controlled process, the capability value of multivariate process is 0,83222 < 1 which means the process is not capable.Keywords: MEWMA control chart, MEWMC control chart, Process capability analysis.

PENGENDALIAN KUALITAS PRODUK MINO DI HOME INDUSTRY “SARANG SARI” BANYUMAS Winahyu Handayani; Tatik Widiharih; Budi Warsito
Jurnal Gaussian Vol 6, No 4 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v6i4.30386

Mino is Banyumas’s signature souvenir that is fancied by the public. High competitiveness makes mino manufacturers are prosecuted to improve the quality of their products. One of the ways to ascertain whether a product has a good quality is by looking at the number of defective products, the less the number of defective products the better the quality. The objective of the study is to minimize broken and burnt products and also size faultiness of the mino. Control Charts and R are used to view defectiveness data from mino’s diameter and mino’s weight respectively, where as Control Chart p is used to see the data of burnt and broken mino. Furthermore, the value of process capability (Cpk) used to review whether the process is considered capable or not capable. The result and analysis at “Sarang Sari” Nopia and Mino’s Home Industry Banyumas show attribute data in the form of broken and burned defects is restrained after eliminating seven observations data. Thereupon, the variable data in the form of mino’s weight data is restrained after omitting the three observations data with Cpk value is 1.1180, and for mino’s diameter data process has been restrained with Cpk value of 0.9559. Factors that are affecting mino’s defectiveness are equipment, method and measurement. Meanwhile, the profit value of this mino home industry business is Rp 9.276.110 per month. Keywords: Mino, Chart Control, Process Capability, Economic Analysis

GRAFIK PENGENDALI MIXED EXPONENTIALLY WEIGHTED MOVING AVERAGE – CUMULATIVE SUM (MEC) DALAM ANALISIS PENGAWASAN PROSES PRODUKSI (Studi Kasus : Wingko Babat Cap “Moel”) Aulia Resti; Tatik Widiharih; Rukun Santoso
Jurnal Gaussian Vol 10, No 1 (2021): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v10i1.30938

Quality control is an important role in industry for maintain quality stability. Statistical process control can quickly investigate the occurrence of unforeseen causes or process shifts using control charts. Mixed Exponentially Weighted Moving Average - Cumulative Sum (MEC) control chart is a tool used to monitor and evaluate whether the production process is in control or not. The MEC control chart method is a combination of the Exponentially Weighted Moving Average (EWMA) and Cumulative Sum (CUSUM) charts. Combining the two charts aims to increase the sensitivity of the control chart in detecting out of control. To compare the sensitivity level of the EWMA, CUSUM, and MEC methods, the Average Run Length (ARL) was used. From the comparison of ARL values, the MEC chart is the most sensitive control chart in detecting out of control compared to EWMA and CUSUM charts for small shifts. Keywords: Grafik Pengendali, Exponentially Weighted Moving Average, Cumulative Sum, Mixed EWMA-CUSUM, Average Run Lenght, EWMA, CUSUM, MEC, ARL

METODE K-HARMONIC MEANS CLUSTERING DENGAN VALIDASI SILHOUETTE COEFFICIENT (Studi Kasus : Empat Faktor Utama Penyebab Stunting 34 Provinsi di Indonesia Tahun 2018) Silvy ‘Aina Salsabila; Tatik Widiharih; Sudarno Sudarno
Jurnal Gaussian Vol 11, No 1 (2022): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v11i1.34003

The k-harmonic means method is a method of using the cluster center point value, which is to determine each cluster from its center point based on the calculation of the harmonic average. The k-harmonic means determines the existence of each data point based on the membership function and weighting function by using a distance measure. in the clustering, which aims to increase the importance of data that is far from each central point. This causes the k-harmonic means to be insensitive in initialization in determining the cluster center point and significantly improves the quality of clustering compared to k-means. In determining the level of similarity, the determination of the level of similarity uses the distance measure and the distance measure used is the Euclidean distance measure. The distance measure used in cluster analysis can affect the cluster results obtained. Thus, to determine the quality of the results of the cluster analysis, validation tests were carried out using an internal criteria approach, namely silhouette coefficient. In this study, the k-harmonic means used to classify provinces in Indonesia based on the causes of stunting in 2018. The stunting in children under five in Indonesia has exceeded the limit set by WHO. In 2016-2017 there was an increase in the prevalence of stunting by 27.5% to 29.6%. The k-harmonic means method is used so that the four main factors causing stunting in every province in Indonesia can be seen and the prevention and cure of stunting can run optimally. This method is also used because the data on the four factors that cause stunting show a significant rate of change and as a measure of central tendency in 34 provincial objects in Indonesia. Four factors that cause stunting are used, namely the percentage of households that do not have access to clean drinking water, the percentage of exclusive breastfeeding, the percentage of Low Birth Weight Babies (LBW) 2,500-grams born safely and the percentage of households that do not have proper sanitation facilities. The results obtained by the cluster which is optimal at k= 3 using the Euclidean, where the silhouette coefficient = 0,3040722675 ≈ 0,3. Based on the results of the cluster analysis, it is known that in cluster one, the main factor that stands out the most is the percentage of exclusive breastfeeding. In cluster two, the main factor that stands out the most is the percentage of Low Birth Weight Babies (LBW) 2,500-grams born safely. In cluster three, the most prominent main factors are the percentage of Low Birth Weight Babies (LBW) 2,500-grams born safely and the percentage of households that do not have proper sanitation facilities with the highest average centroid among other clusters. Keywords: Clustering, K-Harmonic Means, Euclidean distance, Silhouette Coefficient, Stunting

RANCANGAN D-OPTIMAL UNTUK MODEL EKSPONENSIAL GENERAL Tatik Widiharih; Sri Haryatmi; Gunardi Gunardi
MEDIA STATISTIKA Vol 7, No 2 (2014): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Exponential model is widely used in biology, chemistry, pharmacokinetics and microbiology. D-optimal criteria is criteria with the purpuse to minimize the variance of the estimator of parameters in the model. In this paper will discuss the D-optimal design for the generalized exponential model with homoscedastics errore assumtion. We used minimally supported design with the proportion of each design point is uniform. The optimization is used modified Newton, and the results obtained that the design points are interior points of the design region. Keywords: D-Optimal, Generalized Exponential, Minimally Supported Design, Support Point, Homoscedastics

VALUE AT RISK IN STOCK PORTFOLIO USING T-COPULA: Case Study of PT. Indofood Sukses Makmur, Tbk. and Bank Mandiri (Persero), Tbk. Qorina Rara Sartika; Tatik Widiharih; Moch Abdul Mukid
MEDIA STATISTIKA Vol 12, No 2 (2019): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Value at Risk (VaR) is a measuring tool that can calculate the amount of the worst losses that occur in the stock portfolio with a certain level of confidence and in certain period of time. In general, financial data has a high volatility value, which is caused the variance of residual model is not constant and nonnormally distributed. In this case, Copula-GARCH can be used to calculate the VaR. The Generalized Autoregressive Conditional Heterocedasticity (GARCH) model can resolve the time series models that have non-constant residual variance. This research use the t-Copula to model the dependency structure in the combined distribution of stock returns. The t-copula function is good in terms of reaching the extreme value state that often occurs in the financial data of stock returns and has heavytails. The empirical data uses the stock return data of PT. Indofood Sukses Makmur, Tbk (INDF) and Bank Mandiri (Persero) Tbk (BMRI) in the period of October 8, 2012 - October 8, 2017. In this research, Value at Risk is calculated using the period 1 day ahead at 90% confidence level that is 0.042, at 95% confidence level that is 0.025 and at 99% confidence level that is 0.017 with weight of each stock is 50%.

CREDIT SCORING MENGGUNAKAN METODE LOCAL MEANS BASED K HARMONIC NEAREST NEIGHBOR (MLMKHNN) Tatik Widiharih; Moch Abdul Mukid
MEDIA STATISTIKA Vol 11, No 2 (2018): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Credit Scoring is designed so that lenders can easily make decisions regarding whether a loan proposal from a prospective customer is worthy of approval or not. This study examines the application of the Multi Local Means Based K Harmonic Nearest Neighbor (MLMKHNN) method in the case of motorcycle credit in a financial institution. The classification capability of this method in detecting potential borrowers into the credit category is either good or bad compared to its previous method, Local Means Based K Harmonic Nearest Neighbor (LMKNN). In this case the MLMKHNN method has not shown better performance than the LMKNN method. At the same level of total accuracy, MLMKHNN requires more numbers of neighbors than the number of neighbors required by the LMKNN method. Keywords: sampling design, all possible samples, statistical efficiency, cost efficiency

Co-Authors Abdiyasti Nurul Arifa Abdul Hoyyi Ade Irma Pramudita Agus Rusgiyono Amalina Sari Dewi Anestasya Nur Azizah Arief Rachman Hakim Aulia Resti Bramesa Winanda Nugraha Budi Warsito Chalimatus Sa'diah Cylvia Evasari Margaretha Delsy Nurutsaniyah Denny Jales Manalu Dheanisa Widyanti Di Asih I Maruddani Diah Aliyatus Saidah Diah Safitri Dilla Retno Deswita Dinda Virrliana Ramadhanti Dwi Ispriyanti Eka Lestari Farisiyah Fitriani Fath Ezzati Kavabilla Fithroh Oktavi Awalullaili Genisia Pramestiloka Aulia Ghina Nabila Saputro Putri Gunardi . Hasbi Yasin Immawati Ainun Habibah Irma Dwi Tyana Isna Wulandari Iut Tri Utami Moch. Abdul Mukid Muhamad Syukron Mustafid Mustafid Nesari Nesari Nisa Afida Izati Puspita Ayu Utami Puspita Kartikasari Qorina Rara Sartika Rita Rahmawati Rizki Pradipto Widyantomo Rukun Santoso Ryan Anugrah Salma Farah Aliyah Salma Innassuraiya Sensiani Sensiani Setya Adi Rahmawan Silvy ‘Aina Salsabila Sintia Rizki Aprilianti Sisca Indah Pratiwi Sri Haryatmi Sudarno Sudarno sudarno sudarno Sugito Sugito Suparti Suparti Syavhana Yusricha Zuhri Putri Tita Aulia Edi Putri Winahyu Handayani

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