Article Per Year (5 Year)
p-Index From 2021 - 2026
2.203
P-Index
This Author published in this journals
All Journal UNEJ e-Proceeding JURNAL PENGABDIAN KEPADA MASYARAKAT IJISTECH (International Journal Of Information System & Technology) Jurnal Saintika Unpam : Jurnal Sains dan Matematika Unpam Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika IJISTECH Jurnal Difusi Industrial Research Workshop and National Seminar Tedc STATISTIKA
Euis Sartika
Politeknik Negeri Bandung
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Veterinary Other

Published : 17 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 17 Documents
Search

 1   2 
Comparison of Fuzzy Time Series and Double Smoothing Holt Methods for Rainfall Forecasting Endang Habinuddin; Euis Sartika; Neneng Nuryati
IJISTECH (International Journal of Information System and Technology) Vol 6, No 3 (2022): October
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v6i3.243

Abstract

This research aims to compare the time series forecasting method, namely the Fuzzy Time Series method, with Double Exponential Smoothing Holt. The data used in this study is the rainfall data of the city of Bandung every month from January 2012 to December 2021. The analysis of the two methods is seen for accuracy according to the measure of error, namely MSE (Mean Square Error) and MAD (Mean Absolute Deviation). The results show that the Fuzzy Time Series method has MSE of 15558.89 and MAD of 108.97. While the Doube Smoothing Holt method has MSE of 23367.79 and MA of 115.94 So the Fuzzy Time Series method is reliable to use for forecasting rainfall in Bandung because the error values is lower than that of the Exponential Smoothing Holt.
Comparison of Fuzzy Time Series and Double Smoothing Holt Methods for Rainfall Forecasting Endang Habinuddin; Euis Sartika; Neneng Nuryati
IJISTECH (International Journal of Information System and Technology) Vol 6, No 3 (2022): October
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v6i3.243

Abstract

This research aims to compare the time series forecasting method, namely the Fuzzy Time Series method, with Double Exponential Smoothing Holt. The data used in this study is the rainfall data of the city of Bandung every month from January 2012 to December 2021. The analysis of the two methods is seen for accuracy according to the measure of error, namely MSE (Mean Square Error) and MAD (Mean Absolute Deviation). The results show that the Fuzzy Time Series method has MSE of 15558.89 and MAD of 108.97. While the Doube Smoothing Holt method has MSE of 23367.79 and MA of 115.94 So the Fuzzy Time Series method is reliable to use for forecasting rainfall in Bandung because the error values is lower than that of the Exponential Smoothing Holt.
PERAMALAN DISTRIBUSI KEDATANGAN TURIS MANCANEGARA MELALUI PINTU MASUK BANDARA SOEKARNO HATTA MENGGUNAKAN ARIMA Euis Sartika; Sri Murniati
JURNAL SAINTIKA UNPAM Vol 4, No 1 (2021)
Publisher : Program Studi Matematika FMIPA Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jsmu.v4i1.10796

Abstract

Penelitian ini bertujuan untuk melihat pola perkembangan Jumlah Wisatawan Mancanegara yang berkunjung ke Indonesia melalui pintu Bandara Soekarno-Hatta. Data yang digunakan adalah data time series univariat yakni Jumlah Wisatawan Mancanegara yang berkunjung ke Indonesia melalui pintu masuk Bandara Soekarno-Hatta periode bulanan dari tahun 2008 sd 2017. Alasan pemilihan Bandara Soekarno_Hatta sebagai pintu masuk turis Wisman adalah karena Bandara Soekarno-Hatta merupakan bandara tersibuk dengan pergerakan  penumpang tertinggi dan terhubung ke berbagai negara.  Analisis peramalan yang paling tepat digunakan untuk data time series tanpa pengaruh musiman adalah ARIMA Box-Jenkins. Hasil penelitian menunjukkan bahwa model terbaik ARIMA (p,d,q) adalah ARIMA (1,1,2). Salah satu syarat yang harus dipenuhi dalam model ARIMA adalah stasioneritas dalam varians dan stasioneritas dalam rata-rata (Mean). Jika datanya tidak stasioner dilakukan differencing beberapa kali sampai diperoleh data stasioner. Dalam penelitian ini dilakukan satu kali differencing, sehingga dapat ditentukan nilai d=1. Model ramalan sementara yang dapat dibentuk adalah ARIMA(1,1,2), ARIMA(0,1,1), ARIMA(2,1,1), dan ARIMA(1,1,0). Namun berdasarkan uji signikasi Estimasi Parameter, uji kelayakan model atau Diagnostik Checking (White Noise dan Normalitas Residual) serta nilai AIC terkecil, maka dapat disimpulkan bahwa model ARIMA(1,1,2) yang terbaik dan dapat digunakan untuk peramalan.
THE ROLE OF SCIENTIFIC CALCULATORS IN IMPROVING STATISTICS LEARNING Adila Sosianika; Euis Sartika; Fatya Alty Amalia
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 2 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i2.282

Abstract

In its development, Business Statistics has used several types of technology to facilitate the learning process for students, such as statistical software, spreadsheets, calculators, multimedia materials, and data repositories. The calculator includes computer technology with a simple version but allows students to experience an active learning process. Thus, the calculator media was chosen as the main learning media in business statistics courses, including in evaluating student abilities. Therefore, this study aims to determine the effectiveness of using calculators in Business Statistics courses. The research was conducted using a mix method, namely qualitative (questionnaire) and quantitative (experimental). The results showed that there was an increase in the average value of Simple Linear Regression for groups of students who used statistical applications on calculators compared to groups who did not use calculators. Based on the results of the questionnaire and suggestions, it was found that 87.7% of students considered it easy to understand the Business Statistics application questions, when using the statistical application on a calculator. Suggestions made by students were the availability of guidelines for using statistical calculator applications for practice, and the availability of calculators in the research laboratory that students could use for practice
Penerapan K-Means Cluster dan Evaluasi Clustering pada Pesebaran Kasus Covid-19 Euis Sartika; Sri Murniati; Agus Binarto; Endang Habinuddin
Statistika Vol. 22 No. 2 (2022): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v22i2.1229

Abstract

ABSTRAK Indonesia menduduki negara dengan kasus positif Covid-19 tinggi. Jumlah penduduk yang besar berpotensi dalam penularan virus. Diperlukan upaya untuk mengurangi penularan virus ini, salah satunya adalah mengetahui karakteristik data pasien Covid-19 untuk tiap provinsi dan mengelompokkannya berdasarkan kesamaan karakteristik dari pasien, sehingga dapat diketahui karakteristik dari masing-masing kelompok pasien. Analisis yang paling tepat dalam mengatasi permasalahan ini adalah K-Means Cluster, yang bertujuan mengelompokkan n objek berdasarkan p variabel yang memiliki kesamaan karakteristik diantara objek-objek yang diklasifikasikan ke dalam satu atau lebih cluster, sehingga objek yang berada dalam satu cluster akan mempunyai kesamaan sifat. Data penelitian adalah kasus Covid-19 untuk 34 Provinsi di Indonesia tahun 2021. Penelitian ini bertujuan menerapkan metode K-Means Cluster sehingga diketahui karakteristik cluster tiap provinsi yang terbentuk berdasarkan tingkat sebaran kasus Covid-19, dan mengetahui variable yang paling berpengaruh pada cluster yang terbentuk.Variabel dalam penelitian ini adalah pasien terkonfirmasi, pasien sembuh, pasien meninggal, jumlah penduduk, kepadatan penduduk, usia lansia, dan sarana kesehatan.. Informasi dari hasil penelitian ini diharapkan dapat memberi alternatif untuk pencegahan Covid-19 pada kelompok provinsi berdasarkan kesamaan sifat pasien yang terjangkit Covid-19 dan ciri khas dari tiap kelompok. Sehingga diharapkan dapat memutus rantai penyebaran Covid-19 di Indonesia. Hasil penelitian menunjukkan, pesebaran kasus Covid-19 di 34 provinsi Indonesia dapat dikelompokkan ke dalam tiga klaster. Provinsi dengan jumlah penduduk terbanyak, kepadatan penduduk tertinggi, jumlah penduduk lansia terbesar, dan sarana kesehatan terbanyak terdapat pada klaster 1 juga menunjukkan jumlah pasien terkonfirmasi, jumlah pasien sembuh, dan jumlah pasien meninggal tertinggi. Variable-variabel yang paling mendominasi dalam K-Means cluster ini adalah jumlah penduduk, kepadatan penduduk , jumlah penduduk lansia, dan sarana Kesehatan. Kata Kunci: Covid-19, analsis cluster, K-Means cluster ABSTRACT Indonesia is the country with the highest number of positive Covid-19 cases. A large population has the potential to transmit the virus. Efforts are needed to reduce the transmission of this virus, one of which is knowing the characteristics of the Covid-19 patient data for each province and grouping them based on the similarity of the characteristics of the patients, so that the characteristics of each group of patients can be known. The most appropriate analysis in overcoming this problem is the K-Means Cluster, which aims to group n objects based on p variables that have similar characteristics among objects classified into one or more clusters, so that objects in one cluster will have similar properties. . The research data are Covid-19 cases for 34 provinces in Indonesia in 2021. This study aims to apply the K-Means Cluster method so that the characteristics of the clusters of each province formed based on the level of distribution of Covid-19 cases are known, and determine the variables that have the most influence on the clusters formed. The variables in this study are confirmed patients, recovered patients, deceased patients, population, population density, elderly age, and health facilities. Information from the results of this study is expected to provide an alternative for Covid-19 prevention in provincial groups based on the similarity of patient characteristics. infected with Covid-19 and the characteristics of each group. So that it is expected to break the chain of the spread of Covid-19 in Indonesia. The results show that the distribution of Covid-19 cases in 34 provinces of Indonesia can be grouped into three clusters. Provinces with the highest population, highest population density, largest number of elderly population, and highest number of health facilities are in cluster 1 also showing the highest number of confirmed patients, number of recovered patients, and highest number of patients dying. The most dominating variables in this K-Means cluster are population, population density, number of elderly people, and health facilities. Keywords: Covid-19, cluster analysis, K-Means cluster
DIJKSTRA ALGORITHM IN DETERMINING THE SHORTEST ROUTE FOR DELIVERY SERVICE BY J&T EXPRESS IN BANDUNG Anie Lusiani; Siti Samsiyah Purwaningsih; Euis Sartika
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 2 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i2.337

Abstract

The determination of the shortest route can be done using various methods, one of which is the Dijkstra algorithm. This algorithm is often used in routing problems with minimum weight in computer networks, communication networks and transportation networks. There are several applications of the Djikstra algorithm, namely solving the problem of the shortest path of neutrosophy, mapping tourism potential, and developing geographic information systems in the health sector. In this research, Dijkstra algorithm will be applied to optimize the mileage of the delivery of goods packages. Data and information namely the address, weight and number of customer packages carried by a courier in one delivery trip are obtained from the drop point of PT. J&T Express in Sarijadi area of Bandung City. Meanwhile, data about mileage is obtained from the Google Maps application. All this data is used to construct an initial model graph that is a connected weighted graph, where the location of a drop point or a customer is a vertex and a road connecting two locations is an edge on the graph. The weight in this graph is the mileage from the drop point to the customers or from one customer to another. Then, the Djikstra algorithm is run on this graph where the drop point is the starting point of the route, so that the courier visits all customers and returns again to the drop point. The resulting route is a cycle in the graph which is the shortest closed route at 1890 meters.
TSP METHOD USING NEAREST NEIGHBOR ALGORITHM AT PT. J&T EXPRESS IN BANDUNG Anie Lusiani; Siti Samsiyah Purwaningsih; Euis Sartika
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 3 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i3.449

Abstract

Effectiveness and efficiency are very important for an expedition company in optimizing the delivery of goods by a courier. The Traveling salesman problem (TSP) method using the Nearest Neighbor Algorithm can optimize the delivery of goods to all consumer location points with only one visit in one trip. The purpose of this study is to find the shortest route using the TSP method based on the travel distance data from drop point PT. J&T Express Sarijadi Bandung to all consumer points and back to this drop point. This data is processed using Matlab and Excel Solver software based on the Nearest Neighbor Algorithm. The results of this study show that the TSP method produces the shortest route, which is 1,944 meters. The delivery route generated by this method provides travel distance efficiency of 50.09% from the route without the TSP method, which is 3,960 meters. Thus, it is expected that there will also be optimization of time and transportation costs in this delivery.
Co-Authors Agus Binarto Anny Suryani Endang Habinuddin Endang Habinuddin Fatya Alty Amalia Hadiani, Fatmi Irfani Azis Jayanti, Retno Dwi Karnisah, Iin Lusiani, Anie Muldiani, Ratu Fenny Neneng Nuryati Siti S Purwaningsih Siti S. Purwaningsih Siti Samsiyah Purwaningsih Sosianika, Adila Sri Murniati Sri Suratmi Sri Suratmi Yuliah, Siti