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All Journal PROSIDING SEMINAR NASIONAL Epsilon: Jurnal Matematika Murni dan Terapan Intiqad: Jurnal Agama dan Pendidikan Islam JSEH (Jurnal Sosial Ekonomi dan Humaniora) JIE (Journal of Islamic Education) Justek : Jurnal Sains Dan Teknologi Jurnal Pertanian Agros Review of Management and Entrepreneurship Square : Journal of Mathematics and Mathematics Education Jurnal Abdidas Journal of Intelligent Computing and Health Informatics (JICHI) Infotech: Jurnal Informatika & Teknologi Jurnal Info Sains : Informatika dan Sains Jurnal Pengabdian Masyarakat Intimas (Jurnal INTIMAS): Inovasi Teknologi Informasi Dan Komputer Untuk Masyarakat Jurnal Riset Rumpun Matematika dan Ilmu Pengetahuan Alam (JURRIMIPA) Prosiding University Research Colloquium Abdimas Mandalika Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial Journal of applied statistics and data mining Journal of Islamic Education
Sulistijanti, Wellie
Akademi Statistika Muhammadiyah Semarang
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Public Health Social Sciences Transportation Other

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Journal : PROSIDING SEMINAR NASIONAL

 1 
PERAMALAN PRODUKSI TEH HIJAU DENGAN PENDEKATAN AUTOREGRESSIVE INTEGRATED MOVING AVERAGE Wijaksono, Satrio; Sulistijanti, Wellie
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2017: Prosiding Seminar Nasional Pendidikan, Sains dan Teknologi
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Tea plantation is one aspect of the lucrative agricultural sector in Indonesia.The world's need for very large plantation commodities, especially tea. theproduction of tea shoots as a raw material greatly determines the continuity oftea production as a whole. Tea production usually fluctuates from time to time.To establish a management view of future tea productivity forecasting, we canuse the Autoregressive Integrated Moving Average (Time Series) AutoregressiveIntegrated Moving Average (ARIMA) analysis. With the MSE value of 0.03668the best ARIMA model obtained is ARIMA (1.0.0), with general forecastingmodel: The data used is the production data of tea sales at PT. Rumpun Sari Medini from 2011-2016. The purpose of this research is to predict the amount of teasales production at PT. Rumpun Sari Medini Year 2017. Based on the results ofthis study, it was found that the highest tea production value occurred inDecember 2017 of 226,670 quintals, while the lowest production in January2017 was 226,603 quintals.Keyword: ARIMA, Peramalan Produksi Teh, PT. Rumpun Sari Medini
PERAMALAN JUMLAH TAMU DAN PENGUNJUNG DINNER HOTEL MEGA BINTANG SWEET KABUPATEN BLORA DENGAN PENDEKATAN ARIMA Irfana Maulana Ismail; Wellie Sulistijanti
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2018: SEMINAR NASIONAL PENDIDIKAN SAINS DAN TEKNOLOGI
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Mega Bintang Sweet Hotel is one of the hotels in Blora Regency. Article is forecasting comparative analysis of number of guess room occupancy at Mega Bintang Sweet Hotel, Blora, Central Java using forecasting methods: Autoregressive Integrated Moving Average (ARIMA). Article used 60 data from January 2012 to December 2016, and the results of research using forecasting method suggest that the right model is ARIMA (0,1,1) model with the following equation : Zt = -0,6840Zt-1 – 0,4813t-2 + at + 1,0135at-1 and the smallest MSE is 7754.  Keywords : forecasting, guess room occupancy, MSE.
PENJUALAN SEPATU MEREK ‘NIKE’ DENGAN METODE AUTOREGRESSIVE INTREGATED MOVING AVERAGE (ARIMA) Rizal Ripal Rifana; Wellie Sulistijanti
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2017: Prosiding Seminar Nasional Pendidikan, Sains dan Teknologi
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Sales are the prevalent income in the company and are the gross amount that is levied on the customer for goods and services, In the global trading era. Therole of Industry becomes very important, especially in maintaining fair businesscompetition. The data used is from Kavernosa Sport Shop from 2012 until 2016.ARIMA method is a model formation approach that is strong enough for timeseries analysis. In this analysis we get the best model to predict the ARIMAmodel (0,0,1) With model equation: √ (Y_t) = 32,8 + e_t + 0,4153e_ (t-1).From the equation model can be predicted that the highest number of salesoccurred in January in 2017 with a prediction of sales of as many as 45 pairs ofshoes.Keywords: Toko Kavernosa Sport Majalengka West Java, Model Shoes Brand 'Nike', ARIMA.
PERAMALAN HARGA MINYAK MENTAH STANDARWEST TEXAS INTERMEDIATEDENGAN PENDEKATAN METODEARIMA Syahril Faozi; Wellie Sulistijanti
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2017: Prosiding Seminar Nasional Pendidikan, Sains dan Teknologi
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Crude Oil is an important commodity. Because crude oil is a much needed source of energy all over the world. So that changes of oil prices will greatlyaffect the state of a country's economy. The price of crude oil in certainconditions has a significant increase and decrease. Rising crude oil prices willhave an impact on both exporting and importing countries in terms of inflation,stock prices and interest rates. Thus, statistical techniques that can be used toforecast time series data types are ARIMA (Autoregressive Integrated MovingAverage). Based on the above description of the objectives to be achieved is toforecast the price of crude oil on June 23 - July 3, 2016. From the forecastingresults with Box-Jenkins method, the best ARIMA model obtained is ARIMA (1,1,1) with forecasting model:   Keywords: ARIMA, Oil Price, Forecast
PERBANDINGAN METODE AUTOREGRESI DAN AUTOKORELASI SERTA SINGLE EXPONENTIAL SMOOTHING Aprilia Ummi Mujahidah; Wellie Sulistijanti
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2017: Prosiding Seminar Nasional Pendidikan, Sains dan Teknologi
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Saripetojo Ice factory was founded in 1923 and produce ice to meet household needs as well as the preservation of fish, of which most is Cilacap Regency sea. This research aims to predict sales of ice in an ice Factory Saripetojo Cilacap in 2017. By using the method of forecasting method Autoregresi and Autocorrelation and Single Exponential Smoothing. The data used in this study as many as 84 of data from January 2010 until December 2016. From the results of research using the method of Autoregresi and Autocorrelation within one period producing the equation Autoregresi is better than Single Exponential Smoothing method with a value of 11568614 MSE. Based on the Autoregresi equation is obtained the highest occurring forecasting in December that is of low beams and 23524 occurred in January, namely of 18770 beams.Keywords: Autoregresi and autocorrelation, MSE, Single Exponential Smoothing
ANALISIS PERAMALAN JUMLAH PERMINTAAN DARAH DI UNIT TRANFUSI DARAH (UTD) KOTA SEMARANG Hendrani Ismanto; Wellie Sulistijanti
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2018: SEMINAR NASIONAL PENDIDIKAN SAINS DAN TEKNOLOGI
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Blood is an important component that plays a role in bringing nutrients and oxygen to all organs of the body. The demand for blood supply is increasing every year as population increases are no exception in Semarang. To anticipate the amount of blood demand that is uncertain, a model is needed that can predict the amount of blood demand. The method used is the Box-Jenkins ARIMA method, the object to be studied is the demand for blood types at the Indonesian Red Cross Blood Transfusion Unit (UTD) in the city of Semarang in 2011-2016. The results obtained are blood demand data can be predicted using the ARIMA Box-Jenkins method with the ARIMA model (1,1,0). Keywords: Darah, ARIMA Box-Jenkins, Peramalan, Semarang
Peramalan Hasil Panen Mangga dengan Pendekatan Seasonal Autoregresif Integrated Moving Average Method Willy Estuhardini Ersa Muthahar; Wellie Sulistijanti
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2017: Prosiding Seminar Nasional Pendidikan, Sains dan Teknologi
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Mango is one of the agricultural products in Indramayu large enough.This arises from a number of farmers who cultivate this fruit, and the public interestis high enough to consume this fruit. The data studied from 2003 until 2015.Given the plot of data generated, the data has a seasonal pattern of eachperiod. This research is done by using SARIMA method (SeasonalAutoregressive Moving Average). From the results of forecasting methodsSARIMA models Box-Jenkins ARIMA produce (1,1,1) (1,1,0) =42) with the equation.From this research obtained by forecasting yields all kinds of mangoes in 20162017 in Indramayu district with the highest prediction results obtained inOctober-December 2017 and the lowest padabulan January-March 2016  Keywords: Forecasting, Harvest Mango, SARIMA
Co-Authors Adiyah Mahiruna Aidil, Idil Andita, Ayu Aprilia Ummi Mujahidah Arista Fitri Diana Atika Nurani Ambarwati Aulia, Lathifatul Ayu Andita Aziz, Rizal Abdul Azizah, Dzahari Alikharimah Cahyani, Desy Eki Dani Ramdani Fachri Putra Supriyandiari Fajar Ardy Nugroho Fakta Liza Firda Aulia Hendrani Ismanto Ikhtiyar, Zakaria Bani Irfana Maulana Ismail Istiawan, Deden JAYUS Jayus Jayus Khikmah, Laelatul Khoerul Soleh Lita Citra Dewi Susasimy Mahiruna, Adiyah Mardiyah, Aini Mawar Mira Zayan Monica Hellen Dwi Pramesti Muh Nasihin Muh. Nasihin Muhammad Haikal Darmawan Muhammad Sulthan Madany Mukhlidin Muslikhun, Alfin Nasihin, Moh Nasikhin, Muh Nur Hijjah Wahid Fajar Irianti Nurul huda Putri, Meia Rizqi Talitha Rahayu Dwiastuti Pujiningrum RAHMAT SETIAWAN Ratri Wulandari Revino Januar Rachmadi Rizal Abdul Aziz Rizal Ripal Rifana Rowiyani Rowiyani S Susilowat S Susilowat Salsabilla, Salwa Sangnandha, Habill Putra Santoso, Arif Gunawan Sari, Silvia Novita Setyawan, Arie Yoga Soleh, Khoerul Suprayitno, Muhammad Robeth Susasimy, Lita Citra Dewi Syahril Faozi Tarita Intan Soraya Toyib Abdullah Ulfatus Sholihah W, Taswati Nova Wijaksono, Satrio Wijayaningrum, Taswati Nova Willy Estuhardini Ersa Muthahar Windyaning Ustyannie Wulan Bhakti Pertiwi Yulianto, Safaat