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All Journal Jurnal Gaussian Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL PANGAN Jurnal Keluarga Berencana Abdi: Jurnal Pengabdian dan Pemberdayaan Masyarakat Al-Muqayyad Mitra Ash-Shibyan: Jurnal Pendidikan dan Konseling International Journal of Industrial Engineering and Engineering Management
Anne Mudya Yolanda
Program Studi Statistika, Jurusan Matematika, Universitas Riau
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Education Environmental Science Health Professions Industrial & Manufacturing Engineering Medicine & Pharmacology Public Health Social Sciences Other

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Journal : Al-Muqayyad

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Peramalan Data dengan Teknik Pemulusan Simple Moving Average (Studi Kasus Harga Saham Harian PT Bank BRI Syariah Tbk) Anne Mudya Yolanda; M. Ridhwan
AL-Muqayyad Vol. 3 No. 2 (2020): Al-Muqayyad
Publisher : STAI Auliaurrasyidin Tembilahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46963/jam.v3i2.195

Abstract

Time series analysis is used to model time series data and forecast data for future periods. This research was conducted to predict data with a simple smoothing technique, namely the Simple Moving Average of PT Bank BRI Syariah Tbk's stock closing price data. The closing price of shares was analyzed using three average criteria, namely 3, 5, 20, and 100 of the most recent data. Comparison of accuracy with SSE, MSE, and MAPE showed that the best in predicting daily stock closing price data was the Simple Moving Average using the latest 3 data with a prediction result for the future period of Rp. 748, -.
Analisis Komponen Utama dan Biplot untuk Mereduksi Faktor Inflasi Berdasarkan Indeks Harga Konsumen Anne Mudya Yolanda; Arisman Adnan; Rustam Efendi; Haposan Sirait; Irfansyah Irfansyah; Okta Bella Syuhada; Rahmad Ramadhan Laska; Riko Febrian
AL-Muqayyad Vol. 5 No. 2 (2022): Al-Muqayyad
Publisher : STAI Auliaurrasyidin Tembilahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46963/jam.v5i2.766

Abstract

Inflation of a region can be measured from the Consumer Price Index (CPI) by spending group. The aim is to look at the factors that influence monthly inflation based on the CPI for 2021. Principal Component Analysis is used to reduce the expenditure group variables in the CPI, followed by biplot analysis to display the visualization of the first two main components of the PCA in a two-dimensional graph. The results of the main component analysis, (1) the primary expenditure component consists of housing, water, electricity and household fuel variables; equipment, tools and household routine maintenance; transportation; information, communication and financial services; recreation, sports and culture, (2) secondary expenditure components include food, drink and tobacco variables; health; education; general, and (3) complementary expenditure components, namely clothing and footwear variables; personal equipment and other services. These three components simultaneously can represent 88.1% of the diversity of the data. Biplot analysis succeeded in describing the similarity and position of the variables with a total variance of 75%
Co-Authors Achmad Isya Alfassa Agus Kurniawati Andriani, Yulia Arisman Adnan Ayu Agustiani Azra Aulia Dwiputri Bustami Bustami Bustami Ecelly Indriani Putri Eva Eriani Fanny Septya Febrianti, Lusi Goldameir, Noor Ell Gustriza Erda Haposan Sirait Haposan Sirait Imtikhanah Anis Mahmudiati Irfansyah Irfansyah Isti Yuliani Kristiana Yunitaningtyas M. Ridhwan Nisha Thahira Noor Ell Goldameir Nurul Imani Okta Bella Syuhada Putri Sion Cahayana Rahmad Ramadhan Laska Ratna Mustika Dewi Raudatul Yusra Ridho Tri Mulya Riko Febrian Rustam Efendi Tira Mei Darnis Windy Maya Sari Zul Indra