Sutte Indicator: an approach to predict the direction of stock market movements

The purpose of this research is to apply technical analysis of Sutte Indicator in stock trading which will assist in the investment decision making process i.e. buying or selling shares. This research takes data of "A" on the Indonesia Stock Exchange(IDX or BEI) 29 November 2006 until 20 September 2016 period. To see the performance of Sutte Indicator, other technical analysis are used as a comparison, Simple Moving Average (SMA) and Moving Average Convergence/Divergence (MACD). To see a comparison of the level of reliability prediction, the stock data were compared using the mean absolute deviation (MAD), mean of square error (MSE), and mean absolute percentage error (MAPE). The result of this research is that Sutte Indicator can be used as a reference in predicting stock movements, and if it is compared to other indicator methods (SMA and MACD) via MAD, MSE, and MAPE, the Sutte Indicator has a better level of reliability

sutteForecastR: Forecasting Data using Alpha-Sutte Indicator

The alpha-Sutte indicator (alpha-Sutte) was originally from developed of Sutte indicator. Sutte indicator can using to predict the movement of stocks. As the development of science, then Sutte indicator developed to predict not only the movement of stocks but also can forecast data on financial, insurance, and others time series data. https://cran.r-project.org/web/packages/sutteForecastR/index.htm

RcmdrPlugin.sutteForecastR: 'Rcmdr' Plugin for Alpha-Sutte Indicator

The 'sutteForecastR' is a package of Alpha-Sutte indicator. To make the 'sutteForecastR' user friendly, so we develop an 'Rcmdr' plug-in based on the Alpha-Sutte indicator function. https://cran.r-project.org/web/packages/RcmdrPlugin.sutteForecastR/index.htm

α-Sutte Indicator: Suatu Pendekan Baru dalam Peramalan Data

α-Sutte Indicator (α-Sutte) merupakan pengembangan dari Sutte Indicator. Sutte Indicator dapat digunakan untuk memprediksi pergerakan saham. Sejalan dengan perkembangan ilmu pengetahuan, maka Sutte Indicator kemudian dikembangkan tidak hanya untuk memprediksi pergerakan saham tetapi juga dapat meramalkan data dalam bidang keuangan, asuransi, dan data time series lainnya. Pengembangan dari Sutte Indicator ini kemudian dikenal dengan nama α-Sutte Indicator (α-Sutte). α-Sutte dikembangkan menggunakan prinsip metode peramalan yaitu menggunakan data sebelumnya. α-Sutte diadopsi dari metode moving average. Moving Average yang digunakan adalah Simple Moving Average-2 (SMA2). SMA2 ini digunakan untuk melihat trend data. Selain itu, α-Sutte juga menggunakan 4 data sebelumnya dengan asumsi bahwa 4 data sebelumnya berpengaruh terhadap prediksi data berikutnya

SuIndiWeb: a web-based platform of sutte indicator to predicting movement of stock

Technical Indicator is an approach to analyze the movement of stock. Are this stock will decrease or increase in future? One new indicator that has been developed is Sutte Indicator. Sutte Indicator is an indicator used in Technical Analysis of Stock Market. Sutte Indicator developed by Ansari Saleh Ahmar in December 2015. Sutte Indicator helps in the decision making process for stock investors when they can make a buy or sale of stocks. Sutte Indicator has been implemented in several stocks such as Apple Inc., XL Axiata Tbk and Smartfren Telecom Tbk. To view the reliability in the prediction of Sutte Indicator then it compared with others Technical Analysis that is Simple Moving Average (SMA) and Moving Average Convergence / Divergence (MACD). From the results of this comparison, Sutte Indicator is obtained that has a level of accu-racy that is better than the SMA and MACD. To simplify the process of use of Sutte Indicator, then make a tools on Web-based platform and the named as SuIndiWeb. SuIndiWeb will be used in the process of pre-dicting stock movements

Profil Tingkat Kreativitas dan Kualitas Pengajuan Masalah Statistika Ditinjau Dari Gaya Kognitif pada Mahasiswa Pendidikan Matematika Angkatan 2014 FMIPA Universitas Negeri Makassar

Penelitian ini bertujuan untuk mengungkap profil mengenai tingkat kreativitas dan kemampuan pengajuan masalah statistika pada mahasiswa Pendidikan Matematika Angkatan 2014 Universitas Negeri Makassar ditinjau dari segi gaya kognitifnya. Penelitian ini menggunakan metode kualitatif yang bersifat eksploratif dengan pemberian scaffolding metakognitif pada saat penelitian. Hipotesis penelitian bahwa mahasiswa yang memiliki gaya kognitif field independent (FI) dalam mengajukan masalah statistika dari informasi yang disediakan sudah dapat mengajukan masalah statistika yang dapat diselesaikan dan memuat data baru dan masalah tersebut sudah termasuk masalah statistika yang berkualitas tinggi, sedangkan mahasiswa yang memiliki gaya kognitif field dependent (FD) pada umumnya masalah statistika yang diajukan masih terbatas pada masalah statistika yang dapat diselesaikan dan tidak memuat data baru dan masalah tersebut termasuk masalah statistika yang berkualitas sedang

Pengembangan Perangkat Perkuliahan Berbasis IT (Suatu Upaya Untuk Meningkatkan Kualitas Hasil Belajar Mahasiswa)

Tujuan jangka panjang dari penelitian ini adalah dikembangkannya perangkat perkuliahan yang berbasis IT yang dapat diakses oleh mahasiswa kapan saja dan dimana saja tanpa adanya batasan waktu dan lokasi sehingga dapat meningkatkan kualitas hasil belajar matematika. Tujuan utama dari penelitian ini adalah untuk mengembangan perangkat perkuliahan Berbasis IT yang berkualitas (valid, praktis, dan efektif) sebagai suatu upaya untuk meningkatkan kualitas hasil belajar matematika. Perangkat perkuliahan yang akan dikembangkan yaitu : RPP/Silabus/SAP, Lembar Kerja Mahasiswa, Buku Mahasiswa, dan Tes Hasil Belajar. Selain tujuan jangka panjang dan tujuan utama, terdapat pula tujuan pendukung dalam penelitian ini yaitu untuk memperoleh informasi yang valid mengenai beberapa aspek terkait dengan penerapan pembelajaran berbasi IT, yaitu : (1) penguasaan mahasiswa terhadap bahan ajar dan (2) aktivitas mahasiswa dalam perkuliahan. Untuk mencapai tujuan tersebut maka proses pengambangan perangkat ini akan menggunakan Model Pengembangan Plomp (1997) terdiri dari fase investigasi awal (prelimenary investigation); fase desain (design); fase realisasi/konstruksi (realization/construction); fase tes, evaluasi dan revisi (test, evaluation and revision); dan implementasi (implementation). Dan untuk menilai kualitas perangkat pembelajaran maka dilakukan uji validitas oleh validator ahli sehingga diperoleh perangkat yang valid, praktis, dan efektif

Forecasting of primary energy consumption data in the United States: A comparison between ARIMA and Holter-Winters models

This research has a purpose to compare ARIMA Model and Holt-Winters Model based on MAE, RSS, MSE, and RMS criteria in predicting Primary Energy Consumption Total data in the US. The data from this research ranges from January 1973 to December 2016. This data will be processed by using R Software. Based on the results of data analysis that has been done, it is found that the model of Holt-Winters Additive type (MSE: 258350.1) is the most appropriate model in predicting Primary Energy Consumption Total data in the US. This model is more appropriate when compared with Holt-Winters Multiplicative type (MSE: 262260,4) and ARIMA Seasonal model (MSE: 723502,2)

Forecasting of the COVID-19 Epidemic: A Scientometric Analysis

This study presented a scientometric analysis of scientific publications with discussions of forecasting and COVID-19. The data of this study were obtained from the Scopus database using the keywords: ( TITLE-ABS-KEY (forecast) AND TITLE-ABS-KEY (covid)) and the data were taken on March 26, 2021. This study was a scientometric study. The data were subsequently analyzed using the VosViewer and Bibliometrix R Package. The results showed that “COVID-19” was the keyword most frequently used by researchers, followed by “forecasting” and “human”. Authors who discussed the topic of forecasting COVID-19 come from 83 different countries/regions, with the most articles sent by authors from the USA

Sutte Indicator: A Technical Indicator in Stock Market

This study aims at development of the technical indicator in Stock Market as Sutte Indicator. Sutte Indicator in stock trading that will assist in the investment decision-making process which is to buy or sell stocks. This study took data from PT. Astra Agro Lestari Tbk. (AALI) which is listed in the Indonesia Stock Exchange (BEI) in the period of 5 April 2001 to 20 September 2016. To find out the performance of Sutte Indicator, two other technical analysis are used as a comparison, they are Simple Moving Average (SMA) and Moving Average Convergence/Divergence (MACD). The mean of square error (MSE), mean absolute deviation (MAD), and mean absolute percentage error (MAPE) are used to find out a comparison of the level of reliability in predicting the stock data. The results of this study are Sutte Indicator could be used as a reference in predicting stock movements. Sutte Indicator have a better level of reliability compared to two other indicators method SMA and MACD based on the MSE, MAD and MAPE. Keywords: Stock Market; Sutte Indicator; Technical Analysis. JEL Classifications: C58 D5