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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Matematika UNAND Jurnal Hasi Penelitian Dan Pengkajian Ilmiah Eksakta - JPPIE Jurnal Ilmu Pendidikan Indonesia UNP Journal of Statistics and Data Science
Dwi Sulistiowati
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary

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ANALISIS RISIKO HARGA JUAL EMAS DAN INVESTASI SAHAM ANTAM MENGGUNAKAN EXPECTED SHORTFALL PADA MASA PANDEMI COVID-19 Dwi Sulistiowati; Maya Sari Syahrul; Ilham Dangu Rianjaya
Jurnal Matematika, Statistika dan Komputasi Vol. 17 No. 3 (2021): May, 2021
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v17i3.12779

Abstract

The Covid-19 pandemic caused the price of gold produced by PT Aneka Tambang (Antam) to experience a high increase following the world gold price, while stock investment decreased. Measuring risk is significant in financial analysis; this is related to investment funds, which are quite large and narrow about public funds. This study analyzes the risk data on Antam gold price and Antam stock closing price with an estimated Shortfall (ES). The method used to measure the risk of investing in stocks is ES. ES is the expectation of a conditional loss that exceeds Value at Risk (VaR). To compute ES data showing deviations from normality and Cornish-Fisher expansion. The volatility measurement model used is the autoregressive conditional heteroskedasticity (ARCH) and generalized ARCH (GARCH) model.This study found that the ES value of Antam gold price was smaller than Antam stock price.
Eksistensi Solusi Stasioner PT -Symmetry Multi Dimer Maya Sari Syahrul; Mahdhivan Syafwan; Admi Nazra; Nurweni Putri; Dwi Sulistiowati
Jurnal Matematika UNAND Vol 8, No 1 (2019)
Publisher : Jurusan Matematika FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmu.8.1.268-274.2019

Abstract

Pada artikel ini akan dikaji eksistensi solusi stasioner dari sistem PT - Symmetry Multi Dimer yang terdiri dari kumpulan-kumpulan dimer di bawah pengaruh potensial linear. Dengan menggunakan analisis perturbasi, diperoleh bahwa sistem PT - Symmetry Multi Dimer mempunyai solusi nol dan solusi tak-nol.Kata kunci: Metode Perturbasi, PT -Symmetry, Dimer, Eksistensi Solusi
Pemodelan Harga Saham Menggunakan Arma-Garch Dwi Sulistiowati; Maya Sari Syahrul; Iswan Rina
Jurnal Penelitian Dan Pengkajian Ilmiah Eksakta Vol 1 No 2 (2022): Jurnal Hasi Penelitian Dan Pengkajian Ilmiah Eksakta - JPPIE
Publisher : LPPM Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jppie.v1i2.532

Abstract

Autoregressive Conditional Heteroscedasticity (ARCH) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models were used for modeling with heteroscedasticity data. This study aims to determine the time series model on the stock price data of PT Triputra Agro Persada Tbk. (TAPG) with modeling ARMA, ARCH and GARCH. Based on the smallest Akaike Information Criterion (AIC) and Schwarz Criterion (SC), it shows that the ARMA(1,0)-GARCH(2,1) model is the best model for predicting the value of TAPG stock prices.
PENGARUHPENDEKATANKONSTRUKTIVISMETERHADAP HASIL BELAJAR SISWA KELAS VIII SMP NEGERI 11 JAYAPURAPADA POKOKBAHASAN GETARAN DAN GELOMBANGTAHUN AJARAN 2012/2013 INDAH SLAMET BUDIARTI; ALBERT LUMBU; DWI SULISTIOWATI
Jurnal Ilmu Pendidikan Indonesia Vol 1, No 2 (2013)
Publisher : Program Magister Pendidikan IPA, Program Pascasarjana Universitas Cenderawasih

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (261.565 KB) | DOI: 10.31957/jipi.v1i2.332

Abstract

This research was made to know the relation and the influence of constructive approach to the learning result of students in grade 8th SMP N 11 Jayapura for the vibration  and wave lesson of 2012/2013 academic year. This research is quantitative research. The population of this research are all of grade 8th students of SMP N 11 Jayapura. The technique of data collection that used is purposive sampling, with 32 students as the sample to know the relationship between the constructive approach with the learning result, correlation analysis has been used to prove it with the result tcount > ttable, equal 4.044 > 2.042, it means there’s any relationship between constructive approach to the learning result, while to know the influence between constructive approach to the learning result, regressive analysis has been applied with the result Fcount> Ftable , equal 16.358 > 4.17, it means there’s an influence between the constructive approach to the learning result of the students. Key word: constructive approach, the learning result.
Classification of Recipients of the Family Hope Program in West Sumatra Province Using the Random Forest Algoritma Nini Erdiani; Dwi Sulistiowati; Nonong Amalita; Zamahsary Martha
UNP Journal of Statistics and Data Science Vol. 3 No. 4 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss4/431

Abstract

According to the Central Statistics Agency (BPS), the percentage of poor people in West Sumatra Province increased by 0.02% in 2024. One of the government's efforts to overcome poverty is a social assistance program issued by the government to help people who are economically disadvantaged. The targeted distribution of social assistance is an important challenge in improving community welfare, especially for families receiving PKH benefits. This study aims to classify households receiving the Family Hope Program (PKH) in West Sumatra Province using a random forest algorithm with Synthetic Minority Oversampling Technique (SMOTE). This study uses data on PKH recipient households in West Sumatra Province in 2024, which has a significant class imbalance. Therefore, the SMOTE method was applied to balance the data. The data was divided into training and testing data with a ratio of 80%:20%, then parameter tuning was performed to optimize mtry and ntree. The model was evaluated using a confusion matrix to compare model performance. The results show that the accuracy obtained is 76%. The precision value is 72%, the recall is 84%, and the f1-score is 78%. Based on the Mean Decrease Gini value, the head of household's diploma became the main attribute in determining whether a household received PKH or not. This study concluded that the use of SMOTE in the random forest algorithm performed well in classifying PKH recipients in West Sumatra Province, where the model performed well and was quite reliable in identifying PKH recipients.
Forecasting the Consumer Price Index of Padang City in 2024 using the Autoregressive Integrated Moving Average Method Suci; Devi Yopita Sipayung; Dila Sari; Fajri Juli Rahman Nur Zendrato; Hadid Habiburrahman; Dwi Sulistiowati; Zilrahmi
UNP Journal of Statistics and Data Science Vol. 4 No. 1 (2026): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol4-iss1/437

Abstract

The Consumer Price Index (CPI), which changes, is influenced by fluctuations in the prices of goods and services in Padang City every year. This is triggered by various factors that are of primary concern to the government. This study uses the Autoregressive Integrated Moving Average (ARIMA) forecasting method to forecast CPI in 2024 by relying on monthly data on the Padang City CPI for the period 2020 to 2023 obtained from BPS. This analysis identifies the ARIMA model (0,2,1) as the best and most optimal model based on the AIC and BIC values, does not show any autocorrelation, and is normally distributed. The forecasting model used shows a smooth and stable increase in the CPI in the period from January to December 2024. This model provides a positive signal for people's purchasing power and economic stability in Padang City in 2024. The results obtained are expected to be used as a strategic tool for preparing future goods and services price planning with more precision.
Classification of Tuberculosis in Rumah Sakit Paru Sumatera Barat Using the C5.0 Algorithm Meliani Maya Sari; Zilrahmi; Dony Permana; Dwi Sulistiowati
UNP Journal of Statistics and Data Science Vol. 4 No. 1 (2026): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol4-iss1/444

Abstract

Tuberculosis (TB) remains a serious public health problem, including in West Sumatra Province, where the number of reported cases has continued to increase in recent years. Consequently, effective methods are required to support early detection and accurate classification of TB patients. This study aims to classify the tuberculosis status of patients at Rumah Sakit Paru Sumatera Barat by applying the C5.0 algorithm. The data used in this study consists of secondary data extracted from patient medical records collected from october to december 2024 with a total of 150 patient medical records. The dataset included eight predictor variables representing clinical symptoms and one target variable, namely sputum smear (BTA) examination results. The research process involved data preprocessing, after which the dataset was divided into training and testing subsets using a 70:30 ratio, a classification model was developed using the C5.0 algorithm, and its performance was evaluated using a confusion matrix. The findings indicate that the C5.0 algorithm achieved an accuracy of 91.11%, with a precision of 95.83%, sensitivity of 88.46%, and specificity of 94.74%. Night sweats were identified as the most influential variable in the construction of the decision tree. These findings indicate that the C5.0 algorithm demonstrates excellent performance and can be applied as a decision support method for classifying tuberculosis based on patients’ clinical symptoms
Co-Authors Admi Nazra Albert Lumbu Devi Yopita Sipayung Dila Sari Dony Permana Fajri Juli Rahman Nur Zendrato Hadid Habiburrahman INDAH SLAMET BUDIARTI Iswan Rina Maya Sari Syahrul Maya Sari Syahrul Meliani Maya Sari Nini Erdiani Nonong Amalita Nurweni Putri Rianjaya, Ilham Dangu suci Syafwan, Mahdhivan Zamahsary Martha Zilrahmi, Zilrahmi