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All Journal Eksakta : Berkala Ilmiah Bidang MIPA Jurnal Varian Pelita Eksakta Journal of Science and Technology Jurnal Pengabdian Pada Masyarakat

Dina Agustina

Departemen Matematika, Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Negeri Padang

Author-ID : 4143484

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Articles

University Students' Procrastination: A Mathematical Model (Case Studies: Student in Mathematics Department Universitas Negeri Padang) Rara Sandhy Winanda; Akira Mikail; Defri Ahmad; Dina Agustina; Rahmawati Rahmawati
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 23 No. 02 (2022): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Mathematical modeling of procrastination was carried out on students in the Mathematics Department at Universitas Negeri Padang. Procrastination is the tendency to delay work and can be contagious among students. Mathematical modeling of procrastination aims to show the spread of procrastination among students. The SEIR compartment model was applied in this study. From a total of 1,154 population members, 93 samples were randomly selected and were given a questionnaire to estimate the parameter values in the model. A couple of steady states appear in the model. The free disease steady state has a biological meaning since all the variables are real, while the endemic steady state is surreal in biological terms. The number of its basic reproduction number, from which the parameter values are derived from the primary data, indicates stability analysis near the free disease steady states. The result shows that procrastination is spread among students in the population, with the number of Ro is 1,009.

Comparison of Portfolio Mean-Variance Method with the Mean-Variance-Skewness-Kurtosis Method in Indonesia Stocks Dina Agustina; Devni Prima Sari; Rara Sandhy Winanda; Muhammad Rashif Hilmi; Dina Fakhriyana
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 23 No. 02 (2022): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

In this paper, we compare the optimal portfolio weight of mean-variance (MV) method with mean-variance-skewness-kurtosis (MVSK) method. MV is a method to get weight on a portfolio. This method can be developed into the method of MVSK with attention to the higher-order moment of return distribution; skewness and kurtosis. In determining the weight of portfolio is also important to consider the skewness and kurtosis of return distribution. This method of considering the aspect of skewness and kurtosis is called the MVSK method with the aim of maximizing the level of return and skewness and minimizing the risks and exceeding of kurtosis. The result indicate that the optimal portfolio return of all methods is MVSK method with minimize variance priority.

Pembuatan Pupuk Kompos Dari Limbah Kulit Kopi Di Daerah Penghasil Kopi Nagari Koto Tuo, Sumatera Barat Riga Riga; Trisna Kumala Sari; Dina Agustina; Bali Yana Fitri; Muhammad Habibul Ikhsan; Ferdi Henfi Pratama; Wandi Oktria
Jurnal Pengabdian Pada Masyarakat Vol 7 No 3 (2022): Jurnal Pengabdian Pada Masyarakat
Publisher : Universitas Mathla'ul Anwar Banten

MAKİNG COMPOST FERTİLİZER FROM COFFEE PEEL WASTE İN THE NAGARİ KOTO TUO COFFEE-PRODUCİNG AREA, WEST SUMATRA. Coffee husk waste in the Nagari Koto Tuo coffee producing area is not used optimally. It just became a pile of garbage in several places. The others were burned which can cause health problems in the future. One alternative to manage coffee husk waste is to fermentate it into compost. The community service for the bioconversion of coffee husk waste into fertilizer is carried out in three steps. The aim of this activity is to increase the knowledge and skills of the community in utilizing coffee skin waste. The practice of making compost was carried out in a composter using the EM-4 bioactivator. The achievement obtained from this community service was that participants were able to understand the bioconversion process of coffee skin waste into compost, which was proven by the percentage of knowledge and skills (greater than 80%).

Construction Of Mathematics Materials Through Lesson Study Supported By ICT-Based Learning Media In MGMP Mathematics of SMP Negeri District X Koto Solok District Dina Agustina
Pelita Eksakta Vol 6 No 1 (2023): Pelita Eksakta Vol. 6 No. 1
Publisher : Fakultas MIPA Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/pelitaeksakta/vol6-iss1/200

Based on observations and discussions with several mathematics teachers at Singkarak State Middle School, X Koto Singkarak District, Solok Regency, problems were found in learning mathematics, namely students still had difficulty understanding mathematical concepts and students were less active in the learning process. An indication of this is the low student learning outcomes. Teachers still do not utilize learning models and media that can attract students' interest in learning. Conducted training on strengthening mathematics material through ICT-based lesson study. The results showed that there was an increase in the teacher's understanding of the material, the teacher's skills in making learning media and the teacher's proficiency in using IT-based learning media.

Analisis Algoritma LSTM dan SVR untuk Memprediksi Saham Perbankan di Pasar Indonesia Agustina, Dina; Sari, Devni Prima
JOSTECH Journal of Science and Technology Vol 4, No 2: September 2024
Publisher : UIN Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/jostech.v4i2.9886

Penelitian ini membahas analisis komparatif algoritma Long Short-Term Memory (LSTM) dan Support Vector Regression (SVR) untuk memprediksi harga saham dari empat bankdi Indonesia: Bank BCA (BBCA.JK), Bank BNI (BBNI.JK), Bank BRI (BBRI.JK), dan Bank Mandiri (BMRI.JK). Studi ini dikarenakan semakin pentingnya prediksi harga saham yang akurat di pasar saham Indonesia untuk pengambilan keputusan yang lebih baik di sektor perbankan. Metodologi yang digunakan melibatkan pelatihan model LSTM dan SVR dengan menggunakan data saham historis dan mengevaluasi kinerja prediksi dengan menggunakan Root Mean Square Error (RMSE). Tujuannya adalah untuk mengetahui algoritma mana yang memiliki akurasi prediktif yang lebih baik untuk saham perbankan di pasar Indonesia. Hasilnya menunjukkan perbedaan yang mencolok dalam nilai RMSE antara model LSTM dan SVR pada bank-bank yang dipilih. LSTM menghasilkan nilai RMSE sebesar 84.2712, 103.7936, 15.5974, dan 26.8980 untuk masing-masing bank, sementara SVR menunjukkan nilai RMSE yang lebih rendah, yaitu 4.9627, 5.4234, 5.4234, dan 2.5470. Hasil penelitian menunjukkan bahwa algoritma SVR lebih baik dibandingkan LSTM dalam memprediksi harga saham perbankan, serta menunjukkan potensi penerapannya di pasar saham Indonesia untuk meningkatkan proses pengambilan keputusan investasi.

Stock Price Index Prediction Using Random Forest Algorithm for Optimal Portfolio Humairah, Putri; Agustina, Dina
Jurnal Varian Vol 8 No 1 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v8i1.4276

With a majority Muslim population in Indonesia, Islamic capital markets such as the Jakarta IslamicIndex (JII) are a relevant choice because the JII is an investment index that complies with Sharia principles. This research aims to predict stock prices in the JII using the Random Forest (RF) algorithm andform an optimal portfolio with the Mean-Variance Efficient Portfolio (MVEP) model. The data used isthe daily closing price of JII stocks from April 2023 to March 2024, obtained from the Indonesia StockExchange and Yahoo Finance. The RF method is used to predict stock prices, with model performanceevaluation using Mean Absolute Percentage Error (MAPE). The results showed that the application ofML with the RF algorithm in predicting stock prices produced very good predictions because the evaluation results using MAPE were in the 0%-10% range, namely a value of 2.522% for ACES shares;1.222% for ICBP shares, and 0.760% for INDF shares. The optimal portfolio formed using MVEPproduces a stock composition with a weight of 7.64% for ACES, 22.46% for ICBP, and 69.90% forINDF. The optimal portfolio’s estimated expected return and risk are 0.0546% and 0.0103%.

Bridging the Gap in Interactive Education: A WordWall Training Initiative for MGMP Instructors in Padang Panjang Agustina, Dina
Pelita Eksakta Vol 7 No 2 (2024): Pelita Eksakta, Vol. 7, No. 2
Publisher : Fakultas MIPA Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/pelitaeksakta/vol7-iss2/242

In the quest for educational advancement in Padang Panjang, Indonesia, this article presents a groundbreaking initiative titled "Bridging the Gap in Interactive Education: A WordWall Training Initiative for MGMP Instructors." The primary objective of this initiative was to elevate interactive teaching methodologies among MGMP (Mata Pelajaran Guru) instructors by focusing on three crucial assessment indicators: the enhancement of knowledge regarding instructional media, the cultivation of proficiency in utilizing teaching media throughout the learning process, and the introduction of innovative tools and insights applicable to the teaching process. Conducted with active participation from MGMP instructors, this training program centered around WordWall, a digital educational platform. The remarkable outcome of this study reveals unanimous agreement, with all participating instructors unequivocally affirming their satisfaction with the improvements in the assessed indicators. These results signify the effective bridging of the gap in interactive education by offering professional development opportunities and introducing novel tools, such as WordWall. This initiative serves as a pivotal step in empowering instructors and elevating the quality of education in Padang Panjang, underscoring the importance of embracing innovative teaching methodologies for a brighter educational future.

Analysis of Gold Price Forecasts Using Automatic Clustering Method and Fuzzy Logic Relationship Jannah, Ro'i Khatul; Agustina, Dina
Jurnal Varian Vol. 8 No. 2 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v8i2.4382

Gold is often chosen as an investment due to its lucrative potential. To maximize profits and avoid losses, investors need to understand the volatile price movements of gold. This research aims to forecast the price of gold in the next period. In this research, the forecasting method used is Automatic Clustering and Fuzzy Logical Relationship (ACFLR). ACFLR is a method that uses the concept of fuzzy logic for modeling time series data. The forecasting process includes data sorting, cluster formation, interval determination, fuzzification, FLR and FLRG formation, and calculation of forecasting values. Based on this method, the result of the gold price forecast in Padang City for the next period, namely January 2024 using the ACFLR method is IDR 978,796.9. with a MAPE value of 0.9%, which means this method is very good. For further researchers, it is hoped that the Fuzzy Time Series method can use other forecasting models in order to obtain the most optimal method for forecasting gold prices.

Co-Authors Akira Mikail Bali Yana Fitri Defri Ahmad Devni Prima Sari Dina Fakhriyana Ferdi Henfi Pratama Humairah, Putri Jannah, Ro'i Khatul Muhammad Habibul Ikhsan Muhammad Rashif Hilmi Rahmawati Rara Sandhy Winanda Riga Riga Trisna Kumala Sari Wandi Oktria

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