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All Journal Journal of Natural Sciences and Mathematics Research BAREKENG: Jurnal Ilmu Matematika dan Terapan Mandalika Mathematics and Educations Journal Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi MATHunesa: Jurnal Ilmiah Matematika
Suhendra, Helen
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Transportation

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Perbandingan Model Pembelajaran Case Method Dan Diskusi Dengan Menggunakan Hipotesis Uji Mann Whitney Dan Kolmogorov Smirnov Suhendra, Helen; Ineu Sulistiana
Mandalika Mathematics and Educations Journal Vol 7 No 1 (2025): Edisi Maret
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v7i1.7505

Abstract

Pendidikan merupakan sebuah proses pembelajaran bagi setiap individu. Dalam sistem pembelajaran, ada banyak cara atau model-model yang dapat diterapkan dalam perkuliahan agar suasana belajar mengajar terasa lebih menyenangkan yaitu model pembelajaran diskusi, kolaboratif, case method dan sebagainya. Pada penelitian ini digunakan model pembelajaran diskusi dan case method untuk mengetahui apakah ada perbedaan antara kedua model tersebut, maka digunakan uji nonparametrik dua sampel independen. Uji yang digunakan untuk membandingkan perbedaan antara dua sampel yang independen yaitu Uji Mann Whitney dan Uji Kolmogorov Smirnov. Alasan digunakan metode tersebut, karena metode ini dapat menilai apakah dua sampel independen yang diamati terdapat perbedaan atau tidak secara signifikan. Tujuan penelitian ini adalah untuk menguji apakah ada perbedaan nilai yang signifikan antara kedua model pembelajaran tersebut dan melihat metode manakah yang terbaik dengan melihat Mean Square Error (MSE) terkecil. Hasil penelitian menyimpulkan bahwa perhitungan pada pengujian hipotesis Uji Mann Whitney dan Uji Kolmogorov smirnov terhadap model pembelajaran case method dan diskusi yaitu terima H0 artinya tidak ada perbedaan bermakna antara model pembelajaran case method dan diskusi. Berdasarkan hasil statistik Uji Kolmogov Smirnov ternyata lebih baik dibandingkan dengan Uji Mann Whitney. Karena Uji Kolmogov Smirnov memiliki nilai Error atau MSE lebih kecil dibandingkan dengan Uji Mann Whitney.
VOLATILITY ANALYSIS AND INFLATION PREDICTION IN PANGKALPINANG USING ARCH GARCH MODEL Dalimunthe, Desy Yuliana; Kustiawan, Elyas; -, Khadijah; Halim, Niken; Suhendra, Helen
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp237-244

Abstract

One of the concerns of both developed and developing countries, as well as in a region, is the amount of inflation that occurs. Inflation is a serious problem. Inflation is a macroeconomic variable that affects people's welfare and is defined as a complex phenomenon resulting from general and continuous price increases. This research aims to analyze the volatility and projected value of the inflation rate, especially in Pangkalpinang City, using the Autoregressive Conditional Heteroskedasticity (ARCH) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models. This research uses time series data on inflation rate of Pangkalpinang, Bangka Belitung Island Province from January 2014 to May 2024. This data was obtained through publications from the Central Statistics Agency of Bangka Beliltung Islands Province. The ARCH model is used to handle heteroscedasticity in data, while the GARCH model is a development of the ARCH model and serves as a generalization of the volatility model. This research shows that the predicted inflation rate in Pangkalpinang City from June 2024 to November 2024 tends to decrease with a MAPE prediction accuracy level of 200.04%. The high MAPE value is caused by actual data moving toward 0.
PENERAPAN MODEL ARIMAX DALAM MEMPREDIKSI SAHAM TINS DAN INFLASI DI KOTA PANGKAL PINANG suhendra, helen; Desy Yuliana Dalimunthe
MATHunesa: Jurnal Ilmiah Matematika Vol. 13 No. 2 (2025)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini bertujuan untuk memprediksi harga saham PT Timah Tbk (TINS) dengan menggunakan pendekatan model ARIMAX, serta menganalisis hubungan antara inflasi di Kota Pangkal Pinang sebagai variabel eksogen dan pergerakan saham TINS sebagai variabel endogen. Data yang digunakan merupakan data bulanan dari Januari 2020 hingga April 2025. Model ARIMAX dipilih karena mampu mengakomodasi hubungan jangka pendek dan panjang antar variabel. Berdasarkan hasil identifikasi orde model menggunakan plot ACF dan PACF serta pemilihan model terbaik berdasarkan kriteria Akaike Information Criterion (AIC), diperoleh model ARIMAX(1,1,2) sebagai model terbaik. Hasil estimasi menunjukkan bahwa parameter AR(1) dan MA(2) signifikan secara statistik, sedangkan variabel inflasi tidak signifikan, namun tetap relevan secara teoritis. Model ARIMAX(1,1,2) berhasil memenuhi uji asumsi residual white noise dan menghasilkan nilai MAPE sebesar 12,5%, yang menunjukkan tingkat akurasi prediksi yang baik. Oleh karena itu, model ini direkomendasikan untuk digunakan dalam prediksi jangka pendek harga saham TINS dan sebagai dasar penyusunan kebijakan ekonomi di tingkat regional.
Implementasi Artificial Neural Network (ANN) dalam Memprediksi Nilai Tukar Rupiah terhadap Dolar Amerika Sakti, Adam Indra; Saputra, Lianda; Suhendra, Helen; Halim, Nikken; Alviari, Irfaliani; Ilham, Muhammad Rozan Nur; Putri, Marwah Hotimah Nada; Dalimunthe, Desy Yuliana
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 12 Issue 2 December 2024
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v12i2.26654

Abstract

The exchange rate of one country's currency against other countries takes an important role in the development and economic activities for a nation. This condition of the Indonesian currency exchange rate, namely the rupiah, is now continuously increasing, meaning that the exchange rate is weakening and experiencing depreciation. Apart from that, the rupiah exchange rate also experiences fluctuations, so forecasting is needed to find solutions to problems that will arise if the currency exchange rate increases. This research purpose is to find the best of network archictecture and to predict the selling rate of the rupiah (Rp) per 1USD for one year. The forecasting method used in this research is using an Artificial Neural Network (ANN) with Backpropagation algorithm. This method is suitable for use in time series analysis because the algorithm is able to adjust the data and has a relatively small error. The data used is the rupiah exchange rate against the USD in the form of time series data, which from March 1, 2019 to February 28, 2024. The data scenario of 90% training and 10% testing at the training stage obtained the best architecture 4-20-1 with MSE is 0.0010385. The data scenario is 80% training and 20% testing where in the training the best architecture is 4-25-1 with an MSE of 0.00089412. The data scenario is 70% training 30% testing where in the training the best architecture is 4-25-1 with an MSE of 0.00099221. Thus, the prediction prices used are predictions for the 80% training data scenario and 20% testing data, because the accuracy results (MSE) are better than the other two scenarios.
Analysis of Population, Poverty, Unemployment Rate, and Gini Ratio on Human Development Index in Bangka Belitung Suhendra, Helen; Adam Indra Sakti; Muhammad Akbar Khaffi; Dalimunthe, Desy Yuliana; Haris Zirtana; Ridho Juniar; Diah Novita Sari; Muhammad Raqi Tama; Kristin Verahditiya
Journal of Natural Sciences and Mathematics Research Vol. 11 No. 1 (2025): June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jnsmr.v11i1.23671

Abstract

The Human Development Index (HDI) is a measure that evaluates human development achievements based on fundamental quality-of-life components that can influence individual productivity levels. This study aims to analyze the impact of Population Size, Percentage of Poor Population, Open Unemployment Rate (TPT), and Gini Ratio on the Human Development Index (HDI) in the Bangka Belitung Islands Province from 2018 to 2023. The panel data regression method was employed, combining time series and cross-sectional data to provide more accurate information. The findings reveal that the HDI of the Bangka Belitung Islands Province has increased yearly, though it remains below the national average. The selected model was the Fixed Effect Model (FEM) based on the results of the Chow and Hausman tests. Analysis indicates that Population Size has a positive and significant effect on HDI, while the Percentage of Poor Population has a negative and not significant effect. Additionally, the Open Unemployment Rate (TPT) has a positive and significant effect on HDI, whereas the Gini Ratio has a negative and significant effect. Simultaneously, the four independent variables contributed 95.44% to HDI. These findings are expected to inform government efforts to improve human development quality, such as poverty alleviation, and highlight the need for attention to population management in balancing employment opportunities in the region and the government should work to reduce the unemployment rate through policies that focus on job creation, increasing workforce competitiveness, and addressing inequality, as reflected by the Gini ratio. This can be achieved by expanding equitable access to education and healthcare.
Co-Authors -, Khadijah Adam Indra Sakti Alviari, Irfaliani Desy Yuliana Dalimunthe Desy Yuliana Dalimunthe, Desy Yuliana Diah Novita Sari Halim, Niken Halim, Nikken Haris Zirtana Ilham, Muhammad Rozan Nur Ineu Sulistiana Kristin Verahditiya Kustiawan, Elyas Muhammad Akbar Khaffi Muhammad Raqi Tama Putri, Marwah Hotimah Nada Ridho Juniar Sakti, Adam Indra Saputra, Lianda