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All Journal EIGEN MATHEMATICS JOURNAL Mandalika Mathematics and Educations Journal Contemporary Mathematics and Applications (ConMathA) Bakti Sekawan : Jurnal Pengabdian Masyarakat Jurnal Sains Natural Al-Aqlu : Jurnal Matematika, Teknik dan Sains Semeton Mathematics Journal
Robbaniyyah, Nuzla Af'idatur
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Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering Health Professions Materials Science & Nanotechnology Mathematics Nursing Physics Public Health Social Sciences Other

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Journal : Semeton Mathematics Journal

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Trends Analysis Between The Relationship Rice Harvest and Rice Productivity in Nusa Tenggara Province Hamdiah, Yulinda Raudatul; Robbaniyyah, Nuzla Af'idatur
Semeton Mathematics Journal Vol 2 No 1 (2025): April
Publisher : Program Studi Matematika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/semeton.v2i1.257

Abstract

This study aims to analyze the monthly trends in rice productivity and harvested area in West Nusa Tenggara (NTB) Province in 2023 and identify the relationship between these two variables. The data used in this research were obtained through a rice crop cutting survey based on the Area Sample Frame (KSA) method conducted by the Central Statistics Agency. Productivity was calculated based on the amount of yield produced per unit area of land each month. The results showed that rice productivity in NTB Province fluctuated, with the highest productivity recorded in January at 56.54 quintals per hectare (ku/ha) and the lowest in June at 48.40 ku/ha. Similarly, the harvested area varied, with the largest area recorded in March at 73,766 hectares and the smallest in December at 5,382 hectares. The analysis of the relationship between harvested area and rice productivity revealed an inverse pattern, where an increase in harvested area was not always accompanied by an increase in productivity. Therefore, rice productivity and harvested area are more influenced by external factors and do not directly affect each other.
Analisis Pola Periodik Harga Saham Coca-Cola Menggunakan Deret Fourier dalam Model Regresi Linear Karang, Gusti Yogananda; Hardi, Rida Alkausar; Rizki, Miptahul; Robbaniyyah, Nuzla Af'idatur; Rusadi, Tri Maryono
Semeton Mathematics Journal Vol 2 No 1 (2025): April
Publisher : Program Studi Matematika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/semeton.v2i1.271

Abstract

This study aims to identify periodic patterns and predict the movement of Coca-Cola (KO) stock prices using Fourier series in a linear regression model. The data utilized includes daily closing stock prices over the 2014-2024 period. A Fourier model with 15 harmonic components was chosen to optimize the balance between prediction accuracy and the risk of overfitting. The analysis results showed an R-squared value of 0.9174, indicating a high capability of capturing stock price variations. The detected price fluctuations reveal significant seasonal cycles and periodic trends. The price forecast for the 2024-2029 period indicates potential higher volatility, influenced by consumer demand dynamics, global economic uncertainty, product innovation, as well as geopolitical factors and climate change. These findings provide insights for investors to develop investment strategies based on the detected stock price fluctuation patterns.
Simulasi Penghilangan Noise pada Sinyal Suara menggunakan Metode Fast Fourier Transfrom Septiawan, Redza Dwi; Rayes, Putri Rahmasari; Robbaniyyah, Nuzla Af'idatur
Semeton Mathematics Journal Vol 1 No 1 (2024): April
Publisher : Program Studi Matematika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/semeton.v1i1.203

Abstract

Sound signals are widely used such as when communicating, recording, or medical testing. However, voice signals are often contaminated by noise or interference which can reduce the quality and clarity of sound caused by weather, being in crowded places and other factors. Therefore, noise reduction in voice signals is important in voice signal processing. This study aims to reduce noise in voice signals using the FFT method. The Fast Fourier Transform (FFT) method is used to identify frequencies and reduce noise in voice signals. The data used is in the form of recordings, namely the sound of speech and the sound of rain as noise. This research was conducted with the help of MATLAB R2022a software. The results of this study indicate that the FFT method is effective in reducing noise in the voice signal and improving the sound quality to be cleaner and clearer than the original sound signal before noise removal is performed.
Simulasi dan Akurasi Numerik Persamaan Gelombang Satu Dimensi Menggunakan Aproksimasi Metode Beda Hingga Robbaniyyah, Nuzla Af'idatur; Muliyanti, Annisa Sri; Malasso, Dede Ambiya; Pajri, Dwi Hafizatul
Semeton Mathematics Journal Vol 1 No 1 (2024): April
Publisher : Program Studi Matematika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/semeton.v1i1.204

Abstract

The wave equation is a form of partial differential equation that represents physical phenomena on classical physics that are often encountered in everyday life. For example a mechanical waves, such as water waves, sound waves, and seismics waves or light waves. In this research, discussed one-dimensional homogeneous wave equation. Analytical solutions and numerical solutions will be peeled in this research. The numerical solution is approached by using the finite center difference method with an explicit scheme. The solution obtained is simulated with MATLAB software. The results show that the analytical solution has the same pattern as the numerical solution. In other hand, a good level of accuracy was also is obtained using different methods by using a Mean Absolute Percentage Error (MAPE) value of 12%.
Design of Facial Expressions Recognition for Academic Presence By Using Backpropagation Artificial Neural Networks Based on Principal Components Analysis Setiawati, Setiawati; Zahro, Uswatun Az; Robbaniyyah, Nuzla Af'idatur; Ihwani, Ivan Luthfi
Semeton Mathematics Journal Vol 1 No 2 (2024): Oktober
Publisher : Program Studi Matematika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/semeton.v1i2.240

Abstract

There are 4,004 universities in Indonesia where each university needs data to find out student activities, one of which is through attendance. Some universities in Indonesia still use manual attendance systems and attendance systems through the website. This system has several obstacles that require solutions. Therefore, a more concise system is needed to assist students in filling in the attendance. This research aims to make a design to make academic presence for students by using neural network. There are many methods that can be used to create this system including using Principal Component Analysis (PCA) based on Backlpropagation Neural Network (BNN) because it can help the system perform faster and more accurately without losing important information. After carrying out a series of steps of algorithm designed for student attendance, we get the recognition of facial image expressions by using ANN Backpropagation and recognition of facial image expression with PCA.
Analysis of Changes in Agricultural Land Area in Central Lombok Regency Using Google Earth Engine Ulatalita, Nabila Anzela; Fatanaya, Nafika; Ulfa, Kurnia; Robbaniyyah, Nuzla Af'idatur; Alfian, Muhammad Rijal
Semeton Mathematics Journal Vol 2 No 2 (2025): Oktober
Publisher : Program Studi Matematika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/semeton.v2i2.317

Abstract

Agricultural land plays a vital role in supporting food security and the regional economy; however, rapid development often leads to land-use conversion. This study aims to analyze changes in agricultural land in Central Lombok Regency over the past ten years (2014–2023) using the Google Earth Engine (GEE) platform. The research utilized Landsat satellite imagery to classify land cover types and identify agricultural areas through supervised classification and change detection techniques. The analysis results show a significant decline in agricultural land area, from 29% in 2014 to 26% in 2023. This decrease indicates a conversion of agricultural land to other more economically profitable uses, such as infrastructure development and plantation expansion. The accuracy assessment yielded an overall accuracy of 99%, which is categorized as very good, demonstrating the reliability of the model in mapping land-use changes. The findings of this study are expected to provide useful insights for policymakers in promoting sustainable land-use planning and mitigating the negative impacts of land conversion on the agricultural sector in Central Lombok Regency.
Application of Google Earth Engine for Agriculture Drought Monitoring in East Lombok Robbaniyyah, Nuzla Af'idatur; Hidayatunnisa, Nurul; Maharani, Rani; Ulfa, Kurnia; Alfian, Muhammad Rijal
Semeton Mathematics Journal Vol 2 No 2 (2025): Oktober
Publisher : Program Studi Matematika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/semeton.v2i2.319

Abstract

In tropical regions such as East Lombok Regency, where food production is highly dependent on rainfall, drought poses a major threat to the agricultural sector. This study aims to monitor drought patterns over time using Google Earth Engine (GEE). Vegetation indices, including the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Normalized Difference Drought Index (NDDI), were derived from Landsat 8 satellite imagery. The analysis revealed that during the dry season, particularly in August and September, the southern region—especially Jerowaru Sub-district—experienced severe drought conditions. The western parts, including Sambelia, Pringgabaya, and Suela Sub-districts, were also significantly affected, with the most impacted areas being rain-fed rice fields, corn plantations, and mixed horticultural crops. Temporal trend analysis indicated an increasing drought intensity in the later years of observation. The resulting information can support decision-making in drought risk mitigation and sustainable water resource management. By integrating satellite-based drought assessment with agricultural planning, this approach can strengthen food security and promote adaptive agricultural practices in drought-prone regions such as East Lombok Regency.
Co-Authors Abdullah, Umar Abdurahim, Abdurahim Al Paqih, Muhammad Imam Anjani, Mutia Dewi Az-Zahra, Al Farrah Choirunnisa, Fajarani Dani, Ifan Hasnan Fatanaya, Nafika Haizar, Maulana Rifky Hamdiah, Yulinda Raudatul Hardi, Rida Alkausar Harsyiah, Lisa Hidayatullah, Azka Farris Hidayatunnisa, Nurul Irwansyah Irwansyah Ivan Luthfi Ihwani, Ivan Luthfi Karang, Gusti Yogananda Kusuma, Shendy Arya Lailia Awalushaumi Lailia Awalushaumi, Lailia Lansuna, Ni Wayan Eka Maharani, Andika Ellena Saufika Hakim Malasso, Dede Ambiya Marwan Marwan Maulani, Septia Hasna Muhammad Rijal Alfian Muliyanti, Annisa Sri Pajri, Dwi Hafizatul Pradana, Satriawan Qurratul Aini Ramadhan, Fitrah Ramadhan, Hikmal Maulana Rani Maharani Rayes, Putri Rahmasari Rio Satriyantara Rizki, Miptahul Salwa Salwa Satryantara, Rio Septiawan, Redza Dwi Setiawati Setiawati Syamsul Bahri Tri Maryono Rusadi Ulatalita, Nabila Anzela Ulfa, Kurnia Uluwi, Ahmad Ihsan Yumni Awanis, Zata Zahro, Uswatun Az Zikri, Lalu Muhammad Faiz Zulhan Widya Baskara