Semeton Mathematics Journal

Analisis Faktor-faktor yang Mempengaruhi Ketergantungan Penggunaan ChatGPT pada Pengerjaan Tugas Mahasiswa Universitas Mataram

Mon, 27 Oct 2025 00:00:00 +0000

The use of artificial intelligence technology, such as ChatGPT, is increasing among students to support their academic assignments. However, dependence on this technology needs to be analyzed to understand the factors that influence it. This study aims to analyze the factors that influence the dependence on the use of ChatGPT in completing assignments of Mataram University students. Sampling was carried out using the quota sampling method, involving 98 respondents who were Mataram University students and ChatGPT users. The method used was multiple linear regression to evaluate the effect of independent variables on dependence, and factor analysis to identify the structure of these variables. Based on the results of the analysis, one main factor was found which was formed from four variables, namely ChatGPT Ease of Use, ChatGPT Reliability, User Satisfaction, and Perceived Benefits. This main factor was able to explain 71.73% of the total data variation, which showed a significant contribution to students' dependence on using ChatGPT. Thus, this study shows that these variables are interrelated and influence the level of students' dependence on ChatGPT in completing academic assignments.

Peramalan Produksi Kedelai di Provinsi Nusa Tenggara Barat menggunakan Model Grey-Markov (1,1)

Mon, 27 Oct 2025 00:00:00 +0000

The continuously increasing soybean imports are caused by the imblance in domestic soybean produstion. This indicates that nationalsoybean self-sufficiensy has not yet been achieved, as many soybean farmlands have now been converted to other commodities. This condition occurs in West Nusa Tenggara, Which is one of Indonesia’s nationalsoybean production centers. To understand future soybean production conditions, forecasting future soybean production in West Nusa Tenggara province using the grey_markov (1, 1) model. This model only requires minimal data for forecasting, which aligns with the limites research data available. The data used in this study is soybean production data from West Nusa Tenggara province. The research results show that in 2022, soybean production in West Nusa Tenggara province will decline, with the prediction demonstrating good accuracy as indicated by a MAPE value of 15.75%.

Analysis of Changes in Agricultural Land Area in Central Lombok Regency Using Google Earth Engine

Mon, 27 Oct 2025 00:00:00 +0000

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.

Pengendalian Kualitas Produksi Air Minum dalam Kemasan (AMDK) Menggunakan Diagram Kendali MCUSUM dan MEWMA

Kurnia Mahraini Kartika Sari, Lisa Harsyiah, Zulhan Widya Baskara — Mon, 27 Oct 2025 00:00:00 +0000

Quality control in the water production process at PT. X is an essential activity to ensure the quality of packaged drinking water (AMDK) is fit for consumption. Therefore, the water quality of PT. X production must always be closely monitored. To guarantee the safety of drinking water, it must meet microbiological, radioactive, Physical, and chemical requirements according to the regulations stipulated in the Indonesian Ministry of Health Regulation Number 2 of 2023. Quality control is performed using MEWMA and MCUSUM control charts since these control charts can detect shifts in the process mean. The results of applying MCUSUM and MEWMA control charts indicate that the water production quality is statistically out of control. After monitoring, it was found that PH is the most influential variable causing out-of-control situations. An ARL test was conducted to obtain a control chart with the best performance, where a smaller ARL value indicates better sensitivity in detecting shifts in the process mean. The MCUSUM control chart outperforms the MEWMA control chart, with an ARL value of and parameters and , compared to ARL MEWMA of with weighting parameter and .

Optimisasi Linear dan Kuadratik: Tinjauan Literatur

Syamsuddin Mas'ud — Mon, 27 Oct 2025 00:00:00 +0000

Convex Optimization plays a crucial role in various scientific and industrial applications, such as economics, engineering, and computer science, with a primary focus on linear and quadratic optimization. This study examines the characteristics and comparison between linear and quadratic optimization, two main subclasses of convex optimization. Linear optimization (LP) is characterized by a linear objective function and linear constraints, where classical methods such as Simplex and Interior-Point are used for efficient solutions. In contrast, quadratic optimization (QP) involves a convex quadratic objective function with linear constraints, requiring more complex methods such as Karush-Kuhn-Tucker (KKT) factorization, Schur-Complement, Null-Space, Active-Set, and Interior-Point for solving. This paper summarizes various solution methods for both types of optimizations and compares their strengths and limitations. The key findings indicate that linear optimization is simpler and more efficient, while quadratic optimization offers greater flexibility in modeling problems with more complex structures. The study concludes that a deep understanding of both approaches is essential for the development of more efficient and applicable convex optimization algorithms.

Harary Index of the Coprime Graph and Power Graph of the Integer Modulo Group and the Dihedral Group

Luzianawati Luzianawati, Rio Satriyantara — Mon, 27 Oct 2025 00:00:00 +0000

This study investigates the Harary Index of coprime graphs and power graphs constructed from the integer modulo group and the dihedral group. A coprime graph is defined as a graph whose vertices represent the elements of a group, where two vertices are adjacent if the orders of the corresponding elements are relatively prime. Meanwhile, a power graph is a graph in which two elements are connected whenever one is a power of the other within the group. The Harary Index is employed to measure the topological characteristics of the graph based on the distances between its vertices. The results show that the structure of the generated graphs allows for an explicit computation of the Harary Index, particularly for groups whose orders are prime powers.graphs facilitate the calculation of the Harary Index , especially for groups with prime power order.

Application of Google Earth Engine for Agriculture Drought Monitoring in East Lombok

Mon, 27 Oct 2025 00:00:00 +0000

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.

Optimasi Keuntungan Pertanian Melalui Program Linear: Studi Kasus pada Pertanian Padi dan Jagung

Mon, 27 Oct 2025 00:00:00 +0000

Indonesia is an agrarian country with great potential in the agricultural sector, particularly in key commodities such as rice and corn, which play an important role in food security and animal feed. However, limited resources such as land, fertilizer, and labor pose challenges in achieving production efficiency and maximum profits. This study aims to optimize agricultural land allocation to maximize profits using a linear programming model. The case study was conducted on agricultural land owned by a resident of Bajo Village, Bima Regency, West Nusa Tenggara. Primary data was collected through direct interviews, including land area, input requirements (fertilizer, pesticides, herbicides, and labor), and profit per hectare. The model was solved using the graphical method with the assistance of POM-QM for Windows and Google Colab application. The analysis results indicate that the optimal land allocation is 3.65 hectares for rice and 2.54 hectares for corn, yielding a maximum profit of Rp58.906.350,00. This solution meets all available resource constraints. These findings indicate that the linear programming approach is effective in helping farmers make data-driven decisions to improve land and resource management efficiency. The application of this model also opens opportunities for the implementation of similar methods in other sustainable agricultural planning, particularly in the context of small-scale agriculture with limited resources.