Garuda - Garba Rujukan Digital

Pelatihan Keberlanjutan Manfaat Program Merdeka Universitas Teknologi Sumbawa di Desa Kerekeh Abdul Salam; Fahlia Fahlia; Nuramaliyah Nuramaliyah; Agus Santoso; Fendy Maradita; Hanifa Sri Nuryani; Hartini Hartini
Jurnal Pengabdian Masyarakat Nusantara Vol. 3 No. 1 (2023): Februari-Juli 2023
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jpmn.v3i1.881

Sustainability of the Merdeka program aims to provide knowledge and skills in digital marketing, processing PIRT and halal product permits, training on human resources as well as tips and tricks for managing businesses in the digitalization period for MSME players in Kerekeh Village, Unter Iwes District, Sumbawa Regency, West Nusa Tenggara.The implementation was carried out by providing information services using the lecture method in the form of socialization, namely with presentation techniques. With this Community Service, it is hoped that MSME products can be quickly recognized and reach consumers which has an impact on increasing profits or production profits. The activity took place conducively, where all participants were very enthusiastic in participating in the activity from the beginning to the end of the activity. This community service activity involves cross study programs. Not only does this collaboration produce a better and more innovative model, but it also contributes more positively to the knowledge and skills of MSMEs in Kerekeh Village.

Indeks Harga Komsumen (IHK) di Lampung Menggunakan Autoregressive Integrated Moving Average (ARIMA) Mika Alvionita Sitinjak; Nuramaliyah ‎
Indonesian Journal of Applied Mathematics Vol 3 No 1 (2023): Indonesian Journal of Applied Mathematics Vol. 3 No. 1 July Chapter
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM), Institut Teknologi Sumatera, Lampung Selatan, Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35472/indojam.v3i1.1274

The Consumer Price Index (CPI) is an indicator that influences economic growth. CPI is an index that calculates the average of price change of a group of goods and services consumed by households in a certain period of time. CPI is also used to measure inflation in a country. Inflation is described by changes in the CPI from time to time. To anticipate and minimize economic risks caused by inflation, forecasting will be carried out on CPI data. In this study, the CPI will be predicted for the next 6 months using the ARIMA (Autoregressive Integrated Moving Average) model. The result of this research shows that the ARIMA models that can be used to predict CPI are ARIMA (0,2,0), ARIMA (0,2,1), ARIMA (1,2,0), and ARIMA (1,2,1) . The selection of the best model is carried out based on the model that has the smallest AIC value. Based on this, the best model used to predict CPI is the ARIMA model (0,2,1) with an AIC value of 83.21. In addition, this model fulfills diagnostics with white noise residuals, so that forecasting results using this model will be more accurate.

Air Temperature Prediction System Using Long Short-Term Memory Algorithm Faulina, Ria; Nuramaliyah, Nuramaliyah; Safitri, Emeylia
Rekayasa Vol 17, No 3: Desember, 2024
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v17i3.28229

Air temperature is a highly essential parameter in weather forecasting methods and a critical variable for predicting future weather patterns. An accurate temperature prediction system can assist individuals and organizations in preparing for activities heavily influenced by weather conditions. Therefore, developing a precise temperature prediction model requires a reliable and effective algorithm. In this study, the Long Short-Term Memory (LSTM) algorithm, a type of artificial neural network (Recurrent Neural Network - RNN), is implemented with time series data decomposition for variable input processing. LSTM is specifically designed to handle sequential data or time series data, such as weather data. Additionally, LSTM-GRU and LSTM-Conv1D models are utilized. The dataset used in this research comprises air temperature data provided by the Meteorology, Climatology, and Geophysics Agency (BMKG) in the DKI Jakarta region. Model evaluation is conducted using criteria for the smallest Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). Experiments show that the prediction system based on LSTM-GRU achieves the lowest MAE and RMSE values compared to LSTM and LSTM-Conv1D, across 10, 20, and 30-step predictions. It can be concluded that the LSTM-GRU algorithm provides the most accurate predictions compared to the LSTM and LSTM-Conv1D models for sequential temperature data, given sufficient data and a properly configured model. This is also graphically demonstrated by prediction results closely aligning with the actual data.

PENGARUH MATEMATIS JUMLAH MAHASISWA UNIVERSITAS TERBUKA TERHADAP ANGKA PARTISIPASI KASAR PERGURUAN TINGGI TIAP PROVINSI DI INDONESIA Nuramaliyah, Nuramaliyah; Safitri, Emeylia; Faulina, Ria
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 3 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i3.830

Education is a key determinant of the quality of human resources in Indonesia. One indicator used to measure educational participation in a region is the Gross Enrolment Ratio (GER). This study focuses on analyzing the influence of the socio-economic conditions of the population and the number students of Universitas Terbuka on the Gross Enrolment Ratio for higher education (GER-HE) in Indonesia. The aim of this research is to analyze the factors that influence the Gross Enrolment Ratio for higher education in several regions. This study uses a quantitative research design with a regression panel data approach. The study area covers all provinces in Indonesia, comprising 34 provinces. The data used in this study is secondary data obtained from the Badan Pusat Statistik (BPS) for the years 2018-2022, including data on GER-HR, poverty indicator, the number of higher education institutions, and expenditure per capita for each province. Additionally, data was sourced from DAAK-UT to obtain the number of Universitas Terbuka students for the years 2018-2022. Based on the results of the Fixed Effect Model (FEM) panel data regression with individual/cross section effects, the factors that influence the GER-HR value are the number of new UT students and per capita expenditure. The number of new UT students has a positive effect while per capita expenditure has a negative effect on GER-HE in Indonesia. Then for variables that have no effect are the number of universities, and per capita expenditure.

MAPPING INDONESIA'S AGRICULTURAL DIVERSITY: CLUSTERING PROVINCES WITH SELF-ORGANIZING MAPS Fitriana, Ika Nur Laily; Leviany, Fonda; Faulina, Ria; Nuramaliyah, Nuramaliyah; Safitri, Emeylia
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 3 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i3.844

The agricultural sector has an important role in national economic development in Indonesia. Based on data from the 2023 Agricultural Census from the Central Bureau of Statistics, it was found that the quantity and quality of the agricultural sector in various provinces in Indonesia still varies greatly. Hence, the suitable statistical methods are needed, namely cluster analysis, to group 38 provinces in Indonesia based on similar characteristics in the agricultural sector. Cluster analysis in this research uses the Self-organizing Maps (SOM) method. Before cluster analysis is carried out, Principal Component Analysis (PCA) is carried out to reduce the dimensions of the variables so that the data is easier to process and avoids the curse of dimensionality. The PCA results obtained 2 main components formed from 9 agricultural sector variables, which were then used as input data for clustering analysis with SOM. The results of clustering with SOM showed that the optimal number of provincial groups was 3 with a Davies-Boulden Index (DBI) value of 0.544 and a Silhouette of 0.623. The results of grouping the provinces can then be categorized into cluster 1 with a high average value of agricultural sector variables, cluster 2 with a medium average value of agricultural sector variables, and cluster 3 with a low average value of agricultural sector variables.

Peningkatan Literasi Anak Usia Dini melalui Pendampingan Calistung di Taman Kanak-Kanak Nuramaliyah, Nuramaliyah; Mikhratunnisa, Mikhratunnisa; Oryza Safitri; Lukmanul Hakim; Diah Anggeraini Hasri; Amry Purnama Mauladi; Fitriyantari
Abdimas Indonesian Journal Vol. 5 No. 1 (2025)
Publisher : Civiliza Publishing

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

This community service aims to improve early childhood literacy through Calistung (Reading, Writing, and Counting) mentoring using the card method in Kindergarten. The card method is used to help children recognize letters, numbers, and improve reading and writing skills interactively. Mentoring activities are carried out by introducing various letter, number, and picture cards that are in accordance with the material being taught. Mentoring is carried out in a fun way through games and movements that involve the active participation of children. The evaluation results show that children have improved in recognizing letters, numbers, and reading and writing skills. This program has also succeeded in increasing children's motivation to learn in a fun way. With a visual approach and games, children find it easier to understand basic literacy concepts. Mentoring using the card method has proven effective in improving basic literacy skills in early childhood, creating a positive learning atmosphere, and supporting children's cognitive development

Pelatihan Keberlanjutan Manfaat Program Merdeka Universitas Teknologi Sumbawa di Desa Kerekeh Salam, Abdul; Fahlia, Fahlia; Nuramaliyah, Nuramaliyah; Santoso, Agus; Maradita, Fendy; Sri Nuryani, Hanifa; Hartini, Hartini
Jurnal Pengabdian Masyarakat Nusantara (JPMN) Vol. 3 No. 1 (2023): Februari-Juli 2023
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jpmn.v3i1.881

Sustainability of the Merdeka program aims to provide knowledge and skills in digital marketing, processing PIRT and halal product permits, training on human resources as well as tips and tricks for managing businesses in the digitalization period for MSME players in Kerekeh Village, Unter Iwes District, Sumbawa Regency, West Nusa Tenggara.The implementation was carried out by providing information services using the lecture method in the form of socialization, namely with presentation techniques. With this Community Service, it is hoped that MSME products can be quickly recognized and reach consumers which has an impact on increasing profits or production profits. The activity took place conducively, where all participants were very enthusiastic in participating in the activity from the beginning to the end of the activity. This community service activity involves cross study programs. Not only does this collaboration produce a better and more innovative model, but it also contributes more positively to the knowledge and skills of MSMEs in Kerekeh Village.

THE BEST GLOBAL AND LOCAL VARIABLES OF THE MIXED GEOGRAPHICALLY AND TEMPORALLY WEIGHTED REGRESSION MODEL Nuramaliyah Nuramaliyah; Asep Saefuddin; Muhammad Nur Aidi
Indonesian Journal of Statistics and Applications Vol 3 No 3 (2019)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v3i3.564

Geographically and temporally weighted regression (GTWR) is a method used when there is spatial and temporal diversity in an observation. GTWR model just consider the local inï¬‚uences of spatial-temporal independent variables on dependent variable. In some cases, the model not only about local influences but there are the global influences of spatial-temporal variables too, so that mixed geographically and temporally weighted regression (MGTWR) model more suitable to use. This study aimed to determine the best global and local variables in MGTWR and to determine the model to be used in North Sumatraâ€™s poverty cases in 2010 to 2015. The result show that the Unemployment rate and labor force participation rates are global variables. Whereas the variable literacy rate, school enrollment rates and households buying rice for poor (raskin) are local variables. Furthermore, Based on Root Mean Square Error (RMSE) and Akaike Information Criterion (AIC) showed that MGTWR better than GTWR when it used in North Sumatraâ€™s poverty cases.

Low Maternal Seafood Intake During Exclusive Lactation Does Not Significantly Affect Milk Protein Content Sari, Ratna Nurmalita; Nuramaliyah, Nuramaliyah
Journal of Applied Agricultural Science and Technology Vol. 9 No. 2 (2025): Journal of Applied Agricultural Science and Technology
Publisher : Green Engineering Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55043/jaast.v9i2.395

Human milk, which contains complex and highly variably biofluid that nourishes and protects the newborn, is the gold standard for infant nutrition. The biological activity of human milk is significantly influenced by proteins. However, the relationship between crude protein in human milk and the amount of milk consumed by mothers during the exclusive breastfeeding period has not been thoroughly investigated. In the current study, 194 healthy women who were exclusively breastfeeding participated in a cross-sectional study to collect human milk samples and complete a quantitative frequent food questionnaire (FFQ). The consumption of cereals, potatoes, sweet potatoes, leafy vegetables, fruits, other vegetables, legumes, nuts, eggs, meats, dairy products, and seafood was grouped based on the consumption of the mother the day before milk collection. The mid-infrared milk analyzer was used to analyze the samples and determine protein concentration. Using the t-test to analyze the impact of partial factors, and the F-test was employed to evaluate the influence of variables concurrently, at a 5% significance level. The statistical relationship between maternal diet and protein content was evaluated. Seafood consumption was categorized as low compared to other groups. Self-imposed maternal food restrictions may be the cause of the reduced seafood consumption. Human milk has an average protein level of 1.02 g/100 ml. According to the statistics, there was no significant correlation between the crude protein content of human milk and seafood consumption. However, a strong correlation was found between the consumption of eggs, legumes, and nuts, suggesting that these foods may impact on the protein content of human milk (p value <0.05). This finding would suggest that to improve the protein content composition of human milk, nursing mothers should consume more local, high-protein foods.

The Impact of Digital Marketing and Entrepreneurial Capabilities on Marketing Performance Hardiansyah, Rian; Fahlia, Fahlia; Nuramaliyah, Nuramaliyah
Indonesian Business Review Vol 7 No 2 (2024): Indonesian Business Review
Publisher : Universitas Prasetiya Mulya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21632/ibr.7.2.105-114

The objective of this study is to assess the impact of digital marketing and entrepreneurial competence on the marketing performance of micro, small, and medium enterprises (MSMEs) in the Sumbawa district. An investigation was carried out involving 180 owners of Micro, Small, and Medium Enterprises (MSMEs), and the collected data was evaluated using Structural Equation Modeling-Partial Least Square (SEM-PLS). The research findings indicate that both digital marketing competency and entrepreneurial competency have a notable and beneficial impact on marketing performance. Additionally, it is observed that digital marketing competency specifically has a favorable and considerable influence on marketing performance. According to the findings of this study, it is crucial for MSMEs in Sumbawa Regency to give priority to enhancing their digital marketing and entrepreneurial abilities in order to enhance their marketing effectiveness. This research has significant ramifications for owners of micro, small, and medium enterprises (MSMEs), policymakers, and researchers, highlighting the necessity for additional investigation into this subject matter.

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