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The Influence of the Learning Environment in Shaping Early Childhood Learning Motivation Oktaviana, Yogi; Azzahra, Rizqina; Saadah, Siti
Seulanga : Jurnal Pendidikan Anak Vol. 6 No. 1 (2025): Seulanga : Jurnal Pendidikan Anak
Publisher : Jurusan Pendidikan Islam Anak Usia Dini

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47766/seulanga.v6i1.6070

Early childhood learning motivation is the most important development in learning aspect motivation. The learning environment greatly influences the learning process, which must create a conducive and supportive environment, because it significantly affects early childhood learning motivation. Early childhood learning motivation is influenced by various factors, which include parental support, teacher quality, and adequate facilities. Therefore, early childhood learning motivation must be created, because it greatly affects their enthusiasm for learning. The purpose of this paper is to analyze the effect of learning environment on early childhood learning motivation, with several factors considered. This study found that the interaction between parents and children, teachers and children, friends and children greatly influences early childhood learning motivation. This research has significant implications for developing appropriate learning strategies, thus providing high learning motivation for early childhood. The research method used is the literature method with journal and observation collection techniques. Which from the results of this study strongly proves that the learning environment and motivation for early childhood is very influential on themselves for the next level

Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) Methods to Forecast Daily Turnover at BM Motor Ngawi Larasati, Larasati; Saadah, Siti; Yunanto, Prasti Eko
Indonesian Journal of Artificial Intelligence and Data Mining Vol 7, No 1 (2024): March 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v7i1.27643

The number of motorcycles on the report of Indonesian BPS statistics from the Indonesian State Police between 2019 to 2021 by its type has increased annually. Routine motorcycle checks, services, and maintenance are essential to keep a motorcycle in good condition and more durable; therefore, buying spare parts is enlarged in line with the growth of public motorcycle ownership. The necessity of buying spare parts increases with the growth of public motorcycle ownership. Numerous stores in Ngawi offer motorcycle spare parts and check services for routine motorcycle maintenance. One of these stores is BM Motor. To develop an effective product-selling strategy, it is essential to forecast the daily turnover of the shop. To achieve this, the present research aims to analyze the daily turnover using Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM). These methods were applied to a time-series dataset, allowing for an in-depth examination of the patterns and trends in the shop's turnover. The research compares several hyperparameter tunings and scenarios to optimize the models that forecast daily turnover data at the store. The outcomes presented that the LSTM model achieved a lesser MAE score of 0.087, while the RNN model scored 0.092. These findings proved that the LSTM model achieved lower MAE than the RNN model, it means LSTM is more accurate than the RNN model.

Forecasting of GPU Prices Using Transformer Method Faisal Hadi, Risyad; Saadah, Siti; Adytia, Diditq
eProceedings of Engineering Vol. 10 No. 5 (2023): Oktober 2023
Publisher : eProceedings of Engineering

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Abstract— GPU or VGA (graphic processing unit) is a vital component of computers and laptops, used for tasks such as rendering videos, creating game environments, and compiling large amounts of code. The price of GPU/VGA has fluctuated significantly since the start of the COVID19 pandemic in 2020. This research aims to forecast future GPU prices using deep learning-based time series forecasting using the Transformer model. We use daily prices of NVIDIA RTX 3090 Founder Edition as a test case. We use historical GPU prices to forecast 8, 16, and 30 days. Moreover, we compare the results of the Transformer model with two other models, RNN and LSTM. We found that to forecast 30 days; the Transformer model gets a higher coefficient of correlation (CC) of 0.8743, a lower root mean squared error (RMSE) value of 34.68, and a lower mean absolute percentage error (MAPE) of 0.82 compared to the RNN and LSTM model. These results suggest that the Transformer model is an effective and efficient method for predicting GPU prices.Keywords— GPU, Transformer, Forecasting, Time Series Forecasting

Prediksi Harga Dogecoin Berdasarkan Sentimen dari Twitter Menggunakan LSTM Prasetyo Nugroho, Ecky; Saadah, Siti; Afianti, Farah
eProceedings of Engineering Vol. 10 No. 5 (2023): Oktober 2023
Publisher : eProceedings of Engineering

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Abstrak— Dogecoin adalah mata uang kripto yang diciptakan oleh Billy Markus dan Jackson Palmer, tetapi mereka membuat Dogecoin hanya untuk dibuat sebagai bahan candaan di dunia mata uang kripto. Tugas akhir ini menganalisis sentimen dan prediksi terhadap Doge dengan melakukan korelasi antara harga Doge terhadap data yang dikumpulkan dari media social Twitter mengenai Doge. Penelitian ini dilakukan menggunakan pendapat-pendapat yang disampaikan oleh pengguna jejaring sosial yang menggunakan bahasa Inggris. Metode yang digunakan adalah LSTM dengan mengacu pada penelitian-penelitian sebelumnya yang menunjukkan bahwa LSTM memberikan akurasi tertinggi. Data yang digunakan pada penelitian ini adalah harga doge dan tweet pada periode januari-april 2021. Menentukan korelasi antara doge dan tweet dilakukan dengan korelasi pearson dimana hasil korelasi tersebut menentukan korelasi positif, korelasi negatif dan tidak berkorelasi, setelah itu dilakukan prediksi harga doge close dengan LSTM. Harga Doge Close berkorelasi dengan sentimen, namun tidak kuat tidak juga lemah. Tidak ada peningkatan akurasi hasil prediksi dibandingkan pengujian pertama yang dimana pada pengujian pertama nilai RMSE sebesar 0,003 dan pengujian kedua nilai RMSE sebesar 0,008.Kata kunci— analisis sentimen, LSTM, prediksi, korelasi

Edukasi Media Untuk UMKM: Workshop Desain Konten Promosi Digital untuk UMKM Makanan Tradisional: Penelitian Supriadi, Supriadi; Khaeru Ahmadi , Raden; Saadah, Siti; Dewabrata , Bondan; Prio Eko Rahardjo , Rosnindar
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 3 (2026): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 3 (Januari 202
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i3.4895

The development of digital media has created significant opportunities for Micro, Small, and Medium Enterprises (MSMEs) to expand their product marketing reach. However, traditional food MSMEs in Sumenep Regency continue to face challenges in effectively utilizing digital media, particularly due to low media literacy, limited visual design skills, and insufficient understanding of digital promotional content strategies. This Community Service Program (Pengabdian kepada Masyarakat/PKM) aims to enhance the capacity of traditional food MSME actors in Sumenep through media literacy education and digital promotional content design workshops. The program employed a participatory-educative approach, including socialization, training sessions, hands-on practice in creating visual promotional content, discussions, and mentoring. The results indicate an improvement in participants’ understanding of the strategic role of digital media as a marketing tool, enhanced skills in producing more attractive and communicative visual content aligned with product characteristics, and a positive shift in attitudes toward viewing social media as a strategic business asset. Furthermore, the program strengthened participants’ confidence and creativity in promoting traditional food products based on local wisdom. Therefore, the integration of media literacy education and digital content design workshops proves to be an effective and sustainable assistance model in supporting the digital transformation of traditional food MSMEs in regional contexts.

Integration of Green Marketing and Digital Strategy on the Competitiveness of Cassava-Based SMEs in Sumenep Regency Ahmadi, Raden Khaeru; Saadah, Siti; Fitriyah, Eny; Susmiati, Evi
Majapahit Journal of Islamic Finance and Management Vol. 6 No. 1 (2026): Islamic Finance and Management
Publisher : Universitas KH. Abdul Chalim Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31538/mjifm.v6i1.754

Micro, Small, and Medium Enterprises (MSMEs) based on local products play a strategic role in regional economic development; however, they continue to face competitiveness challenges, particularly in rural areas. Increasing consumer awareness of environmental issues and the acceleration of digital transformation require MSMEs to adopt sustainable and adaptive marketing strategies. This study aims to examine the effect of green marketing and digital marketing strategies on the sustainable competitiveness of cassava-processing MSMEs in Banasarep Village, Sumenep Regency, and to develop a Smart Eco-MSME model as an integrative approach. This study employs a quantitative approach using Structural Equation Modeling–Partial Least Squares (SEM-PLS). Data were collected through a structured questionnaire with a five-point Likert scale administered to 30 cassava-processing MSMEs selected using purposive sampling. Data analysis involved outer model evaluation, inner model assessment, and hypothesis testing through bootstrapping procedures. The results indicate that green marketing has a positive and significant effect on the sustainable competitiveness of MSMEs. Digital marketing strategies also show a positive and significant effect, with a stronger influence than green marketing. Simultaneously, green marketing and digital marketing explain 67.2% of the variance in sustainable competitiveness. These findings suggest that integrating environmental values with digital technology utilization can create long-term competitive advantages for MSMEs. This study concludes that the Smart Eco-MSME model is effectively applicable to cassava-processing MSMEs in rural areas. Policy implications highlight the importance of local government support in enhancing digital literacy, promoting green marketing practices, and developing a sustainable MSME ecosystem based on local resources.

Integration of Green Marketing and Digital Strategy on the Competitiveness of Cassava-Based SMEs in Sumenep Regency Ahmadi, Raden Khaeru; Saadah, Siti; Fitriyah, Eny; Susmiati, Evi
Majapahit Journal of Islamic Finance and Management Vol. 6 No. 1 (2026): Islamic Finance and Management
Publisher : Universitas KH. Abdul Chalim Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31538/mjifm.v6i1.754

Micro, Small, and Medium Enterprises (MSMEs) based on local products play a strategic role in regional economic development; however, they continue to face competitiveness challenges, particularly in rural areas. Increasing consumer awareness of environmental issues and the acceleration of digital transformation require MSMEs to adopt sustainable and adaptive marketing strategies. This study aims to examine the effect of green marketing and digital marketing strategies on the sustainable competitiveness of cassava-processing MSMEs in Banasarep Village, Sumenep Regency, and to develop a Smart Eco-MSME model as an integrative approach. This study employs a quantitative approach using Structural Equation Modeling–Partial Least Squares (SEM-PLS). Data were collected through a structured questionnaire with a five-point Likert scale administered to 30 cassava-processing MSMEs selected using purposive sampling. Data analysis involved outer model evaluation, inner model assessment, and hypothesis testing through bootstrapping procedures. The results indicate that green marketing has a positive and significant effect on the sustainable competitiveness of MSMEs. Digital marketing strategies also show a positive and significant effect, with a stronger influence than green marketing. Simultaneously, green marketing and digital marketing explain 67.2% of the variance in sustainable competitiveness. These findings suggest that integrating environmental values with digital technology utilization can create long-term competitive advantages for MSMEs. This study concludes that the Smart Eco-MSME model is effectively applicable to cassava-processing MSMEs in rural areas. Policy implications highlight the importance of local government support in enhancing digital literacy, promoting green marketing practices, and developing a sustainable MSME ecosystem based on local resources.

Post-harvest seaweed quality support in Pagarbatu Village, Sumenep, using SWSolar Dryer technology to create competitive seaweed farmers Zuhri, Ach; Ahsan, Agung Firdausi; Saadah, Siti; Ghibran, Moh Iqbal; Aini, Anis Nur
IMPOWERMENT SOCIETY Vol 9 No 1 (2026): February 2026
Publisher : Institut Teknologi dan Bisnis Widya Gama Lumajang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30741/eps.v9i1.1735

Seaweed is a leading commodity in Sumenep Regency. However, post-harvest quality remains low due to traditional drying methods, which, in turn, affects selling prices and farmer welfare. This community service program aims to improve the quality and competitiveness of seaweed farmers in Pagarbatu Village by applying SW-Solar Dryer technology. Implementation methods include outreach, management and production training, SW-Solar Dryer application, mentoring, and ongoing evaluation with "Kelana" fishing group partners. The results showed that the SW-Solar Dryer can reduce drying time from 2–3 days to just 5–8 hours. It maintains product hygiene because the process is carried out in a closed room. Moisture content produced also meets industry standards. Furthermore, the mentoring program encouraged diversification of processed seaweed-based products. This increased farmers' income and reduced dependence on collectors. Thus, the application of SW-Solar Dryer technology has proven effective in improving post-harvest management, expanding business opportunities, and creating more competitive seaweed farmers.

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