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Wirdayanti
Universitas Tadulako
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Analisis Sentimen Terhadap Kinerja Awal Pemerintahan Menggunakan IndoBERT Dan SMOTE Pada Media Sosial X Ihalauw, Sahron Angelina; Trezandy Lapatta, Nouval; Wiria Nugraha, Deny; Wirdayanti; Ar Lamasitudju, Chairunnisa
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2957

Abstract

Social media platform X has become a key channel for expressing public opinion on political issues, including evaluating the early performance of the government. The first 100 days of an administration are a strategic period to assess policy direction and public perception. This study aims to apply and evaluate the IndoBERT model for sentiment analysis of Indonesian-language tweets discussing the 100-day performance of the Prabowo–Gibran administration, as well as to assess the impact of using the Synthetic Minority Oversampling Technique (SMOTE) to address data imbalance. A total of 15,027 tweets were collected through API crawling and processed through several stages: preprocessing, labeling using the InSet Lexicon, data splitting, and fine-tuning IndoBERT. Two scenarios were tested — without SMOTE and with SMOTE oversampling. The results show that both models achieved the same overall accuracy of 87%, but performance varied across sentiment classes. The model without SMOTE performed better in the positive class with 93% precision, whereas the SMOTE-applied model improved performance in the neutral class (F1-score increased from 70% to 71%; recall from 69% to 71%) and in the negative class (precision increased from 88% to 90%). Considering the balance across classes, the SMOTE-based model was selected as the final model and implemented into a Streamlit application for interactive sentiment analysis. This study expands the application of IndoBERT in the Indonesian political domain by combining the lexical InSet approach with SMOTE oversampling — a combination rarely applied in Indonesian political sentiment analysis. The findings highlight the importance of data balancing strategies in improving transformer-based model performance on imbalanced datasets. Future research is encouraged to explore alternative balancing methods, expand training data, and test other transformer variants to enhance accuracy and generalization.
Implementation of Long Short-Term Memory Algorithms on Cryptocurrency Price Prediction with High Accuracy on Volatile Assets Nursiana Zasqia, Andi Nirina; Laila, Rahmah; Trezandy Lapatta, Nouval; Yazdi Pusadan, Mohammad; Santi, Dessy; Wirdayanti
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2422

Abstract

Cryptocurrencies have emerged as one of the most popular digital assets, characterized by high volatility, which presents a significant challenge in forecasting their price movements accurately. This study aims to implement the Long Short-Term Memory (LSTM) algorithm to predict the prices of selected cryptocurrencies, including Bitcoin (BTC), Binance Coin (BNB), Ethereum (ETH), Dogecoin (DOGE), Solana (SOL), and Shiba Inu (SHIB). The LSTM model is trained using the Adam optimizer and employs early stopping to mitigate overfitting. Model performance is evaluated using Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and the coefficient of determination (R²). The results indicate that the LSTM model achieves strong predictive accuracy for relatively low-volatility assets such as Dogecoin and Solana, with R² scores of 0.9795 and 0.9523, respectively. In contrast, its performance declines when applied to highly volatile assets like Bitcoin and Binance Coin. The findings also suggest that LSTM performs best in short-to-medium-term forecasts (7 to 30 days), but shows limitations in long-term predictions. This study contributes to the field by demonstrating the applicability of LSTM in financial forecasting and highlighting its strengths and constraints across different volatility profiles. Practically, the findings can assist traders and financial analysts in making data-driven decisions by applying LSTM models for more reliable short-term predictions, while emphasizing the need to integrate external market factors to enhance long-term forecast accuracy.
Strategi Pemasaran dan Tantangan Penjualan di Era Digitalisasi : Studi Kasus UMKM Cemilan Keripik Tempe Kenzi di Jl. Danau Maninjau LK. IV Kelurahan Padang Merbau Kota Tebing Tinggi Aziti, Tria Meisya; Saragih, Linda Hertaty; Wirdayanti, Wirdayanti
Community Service Progress Vol. 4 No. 2 (2025): Community Service Progress Edisi Desember 2025
Publisher : STIE Bina Karya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70021/csp.v4i2.277

Abstract

This study aims to analyze and propose effective digital marketing strategies for tempeh producers, who often still rely on traditional marketing methods, and to help MSMEs adapt to changing consumer behavior in the digital era. Tempeh product marketing strategies in the digital era generally discuss the importance of adopting digital technology by tempeh Micro, Small, and Medium Enterprises (MSMEs) to expand market reach and increase competitiveness. It also identifies various sales strategies and challenges they face.
Pengenalan Dan Pelatihan Canva Sebagai Media Ajar Inovatif Bagi Guru Untuk Meningkatkan Mutu Pendidikan Di Smp Negeri 1 Lore Utara Wirdayanti; Santi, Dessy; Ardiansyah, Rizka; Laila, Rahma; Akbar, Muhammad; Syafa'at, Fizar
BERNAS: Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 2 (2026)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/jb.v7i2.16763

Abstract

Program Pengenalan dan Pelatihan Canva sebagai Media Ajar Inovatif bagi guru di SMP Negeri 1 Lore Utaradilaksanakan untuk menjawab tantangan keterbatasan guru dalam mengembangkan media ajar digital yangkreatif dan interaktif, meskipun sebagian besar guru sudah memanfaatkan komputer dan internet sebatasmencari bahan ajar. Target utama program ini adalah meningkatkan literasi digital, keterampilan praktispembuatan media ajar berbasis Canva, motivasi guru dalam menggunakan teknologi pembelajaran, sertapeningkatan kualitas pengajaran melalui media digital yang menarik dan relevan dengan kurikulum. Capaianyang diraih meliputi peningkatan pemahaman guru tentang pemanfaatan teknologi, kemampuan membuatpresentasi, poster, infografis, hingga video pembelajaran sederhana, serta tumbuhnya kepercayaan diri guruuntuk mengintegrasikan Canva dalam proses belajar-mengajar. Metode pelaksanaan terdiri atas tigatahapan, yaitu: (1) tahap persiapan melalui survei awal (pre-test) yang menunjukkan mayoritas guru (74%)telah mengenal Canva sehingga pelatihan difokuskan pada pendalaman fitur; (2) tahap pelatihan denganmetode ceramah, diskusi, demonstrasi, praktik langsung, studi kasus, dan presentasi karya; serta (3) tahapevaluasi melalui post-test, pendampingan, dan supervisi implementasi di kelas. Hasil kegiatan menunjukkanbahwa guru sangat antusias, terbukti dari keterlibatan aktif selama pelatihan serta hasil survei akhir yangmenunjukkan 58% responden sangat puas dan 29% puas terhadap program. Pembahasan menunjukkanbahwa pelatihan ini efektif meningkatkan kompetensi digital guru, memotivasi penggunaan Canva secarakonsisten dalam pembelajaran, serta berdampak positif terhadap keterlibatan siswa di kelas. Dengandemikian, kegiatan ini berhasil mendorong peningkatan mutu pembelajaran melalui penguatan kompetensiTIK bagi guru di SMP Negeri 1 Lore Utara.
The Relationship Between Early Breastfeeding Initiation (EBI) and Bonding Attachment Between Mother and Newborn at the Bineh Krueng Health Center, Southwest Aceh Regency, in 2026 Eka Ilhamni; Fera Sawita; Wirdayanti; Asmaul Husna; Suzanna Fitri
Journal Public Health and Clinical Science Vol. 2 No. 1 (2026): Journal Public Health and Clinical Science
Publisher : Athallah Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64845/clinergy.v2i1.323

Abstract

Early Breastfeeding Initiation (EBI) is an important early intervention in forming an emotional bond between mother and baby through skin-to-skin contact in the first hour of life. The implementation of EBI can increase bonding attachment which plays a role in children's emotional and psychological development. However, not all mothers carry out EBI optimally so that it can affect the quality of the mother-baby relationship. To determine the relationship between Early Breastfeeding Initiation (EBI) and bonding attachment between mother and newborn at the Bineh Krueng Health Center, Southwest Aceh Regency. This study is a quantitative research with an observational analytical design using a cross sectional approach. The population in this study is all mothers who give birth to newborns as many as 60 people. The sampling technique used the Slovin formula so that a sample of 60 respondents was obtained. Data analysis using the Chi-Square test. The results showed that most of the mothers carried out EBI as many as 41 respondents (68.3%) and had good bonding attachment as many as 39 respondents (65%). The results of the Chi-Square test showed a value of p = 0.002 (p < 0.05) which means that there is a significant relationship between EBI and bonding attachment between mother and newborn. There is a significant relationship between Early Breastfeeding Initiation (EBI) and maternal and newborn attachment bonding. It is hoped that health workers can improve education and assistance to mothers and families in the implementation of EBI so that it can be carried out optimally to support the formation of emotional bonds between mothers and babies.
Aplikasi Android Untuk Reservasi Lapangan Futsal Menggunakan Metode First In First Out (FIFO) Jonathan Zebina Laala; Chairunnisa Ar. Lamasitudju; Ryfial Azhar; Rahmah Laila; Wirdayanti; Miftah
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4104

Abstract

Technology facilitates the process of futsal field rental, such as payment queueing and real-time monitoring. An Android application has been developed to manage payment queueing and futsal field rental at Novega Futsal Court, addressing inefficiencies of traditional methods that decrease customer satisfaction. Utilizing Rapid Application Development (RAD) and First In First Out (FIFO) method, this application designed expedite and enhance the queueing process. Data was collected through direct interaction with respondents and on-site observation, while its development involved the use of React Native and Node.js. Testing results indicate the application functions as expected, enabling users to easily rent and pay, and assisting managers in efficiently organizing queues. This application enhances service efficiency and customer satisfaction, making a positive contribution to technology-based futsal management.
Co-Authors ., Rezki A. Masse, Burhannudin Abul Azis, Muhammad Dzaky Aisyah Warsid Amriana Amriana Amriana Amriana Andi Hendra Anita Ahmad Kasim ARDIANSYAH ARDIANSYAH Ardiansyah, R Asmaul Husna Asriani Asriani, Asriani Bakri Budiman, Wahyu Deni Irawan, Deni Deni Luvi Jayanto Deny Wiria Nugraha Dessy Santi Dwi Shinta Angreni Eka Ilhamni Fera Sawita Hajra Rasmita Ngemba Ihalauw, Sahron Angelina Indah Safitri Jonathan Zebina Laala Kade Dwi Arsana, I Gusti Ngurah Agung Laila, Rahma Lamasitudju, Chairunnisa Masykur, M Miftah Miftah Miftah, Miftah Mohammad Yazdi Pusadan Mufthi, Mufthi Muhammad Akbar MUHAMMAD BAKRI Nadhar, Muhammad Ngurah, Gusti Nirwan Nirwan Nouval Trezandy Lapatta Noviantika, Noviantika Nursalim, Moh. Agung Nursiana Zasqia, Andi Nirina Qofifa, Sitti Nurlaili Rafika Sari Rahmah Laila Rahmah Laila Reinaldy Mansa, Jeremy Rinianty, Rinianty Rizka Ardiansyah Rizqa Raaiqa Bintana Ryfial Azhar Sabarudin Saputra Saragih, Linda Hertaty Semmagga, Nuraeni Septiano Anggun Pratama Sri Khaerawati Nur Suryani Putri, Fadiah Suzanna Fitri Syafa'at, Fizar Syahrullah Syahrullah Syahrullah Syaiful Hendra Tria Meisya Aziti Wahyu Setiawan Wongkar, Noel Marcell Jonathan Yanti, Alda Yuri Yudhaswana Joefrie Yusuf Anshori