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All Journal Jurnal Abdimas Ilmiah Citra Bakti (JAICB) ABSYARA: Jurnal Pengabdian Pada Masyarakat SISFOTENIKA
Arwansyah
Undipa Makassar
Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Physics Social Sciences Other

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Pelatihan teknologi informasi pada kantor kelurahan Barrang Caddi Kepulauan Sangkarrang Nurul Aini; Erfan Hasmin; Heriadi Heriadi; Indra Samsie; Sitti Aisa; Muhammad Furqan Rasyid; Sriwahyuningsi Piu; Sunardi Sunardi; Sitti Harlina; Novita Sambo Layuk; Andi Asvin Mahersatillah Suradi; Arwansyah Arwansyah
ABSYARA: Jurnal Pengabdian Pada Masayarakat Vol 4 No 1 (2023): ABSYARA: Jurnal Pengabdian Pada Masyarakat
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/ab.v4i1.15906

Abstract

As a public service provider, the sub-district office plays a crucial role in the issuance of referral letters and certificates. In this era of digitalization, effective and efficient administrative services are demanded, necessitating the improvement of staff knowledge and skills in information technology literacy. Hence, this community engagement activity aims to enhance the quality of administrative services by empowering human resources to operate computers and office applications at the Barrang Caddi Sub-district Office. The training program spans 3 days, encompassing Microsoft Word and Excel tutorials, as well as E-Mail usage. Enthusiasm was evident among the participants, which consisted of 7 sub-district office staff and 4 residents, as they actively engaged in the activities and completed the assigned tasks. The evaluation results demonstrate that the participants have comprehended and effectively applied the knowledge imparted during the training. The training materials have assisted the participants in optimizing their information technology knowledge and skills, such as efficiently managing administrative documents using Microsoft Office, operating E-Mail, and understanding the essential tools in Excel. This training validates the significance of information technology literacy efforts in sub-district office settings, particularly in areas with limited access to information. It is hoped that this community engagement initiative will continue and provide sustained benefits in enhancing administrative services and human resources quality at the Barrang Caddi Sub-district Office
PEMANFAATAN MICROSOFT OFFICE EXCEL DALAM PENINGKATAN TATA KELOLA NILAI GURU SMA NEGERI 6 BARRU Sitti Harlina; Magfirah; Nurul Aini; Usman; Novita Sambo Layuk; Sitti Aisa; Faizal; Sadly Syamsuddin; Heriadi; Arwansyah; Nurdiansah; Sunardi; Madyana Patasik; Khaddafi; Akbar Bahtiar
Jurnal Abdimas Ilmiah Citra Bakti Vol. 5 No. 2 (2024)
Publisher : STKIP Citra Bakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38048/jailcb.v5i2.3277

Abstract

Kegiatan pengabdian masyarakat melalui pelatihan microsoft office excel kepada guru SMA Negeri 6 Barru mempunyai tujuan, peningkatan keterampilan, integritas teknologi dalam pengajaran, pengembangan materi pembelajaran yang relevan dan peningkatan efisiensi administrasi bagi guru yang dapat mencakup beberapa sasaran aspek kunci untuk, peningkatan kompetensi, dan keterampilan guru dalam memanfaatkan teknologi dan platform microsoft office excel dalam proses pengajaran dan manajemen data untuk analisis dan pelaporan nilai yang lebih baik, menciptakan lingkungan pembelajaran yang lebih adaptif dan responsif terhadap kebutuhan siswa.Metode yang digunakan yaitu pelatihan secara tatap muka di kelas, dengan pemberian materi dan latihan untuk mendapatkan hasil yang lebih maksimal. Hasil pret test 30 % pengenalan, 30 % rumus, 10 % fungsi, dan 10 % data dan grafik. Setelah pelatihan hasilnya menunjukkan peningkatan yaitu 85 % pengenalan, 80 rumus, 75 % fungsi, 85% data dan grafik tentang pemahaman dari materi microsoft office excel. Melalui kolaborasi dan pertukaran pengalaman dapat membangun kolaborasi antara guru-guru SMA Negeri 6 Barru dalam menciptakan lingkungan belajar yang inovatif.
2Deep Model Prediksi Berbasis Weighting Average Untuk Time Series Data Arwansyah; Cucut Susanto; Nurdiansah
SISFOTENIKA Vol. 14 No. 2 (2024): SISFOTENIKA
Publisher : STMIK PONTIANAK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30700/sisfotenika.v14i2.462

Abstract

In time series data analysis, the need for accurate and efficient predictive models is becoming increasingly urgent as data complexity rises. This study proposes the 2Deep Model, a hybrid approach that combines Bidirectional Long Short-Term Memory (Bi-LSTM) and Stacked LSTM, utilizing the Weighting Average technique to optimize predictions. This method was chosen for its potential in handling long-term dependencies and temporal complexity in data. Experiments were conducted on five datasets: ETTh1, ETTh2, ETTm1, ETTm2, and AQI Shanghai. The results show that the proposed model achieves low Mean Squared Error (MSE) and Mean Absolute Error (MAE) values on the first four datasets, with an average MSE of 0.0289 and an MAE of 0.0971, along with a relatively high R-squared (R²) value. However, for the AQI Shanghai dataset, the model's performance declined, with higher MSE and MAE values and a lower R². These findings indicate that the 2Deep Model holds significant potential for time series data prediction applications, although there is room for improvement when dealing with more diverse datasets. Future research suggestions include further model optimization and exploring other hybrid methods to enhance model generalization.
Co-Authors Akbar Bahtiar Andi Asvin Mahersatillah Suradi Cucut Susanto Erfan Hasmin Faizal Faizal Harlina, Sitti Heriadi Heriadi Madyana Patasik Magfirah Muh. Khaddafi Muhammad Furqan Rasyid Novita Sambo Layuk Nurdiansah Nurul Aini Sadly Syamsuddin Samsie, Indra Sitti Aisa Sriwahyuningsi Piu Sunardi Sunardi Usman