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All Journal Abjadia, International Journal of Education Jurnal Pengabdian Masyarakat Bhinneka VARIANSI: Journal of Statistics and Its Application on Teaching and Research
Syalsabila, Annisa
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Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Mathematics Public Health Other

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Peningkatan Literasi Data Guru melalui Pelatihan Penyajian Data di SMAN 7 Takalar Mar'ah, Zakiyah; Aidid, Muhammad Kasim; Muthahharah, Isma; Syalsabila, Annisa
Jurnal Pengabdian Masyarakat Bhinneka Vol. 4 No. 1 (2025): Bulan September
Publisher : Bhinneka Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58266/jpmb.v4i1.370

Abstract

Tujuan kegiatan ini adalah untuk memberikan pemahaman dan keterampilan kepada guru SMAN 7 Takalar agar mereka dapat lebih efisien dalam mengelola data hasil belajar siswa, merencanakan pembelajaran, serta membuat laporan dengan menggunakan Microsoft Excel yang sudah tersedia. Microsoft Excel merupakan salah satu perangkat lunak yang sangat penting dalam pengolahan dan penyajian data. Namun, masih banyak siswa SMA dan tenaga kependidikan, yang mengalami kesulitan dalam menggunakan Excel. Sosialisasi dalam kegiatan ini mencakup identifikasi kebutuhan guru, penyuluhan dan diskusi serta penyebaran informasi. Selama pelatihan, para guru diberikan materi secara langsung tentang materi dasar Microsoft Excel, membuat grafik dan diagram serta melakukan simulasi pengolahan data analisis ulangan harian siswa. Kesimpulan kegiatan ini adalah 1) telah memberikan kontribusi yang signifikan dalam peningkatan literasi data melalui pengenalan penyajian data, 2) peserta mampu mengolah dan menyajikan data ujian siswa secara mandiri, 3) penyajian data yang baik sangat penting untuk membantu dalam memahami informasi kompleks serta pada pengambilan keputusan berbasis data.
Identifying Motivational Factors in Nahwu Courses Using Principal Component Analysis (Pca): A Study of Arabic Language Education Students Khairani, Annisa Raina; Fikri, Shofil; Syaqifah, Iklil; Juliansyah, Iqbal; Syalsabila, Annisa
Abjadia : International Journal of Education Vol 11, No 1 (2026): Abjadia
Publisher : Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/abj.v11i1.36003

Abstract

The challenges faced by students in studying Nahwu, an essential component of the Arabic language, often relate to the complexity of its rules, making it feel difficult and diminishing learning motivation. This study aims to analyze the factors influencing students' learning motivation in Nahwu courses at the university level, offering solutions through a deeper understanding of intrinsic motivation, extrinsic motivation, and amotivation. The research employed a descriptive quantitative method with factor analysis using Principal Component Analysis (PCA). Data were collected over a one-month period via questionnaires from 46 fifth-semester students (cohort 2020) in the Arabic Language Education Program at UIN Datokarama Palu. The motivation indicators employed in this study were based on the Academic Motivation Scale (AMS) developed by Robert J. Vallerand, which comprises seven distinct indicators. The findings reveal two main factors affecting learning motivation: the Self-Regulation Factor, which is associated with positive motivation, and the Helplessness Factor, reflecting feelings of inability. These findings are expected to provide insights for educators in creating effective teaching methods to enhance students' motivation and learning outcomes in Nahwu courses.
Trend, Cycle, and Forecasting Analysis of Monthly Inflation in Indonesia Using the Hodrick–Prescott Filter and ARIMA Ikhwana, Nur; Syalsabila, Annisa; Mangiri, Nalto Batty
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 8 No. 1 (2026)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm526

Abstract

This study aims to analyze the structure of inflation and forecast monthly inflation in Indonesia using a time series approach. The method used is the Hodrick–Prescott Filter to decompose data into trend and cycle components, and the ARIMA model to forecast inflation. The data used is monthly inflation data for the period 2010–2025. The decomposition results show that inflation has a relatively stable long-term trend with short-term fluctuations reflecting the presence of economic shocks. Based on model identification, the best model is ARIMA(2,0,1)(1,0,1)[12] which is able to capture past influences, seasonal components, and short-term shocks. The evaluation results show that the model meets the white noise assumption and is suitable for use in forecasting. The forecasting results show that inflation tends to be stable with a moderate increasing tendency, although uncertainty increases over longer periods. This study shows that the combination of structural analysis and time series modeling provides a more comprehensive understanding of inflation dynamics and produces relevant predictions to support decision making.
Co-Authors Aidid, Muhammad Kasim Ikhwana, Nur Juliansyah, Iqbal Khairani, Annisa Raina Mangiri, Nalto Batty Mar'ah, Zakiyah Muthahharah, Isma Shofil Fikri Syaqifah, Iklil