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All Journal Statistika Abdi: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Statistika dan Aplikasinya Mitra Teras: Jurnal Terapan Pengabdian Masyarakat JMT (Jurnal Matematika dan Terapan) BAKTI : Jurnal Pengabdian Kepada Masyarakat
Widyanti Rahayu
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Medicine & Pharmacology Public Health Social Sciences Other

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ANALYSIS OF INDONESIAN STUDENTS' READING LITERACY USING THE SMOOTHLY CLIPPED ABSOLUTE DEVIATION (SCAD) PENALTY Santi, Vera Maya; Riyantobi, Ariq Muammar; Widyanti Rahayu
Jurnal Statistika dan Aplikasinya Vol. 9 No. 1 (2025): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.09111

Abstract

Reading literacy significantly impacts a country's educational level, making it crucial to further investigate into this issue. Identifying factors that influence students' reading literacy, particularly in Indonesia, is a key area of exploration. PISA survey data, conducted every three years, is relevant for researching student proficiency. Each survey period focuses on one of three main topics: science literacy, mathematics literacy, and reading literacy. The 2018 PISA survey data is suitable for studying students’ reading literacy, as the main topic that year was reading literacy. However, PISA survey data includes many strongly correlated independent variables, potentially violating the multicollinearity assumption. To address this, regression analysis with a penalty function is used for variable selection. The SCAD (Smoothly Clipped Absolute Deviation) penalty function has proven effective in previous studies on PISA data. The model using the SCAD penalty function yielded excellent results, indicated by an Adjusted R2 value of 0.967. Based on this model, three main factors influence students' reading literacy in Indonesia: learning facilities, general knowledge, and students' self-confidence.
Pelatihan Konsep Dasar Statistika dan Penyajian Data untuk Meningkatkan Literasi Statistika Siswa SMP di Kabupaten Sukabumi Ladayya, Faroh; Handayani , Dian; Rahayu, Widyanti; Meganingtyas, Devi Eka Wardani; Kemalasari, Erin Naudy; Rahmadani , Zahra Ayu
Mitra Teras: Jurnal Terapan Pengabdian Masyarakat Vol. 3 No. 2 (2024): Mitra Teras: Jurnal Terapan Pengabdian Masyarakat, Volume 3 Nomor 2, Desember 2
Publisher : MJI Publisher by PT Mitra Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58797/teras.0302.06

Abstract

Statistika dan peluang merupakan salah satu materi yang dipelajari dalam pelajaran matematika pada jenjang Sekolah Menengah Pertama. Pentingnya pengetahuan tentang statistika menjadikannya sebagai salah satu materi pada kurikulum. Siswa diharapkan mampu mengolah, menginterpretasi, dan menyajikan data hasil pengamatan. Berdasarkan nilai assesmen nasional siswa nasional didapatkan hasil bahwa persentase siswa yang memenuhi kompetensi minimum pada literasi numerik hanya 32,29% , walaupun memenuhi target nasional namun angka tersebut masih sangat kecil. Diperlukan inovasi pada penyampaian materi matematika khususnya statistika pada jenjang SMP. Penggunaan alat peraga statistika dapat mempermudah siswa dalam memahami statistika terutama dalam penyajian data. Solusi dari permasalahan tersebut adalah menggunakan alat peraga “StatTools” guna meningkatkan kemampuan literasi statistika siswa SMP di Kabupaten Sukabumi. Pelatihan ini diselenggarakan dengan metode ceramah, demonstrasi, dan praktek. Guna mengukur keefektifan dari pelatihan, diberikan kuesioner sebelum dan sesudah pelatihan. Berdasarkan analisis yang dilakukan didapatkan hasil kuesioner setelah pelatihan yang nilainya lebih tinggi dari pada sebelum pelatihan. Peserta merasa mendapatkan pengetahuan baru, memahami materi dengan baik, dan termotivasi untuk pembelajaran lanjutan.
Penentuan Strategi Bersaing Terbaik pada E-Commerce Menggunakan Metode AHP dan Game Theory Aulia Medangara Hakim; Yudi Mahatma; Widyanti Rahayu
JMT (Jurnal Matematika dan Terapan) Vol. 6 No. 1 (2024): JMT (Jurnal Matematika dan Terapan)
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Science, Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/jmt.6.1.2

Abstract

Based on the iPrice.co.id website, there are five e-commerce sites in Indonesia with the highest number of visitors. This is caused by the competitive strategy implemented by each e-commerce in order to win or maintain competition with consideration of the most attractive strategy for potential customers. The purpose of this study is to determine the best competitive strategy that needs to be implemented by e-commerce using game theory and consumer evaluation of e-commerce and supporting variables using the AHP (Analytical Hierarchy Process) method. The sample of this research is Jakarta citizens who are e-commerce users. The results of the research on the AHP method obtained e-commerce ranking results with the highest priority ranking to the lowest, namely Tokopedia, Shopee, Lazada, Blibli and Bukalapak. The variables that consumers pay attention to when making purchases on e-commerce from the highest priority to the lowest, namely Security, Trust, Free Shipping, Lots of Promos, Price, Product Quality, Payment Methods, Web Appearance, Product Brands and Product Diversity, where the 6 variables with the highest priority are then selected and these variables are used to determine the best competitive strategy using the game theory method. The results from game theory show that for Tokopedia e-commerce it is necessary to use a Product Quality strategy, Flood of Promos, and Trust, for Shopee namely Free Shipping, Lots of Promos and Security, for Lazada namely Product Quality, Free Shipping, Lots of Promos, and Security, for Bukalapak namely Product Quality, Price, Free Shipping, Lots of Promos, Trust, and Security, for Blibli namely Price, Free Shipping, Lots of Promos and Security.
PERFORMANCE EVALUATION OF WORD EMBEDDING TECHNIQUES IN TWITTER SENTIMENT ANALYSIS USING LSTM Ladayya, Faroh; Rahayu, Widyanti; Rohimah, Siti Rohmah; Saputra, Ferdiansyah Rizki; Maulana, Thoriq Akbar; Madinah, Najwa Nur
Jurnal Statistika dan Aplikasinya Vol. 9 No. 2 (2025): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.09206

Abstract

Opinions expressed on social media can be used as feedback on a product, both goods and services. The sentiment analysis was utilized for analyzing opinions given by the public via social media. The sentiment contained in an opinion can be positive, negative, or neutral. This study aims to compare the performance of three word embedding techniques—Word2Vec, GloVe, and FastText—when combined with a Long Short-Term Memory (LSTM) model for sentiment classification of Indonesian Twitter data. LSTM was selected due to its ability to model sequential text data and capture long-term contextual dependencies that are often present in natural language. To enable sentiment classification using LSTM, textual data from social media were transformed into numerical vectors. Thus, the word embedding technique is used to convert text into a vector. The vector that had been obtained will be used as input for LSTM. All embeddings were evaluated under the same preprocessing pipeline and LSTM architecture to ensure a fair comparison. Model performance was assessed using accuracy, precision, recall, F1-score, and ROC/AUC metrics. The results indicate that the LSTM model effectively captures sentiment patterns in Indonesian tweets, with Word2Vec achieving the best overall performance, followed by GloVe and FastText. These findings suggest that domain-adapted word embeddings remain highly effective for sentiment analysis in Indonesian social media contexts.
FORECASTING THE PRICE OF CURLY RED CHILI PEPPERS IN EAST JAVA PROVINCE USING ARIMA MODEL WITH ITERATIVE OUTLIER DETECTION PROCEDURE Erdien, Fareka; Rahayu, Widyanti; Sumargo, Bagus; Wulansari, Ika Yuni; Ali, Didiq Rosadi
Jurnal Statistika dan Aplikasinya Vol. 9 No. 2 (2025): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.09208

Abstract

Curly red chili is one of the vegetables with high economic value because it plays a role in supporting the food industry and meeting domestic needs. Fluctuations in the price of curly red chili peppers can change at any time, requiring forecasting to prevent losses for economic actors. This research aims to get the best model for forecasting and determine the accuracy of forecasting the price of curly red chili. The Autoregressive Integrated Moving Average (ARIMA) model is one method that can be used for forecasting with limitations requiring data that must be stationary. Outliers in the ARIMA model affect the autocorrelation structure of a time series so that the estimated values of the Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) become biased so that forecasting with the ARIMA model is less accurate and requires handling outliers in the form of outlier detection, one of which is an iterative procedure. From this study, it was found that the ARIMA(0,2,3) model with outlier detection was the best model for forecasting. Forecasting tends to show a downward trend with an accuracy level of MAPE value of 4.612, which means that the model is very good for forecasting.
Co-Authors Ali, Didiq Rosadi Ana Nur Islamiyah Aulia Medangara Hakim Bagus Sumargo Bagus Sumargo, Bagus Bayu Wibisono Daisy Salsabilah Kusuma Dania Siregar Devi Eka Wardani Meganingtyas Dian Handayani Erdien, Fareka Erin Naudy Kemalasari Eti Dwi Wiraningsih Faroh Ladayya Handayani , Dian Indiyah, Fariani Hermin Kemalasari, Erin Naudy Ketrin Natasya Stefany Kirana, Siti Julpia Ladayya, Faroh Madinah, Najwa Nur Maulana, Thoriq Akbar Meganingtyas, Devi Eka Wardani Mohd Syafrizal Muhammad Rafli Mulyono Nazhiifah, Nisriina Rahmadani , Zahra Ayu Ria Arafiyah Riyantobi, Ariq Muammar Rohimah, Siti Rohmah Saputra, Ferdiansyah Rizki Siregar, Dania Siti Rohmah Rohimah SUYONO Suyono Suyono Suyono Suyono Tri Murdiyanto Vera Maya Santi Wardana, Bintang Mahesa Wulansari, Ika Yuni Yohana Enggar Setyarini Yudi Mahatma Zahra Ayu Rahmadani Zahrah Hashifah