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All Journal Jurnal Riset Kimia JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Knowbase : International Journal of Knowledge in Database SAINSTEK Jurnal Informatika Ekonomi Bisnis
Widya Wahyuni
Fakultas Ilmu Komunikasi
Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering

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PEMANFAATAN ABU KULIT KAKAO UNTUK PEMBUATAN BATU BATA -, Mulyazmi; Praputri, Erti; -, Zulfiandriana; Wahyuni, Widya
Jurnal Riset Kimia Vol 9, No 1 (2015): September
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jrk.v9i1.254

Abstract

Brick is one of building materials derived from clay. The manufacturing process is with or without the use of substances mixing with the process of combustion at high temperatures. One of the mixing substances is derived from the rind cacao ash and its function is as an adhesive on the bricks.The purpose of this research is to understand the characteristics of brick as effect of cocoa rind as the value of compressive strength, porosity, water absorption and weight of a brick. The main materials of brick production are clays and trass ground which are mixed homogeneous with ratio 1 : 2 by varying cocoa rind ash additional by 5%, 10%, and 15%. The result is the compressive strength of the bricks using rind cocoa ash is 392.2 kg/cm3 higher value than traditional brick is 56.1 kg/cm3.
Analisis Sentimen terhadap Opini Feminisme Menggunakan Metode Naive Bayes Wahyuni, Widya
Jurnal Informatika Ekonomi Bisnis Vol. 4, No. 4 (December 2022)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (410.648 KB) | DOI: 10.37034/infeb.v4i4.162

Abstract

The perspective of the development of feminism centered on women around the world who wants to be free from pressure, oppression and inequality from men, continues to this day. Various public opinions about feminism are now contained in various social media. Long debates about criticism and support for feminism in equalizing women's position both in terms of intellect, and the role of women in making decisions. This research was conducted with the aim of looking at public sentiment based on opinions circulating on social media. Hashtags or hash tags related to feminism from social media are the main data that will be used to analyze public opinion sentiment about feminism and 600 data are obtained about feminism. The data obtained were separated into positive, negative and neutral opinions for analysis using Naïve Bayes (NB). The results of using the Naïve Bayes method obtained a recall value of 84%, precision 94% and Fi-Score of 86% with an accuracy of 88%. Through this research, the results of classification using the nave Bayes method in analyzing sentiment against feminist opinions have good performance.
Implementation of the Support Vector Machine Method for Sentiment Analysis Using Twitter Data Wahyuni, Widya
Knowbase : International Journal of Knowledge in Database Vol. 2 No. 2 (2022): December 2022
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v2i2.6019

Abstract

The development of feminism, which is centered on women all over the world who want to be free of male pressure, oppression, and inequality, has continued to the present day. Various public opinions about feminism are now being expressed on various social media platforms. There has been a long debate about feminism's critics and supporters in terms of equalizing women's intellectual and the role of women in making decisions. Not only that, but the desire to end acts of violence and injustice against women is a form of feminism that is often taken for granted, even in the legal realm. The purpose of this study was to examine public sentiment based on opinions shared on social media. Hashtags related to feminism from social media are the main data that will be used to analyze public opinion sentiments about feminism. In this study, 500 tweets were used, and the data was later separated into positive, negative, and neutral opinions before being analyzed using the Support Vector Machine (SVM) method. The results of this study obtained an accuracy of 72%, indicating that the use of SVM to perform sentiment analysis on Twitter data is quite good.
Perancangan Sistem Sms Gateway Untuk Informasi Pada Sma N 1 Pantai Cermin Kabupaten Solok Dengan Menggunakan Bahasa Pemrograman Php Dan Database Mysql Ismalia, Welly; Oktavia, Eva; Wahyuni, Widya
Jurnal Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence) Vol 4 No 3 (2024): Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence)
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakaai.v4i3.888

Abstract

Perkembangan teknologi informasi terus berkembang dan ditandai dengan banyaknya penemuan teknologi inovatif baru dari perusahaan-perusahaan besar di dunia pendidikan. Sebagai salah satu sekolah berstandar nasional menuju internasional, SMA N 1 Pantai Cermin harus mampu meningkatkan kualitas pendidikan menjadi lebih baik, terutama dalam hal informasi mengenai absensi dan komite. Siswa atau orang tua harus datang langsung ke guru mata pelajaran dan wali kelas untuk mendapatkan informasi tersebut. Oleh karena itu, sistem informasi gateway dirancang menggunakan pemrograman PHP dan database MySQL agar dapat menyediakan informasi mengenai absensi dan komite dengan cepat, tepat, dan akurat. Sistem ini dapat diakses dari mana saja selama terhubung dengan seluruh komponen, seperti ponsel atau modem GSM yang terkoneksi dengan PC dan didukung oleh perangkat lunak Gammu dalam proses komunikasinya.
Pengaruh Penambahan Bestmittel Sebanyak 0,4% dan Pengurangan Air 10% Terhadap Kuat Tekan Beton Novan, Andre; Ermiyati; Morena, Yenita; ‘Audah, Safridatul; Wahyuni, Widya; Gussyafri, Haji; Fakhri
SAINSTEK Vol. 13 No. 1 (2025)
Publisher : Sekolah Tinggi Teknologi Pekanbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35583/js.v13i1.310

Abstract

Salah satu aditif pada beton adalah Bestmittel dimana termasuk bahan tambah golongan type E (water reducing and accelerating admixture) yang berfungsi mempercepat pengerasan, mengurangi pemakaian air dan meningkatkan workability. Tujuan penelitian ini untuk mengetahui pengaruh Bestmittel terhadap kuat tekan beton dan mengetahui persentase kenaikan kuat tekan beton normal terhadap kuat tekan beton Bestmittel dengan nilai koefisien menggunakan Peraturan Beton Indonesia (PBI 1971). Benda uji berbentuk silinder dan jumlah 30 buah, variasi umur pengujian beton yaitu 3 hari, 7 hari, 14 hari, 21 hari, dan 28 hari. Variasi dosis penambahan Bestmittel yang digunakan 0,4% dari jumlah semen, serta pengurangan jumlah air 10%. Hasil pengujian kuat tekan beton normal pada umur 28 hari sebesar 25,653 MPa dan kuat tekan beton Bestmittel sebesar 29,615 MPa. Persentase kuat tekan beton Bestmittel umur 14 hari sudah mencapai sebesar 96%. Berdasarkan nilai Koefesian PBI 1971 bahwa kuat tekan beton mencapai 100% jika umur beton 28 hari, sedangkan Beton menggunakan bahan tambah Bestmittel pada umur 21 hari dan 28 hari berturut-turut 105% dan 115%. Hal ini membuktikan bahwa dengan penambahan aditif Bestmittel 0,4% dan pengurangan jumlah air 10% meningkatkan kuat tekan beton, dan mempercepat proses pengerasan beton di umur muda dengan arti bahwa Bestmittel memiliki pengaruh yang signifikan terhadap kuat tekan beton.
Implementation of BERTopic for Topic Modeling Analysis of the Free Nutritious Meal Program Based on YouTube Comments Wahyuni, Widya; Lestari, Tri Putri; Apriliana, Milla; Gumelta, Riyang
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9754

Abstract

The Free Nutritious Meal Program (Makan Bergizi Gratis), represents a significant national effort aimed at mitigating stunting rates in Indonesia, having commenced its operations in January 2025. As the program progressed, public sentiment towards it evolved, resulting in a diverse array of opinions that were extensively debated on various social media platforms, notably YouTube. This study was conducted with the objective of examining the perceptions of the public regarding Makan Bergizi Gratis through a topic modeling methodology employing the BERTopic approach, which analyzed 19,843 comments from YouTube. The analytical framework entailed several stages, including data preprocessing, sentence-based embedding representation, dimensionality reduction via UMAP, clustering through HDBSCAN, and topic interpretation grounded in c-TF-IDF. The findings indicate that public commentary is categorizable into ten primary themes, encompassing issues such as the involvement of political figures, concerns over budget transparency, the program's educational benefits, and the need for equitable access in underserved regions. Evaluation results show that BERTopic outperformed the traditional LDA model, with a coherence score of 0.46 compared to 0.39 and topic diversity of 76 percent compared to 71 percent. This analysis reveals that public perception of Makan Bergizi Gratis is multifaceted, shaped by social experience, political context, and economic expectations. These insights may serve as a valuable foundation for a more comprehensive understanding of public opinion, thereby supporting more targeted and responsive policy development.
Co-Authors -, Mulyazmi -, Zulfiandriana Apriliana, Milla Ermiyati Eva Oktavia, Eva fakhri Gumelta, Riyang Gussyafri Ismalia, Welly Novan, Andre Praputri, Erti Safridatul Audah Tri Putri Lestari, Tri Putri Yenita Morena