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Pengembangan Website Informasi Sekolah di SMP Negeri 2 Kalimanah, Purbalingga Yogiek Indra Kurniawan; Nur Chasanah; Nofiyati Nofiyati
Jurnal SOLMA Vol. 9 No. 2 (2020)
Publisher : Universitas Muhammadiyah Prof. DR. Hamka (UHAMKA Press)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/solma.v9i2.5440

Abstract

Sekolah Menengah Pertama Negeri (SMP N) 2 Kalimanah is a secondary school located in the Kalimanah area, Purbalingga, Central Java. Based on observations and interviews that have been conducted, there are problems at the school, namely regarding the promotion and dissemination of information outside the school which is still lacking because at this time it is only focused on posters and wall magazines. The solution that can be given at SMP N 2 Kalimanah is to create a school information website that specifically displays information for SMP N 2 Kalimanah. With the website, the school can connect more easily with parties outside the school because the website can be accessed by everyone anywhere and anytime as long as it is connected to an internet connection. The service activities are divided into several stages, namely need assessment, application implementation, presentation and website training to teachers, as well as simulation and testing. The result of this activity is a school information website at SMP N 2 Kalimanah that can display news, photos, and activities in the school environment to the wider community. In addition, based on the tests that have been carried out, 95% of respondents stated that the school information website had succeeded in solving the problems of promotion and news delivery at SMP N 2 Kalimanah.
Pengaruh Pengabdian Terhadap Peningkatan Pengetahuan Dalam Pemanfaatan Limbah Kompos Pada Nasabah Bank Sampah Mawar Biru di Kota Tegal Indah Setiawati; Nofiyati Nofiyati; Afik Hardanto; Lulus Ika Riswiana
Abdimas Galuh Vol 8, No 1 (2026): Maret 2026
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/ag.v8i1.21481

Abstract

Kota Tegal menghadapi tantangan pengelolaan sampah yang semakin meningkat, terutama limbah organik yang belum optimal dikelola. Program pengabdian masyarakat ini bertujuan meningkatkan pengetahuan masyarakat terkait pemanfaatan limbah kompos melalui pemberdayaan di Bank Sampah Mawar Biru. Metode yang digunakan adalah pendekatan kuantitatif dengan desain pretest-posttest satu kelompok. Peserta sebanyak 18 orang mengikuti pretest, kemudian diberikan penyuluhan mengenai pengelolaan limbah organik dan kompos, dilanjutkan posttest pada 16 peserta yang hadir. Data dikumpulkan melalui 21 soal pilihan ganda dan penilaian skala likert, kemudian dianalisis secara deskriptif. Hasil menunjukkan adanya peningkatan pengetahuan peserta yang ditandai dengan peningkatan skor dari pretest ke posttest dan fluktuasi nilai yang relatif stabil. Secara umum, program ini berkontribusi positif dalam meningkatkan pemahaman peserta tentang manfaat dan pengelolaan limbah kompos. Kesimpulan, pemberdayaan masyarakat melalui kegiatan ini efektif dalam meningkatkan pengetahuan dan mampu mendorong perubahan perilaku dalam pengelolaan sampah yang berkelanjutan. Saran, kegiatan serupa perlu dilanjutkan dengan melibatkan lebih banyak masyarakat, serta menambah aspek praktik langsung untuk meningkatkan keberhasilan penerapan pengelolaan limbah organik di masyarakat.
Sentiment Analysis of the Kampus Merdeka Program on Twitter Using Support Vector Machine and a Feature Extraction Comparison: TF-IDF vs. FastText Lasmedi Afuan; Nurul Hidayat; Nofiyati Nofiyati; Mohamad Faris As'ad
Journal of Applied Data Sciences Vol 5, No 4: DECEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i4.436

Abstract

The Kampus Merdeka program, launched by the Indonesian Ministry of Education, Culture, Research, and Technology in 2020, aims to enhance students' skills through hands-on work experience. Considering the rising significance of social media, particularly Twitter, in gauging public opinion, this research focuses on analyzing the sentiment towards the Kampus Merdeka program. The primary objective is to classify the sentiments expressed in tweets related to the program and compare two feature extraction techniques—TF-IDF and FastText—to identify the best approach for transforming text data into numerical vectors. The sentiment classification model was built using the Support Vector Machine (SVM) algorithm, a machine learning technique known for its accuracy in text classification. A total of 16,730 tweets were collected and analyzed, yielding an accuracy of 73% for FastText and 72% for TF-IDF. Results show that FastText is more effective in capturing semantic relationships, leading to higher accuracy in sentiment classification. Findings indicate that the public sentiment towards the Kampus Merdeka program is predominantly positive (60.7%), with negative and neutral sentiments at 33.5% and 5.8%, respectively. The success of the FastText method underscores the importance of advanced feature extraction techniques in text classification. The novelty of this research lies in its use of FastText for educational policy evaluation, providing a new perspective on using sentiment analysis to assess public perception of educational programs.