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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Tashdiq: Jurnal Kajian Agama dan Dakwah
Amanda, Annisa
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Religion Humanities Computer Science & IT Education Law, Crime, Criminology & Criminal Justice

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HARMONISASI GERAKAN DAKWAH PIMPINAN CABANG MUHAMMADIYAH SUKAJADI KOTA PEKANBARU DENGAN KONDISI PERUBAHAN NILAI-NILAI SOSIAL MASYARAKAT DI ERA DIGITAL Ananda, Icha; Nisa, Luthfiatin; Putri, Aizha Nabila; Amanda, Annisa; Fitri, Fadhilah Annisa
Tashdiq: Jurnal Kajian Agama dan Dakwah Vol. 12 No. 3 (2025): Tashdiq: Jurnal Kajian Agama dan Dakwah
Publisher : Cahaya Ilmu Bangsa Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.4236/tashdiq.v12i3.11444

Abstract

This study aims to analyze the harmonization of the da'wah movement carried out by the Muhammadiyah Branch Leadership (PCM) Sukajadi Pekanbaru City with the changing social values of society in the digital era. Using a qualitative approach and case study method, this research examines digital da'wah strategies, supporting factors, and challenges faced. The results show that PCM Sukajadi has utilized social media platforms such as Instagram, YouTube, and Facebook to disseminate creative and relevant religious content for the younger generation. However, digital disparities and resistance to changes in da'wah methods remain significant challenges. Recommendations include enhancing digital competencies of preachers, collaboration with educational institutions and NGOs, and community empowerment programs to address technological access gaps. The study concludes that harmonizing da'wah movements in the digital era requires adaptation to social and technological changes, as well as inclusive and participatory approaches. Penelitian ini bertujuan untuk menganalisis harmonisasi gerakan dakwah yang dijalankan oleh Pimpinan Cabang Muhammadiyah (PCM) Sukajadi Kota Pekanbaru dengan perubahan nilai-nilai sosial masyarakat di era digital. Melalui pendekatan kualitatif dan metode studi kasus, penelitian ini mengkaji strategi dakwah digital, faktor pendukung, dan tantangan yang dihadapi. Hasil penelitian menunjukkan bahwa PCM Sukajadi telah memanfaatkan media sosial seperti Instagram, YouTube, dan Facebook untuk menyebarkan konten keagamaan yang kreatif dan relevan bagi generasi muda. Namun, kesenjangan digital dan resistensi terhadap perubahan metode dakwah menjadi tantangan utama. Rekomendasi penelitian mencakup peningkatan kompetensi digital para dai, kolaborasi dengan lembaga pendidikan dan NGO, serta program pemberdayaan masyarakat untuk mengatasi kesenjangan akses teknologi. Penelitian ini menyimpulkan bahwa harmonisasi gerakan dakwah di era digital memerlukan adaptasi terhadap perubahan sosial dan teknologi, serta pendekatan yang inklusif dan partisipatif.
Predicting Prospective Student Interests Using the C4.5 Algorithm and Naive Bayes Ritonga, Ali Akbar; Amanda, Annisa; Hasibuan, Elysa Rohayani
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 1 (2025): Research Article, January 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.14441

Abstract

Students are individuals pursuing higher education at a university with the goal of enhancing their knowledge, skills, and character to succeed in the professional world and contribute to society. The purpose of this study is to analyze the factors that influence prospective students' interest in continuing their education using the C4.5 Algorithm and the Naïve Bayes Method. The importance of understanding prospective students' interest patterns is expected to help universities formulate more effective strategies. The purpose of this study is to determine how well the two methods classify data and understand the factors that most influence prospective students' decisions. The C4.5 Algorithm is known to be effective in building decision trees that are easy to interpret, while the Naïve Bayes Method has the advantage of handling datasets with independent attributes. This study uses the stages of data selection, data pre-processing, algorithm application, and model evaluation. The classification results obtained from the C4.5 Algorithm show that 132 data are included in the interest category and 8 data are not interested, while the Naïve Bayes Method produces 131 data of interest and 9 data are not interested. In conclusion, both methods have good accuracy levels, but the Naïve Bayes Method shows superiority in Recall value, while the C4.5 Algorithm excels in interpretation of results and clarity of classification patterns.
Co-Authors Ananda, Icha Fitri, Fadhilah Annisa Hasibuan, Elysa Rohayani Nisa, Luthfiatin Putri, Aizha Nabila Ritonga, Ali Akbar