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All Journal Jurnal Pekommas Jurnal Teknologi Informasi dan Komunikasi Compiler Jurnal Penelitian Pers dan Komunikasi Pembangunan JISKa (Jurnal Informatika Sunan Kalijaga) Dharma: Jurnal Pengabdian Masyarakat Jurnal INFOTEL Indonesian Journal on Data Science
Muhammad Rifqi Maarif, Muhammad Rifqi
Universitas Tidar
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

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Content Analysis on Twitter Users Interaction within First 100 Days of Jakarta’s New Government by Using Text Mining Maarif, Muhammad Rifqi
Jurnal Pekommas Vol 3 No 2 (2018): October 2018
Publisher : Sekolah Tinggi Multi Media “MMTC” Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30818/jpkm.2018.2030203

Abstract

As one of the biggest democratic country in the world, Indonesia have very responsive society towards the various political move in either the central or local governments. In Indonesia, the first 100 days of new government era usually became a crucial timelines in which the society give their intents attention to government’s performance. By the massive penetration of online social networking platform likes Twitter, the interaction between netizens and government figure official account will significantly increase. The povincial election for of Jakarta momentum was one of the most attractive political events in which Anies Baswedan and Sandiaga Uno were elected the lead of Jakarta government. The implication is the society would look intensively at their performance within their first 100 days. With the huge amount of Twitter users in Indonesia, Indonesian Twitter was very reactive towards any movement of Anies Sandi. Thus, this platform can be utilized to monitor the public opinion towards first 100 days of Anies Sandi government. In this study, we analyzed the content of conversations in interaction among the netizen and official Twitter Account of Anies Baswedan (@aniesbaswedan), Sandiaga Uno (@sandiuno) and the Government of Jakarta (@DKIJakarta). A set of text mining techniques was employed in this study.
ANALISIS PERSEPSI PUBLIK DI MEDIA SOSIAL TERHADAP PRODUK HALAL DI INDONESIA MENGGUNAKAN TEXT MINING Maarif, Muhammad Rifqi; Salim, D Jayus Nor
INDONESIAN JOURNAL ON DATA SCIENCE Vol. 2 No. 2 (2024): Indonesian Journal On Data Science
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/ijds.v2i2.1487

Abstract

The assurance of the halal status of a product is crucial for Muslim consumers, especially in Indonesia, the country with the largest Muslim population in the world. The government, through the Ministry of Religious Affairs, has implemented halal certification to ensure the validity of products. However, the implementation of the halal assurance system remains controversial, with some viewing it as an effort for government profit, particularly by the Ministry of Religious Affairs through the Indonesian Council of Ulama (MUI). Negative sentiments from opposing groups have the potential to escalate and influence other individuals or communities if not properly addressed. One preventive measure is to promote education and awareness of halal products through digital media, especially social media. Given the widespread use of social media, particularly among millennials, it can serve as an effective and cost-efficient platform for education and promotion. Educational efforts via social media require specific strategies to ensure the optimal dissemination of information as intended. Understanding the patterns and characteristics of content as well as the socio-cultural context of social media users is essential. This understanding can be achieved through a comprehensive analysis of the diverse and abundant user-generated content on social media platforms. Therefore, this study proposes a text mining-based method to develop a framework for understanding the characteristics and dynamics of public discourse on halal products on social media.
DIGITALIASI LAYANAN PERSURATAN DI DESA MADUSARI, KABUPATEN MAGELANG MELALUI PENGEMBANGAN APLIKASI BERBASIS WEB Nawawi, Ibrahim; Wibowo, Rheza Ari; Maarif, Muhammad Rifqi
Dharma: Jurnal Pengabdian Masyarakat Vol. 6 No. 1 (2025): Mei
Publisher : Universitas Pembangunan Nasional "Veteran" Yogyakarta

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Abstract

Digitalisasi layanan administrasi desa telah terbukti menjadi solusi efektif dalam meningkatkan efisiensi dan transparansi pelayanan publik. Kegiatan pengabdian ini bertujuan untuk mengembangkan aplikasi berbasis digital yang mempermudah proses persuratan di Desa Madusari, Kabupaten Magelang. Aplikasi ini memungkinkan masyarakat mengakses layanan administrasi, seperti surat keterangan domisili, surat pengantar, dan surat keterangan usaha, secara mandiri melalui perangkat yang terhubung dengan internet. Hasil implementasi menunjukkan bahwa aplikasi ini berhasil mempercepat proses layanan, yang sebelumnya dilakukan secara manual dan memakan waktu. Selain itu, transparansi dalam pengelolaan administrasi meningkat, sehingga memperkuat kepercayaan masyarakat terhadap pemerintah desa. Tantangan terkait literasi digital dan infrastruktur internet tetap menjadi fokus untuk memastikan keberlanjutan aplikasi ini. 
Memahami Persepsi Pelanggan tentang Produk Fashion Lokal di Pasar Online melalui Analisis Konten Nata, Imam Adi; Maarif, Muhammad Rifqi
JURNAL INFOTEL Vol 16 No 1 (2024): February 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i1.1070

Abstract

This research employs Natural Language Processing (NLP) techniques to evaluate customer reviews obtained from online marketplaces. It uses keyword extraction and clustering to identify thematic clusters in the data. These clusters reveal shared contextual significance and provide a higher-level perspective on customer perceptions of local fashion products. Sentiment analysis is also conducted within each theme to understand customer sentiment. This approach goes beyond binary sentiment classification and offers a more nuanced analysis. By incorporating keyword extraction, clustering, and sentiment analysis, this research offers a thorough framework for comprehending customer perceptions in the digital marketplace. It contributes to the field of e-commerce by offering a robust methodology for decoding customer sentiments towards local fashion products. The findings have substantial implications for marketers, designers, and platform providers in online marketplaces, leading to a more consumer-centric e-commerce ecosystem.
Co-Authors Agung Priyanto Agung Priyanto Arif Himawan Chaerul Hadi D Jayus Nor Salim Dimas Pratama Jati Ibrahim Nawawi Imam Adi Nata Jati, Dimas Pratama Ulfi Saidata Aesyi Wibowo, Rheza Ari