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All Journal Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer (BALOK)
Pelangi, Kartika Chandra
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Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice Nursing

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Klasifikasi Teks PornoGrafi Berbasis Machine Learning Menggunakan Metode Naive Bayes Tambung, Samsudin; Pelangi, Kartika Chandra; Nanja, Muis; Malago, Yusrianto
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 4 No 2 (2025)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37195/balok.v4i2.726

Abstract

Abstract- The information via the internet spreads rapidly. Not only does it have a positive impact, but also a negative impact, one of which is the ease of finding information that contains negative things such as pornography. That problem can be overcome by research on machine learning-based classification of pornographic texts using the Naive Bayes method. Naïve Bayes is a probabilistic classifier that calculates a set of probabilities based on the number of frequencies and combinations of each value from a given dataset. Through Naïve Bayes, it is expected that there is a possibility to classify the text of story titles containing pornography downloaded via a web page. The type of data used is pornographic story titles downloaded via porn sites. There are 100 story title datasets employed. The classification stages using the Naive Bayes Classifier Algorithm include Preprocessing, TF-IDF weighting, Naive Bayes classification, and testing using Classification Accuracy, Precision, and Recall. The test results using the Data Splitting method are examined into five comparisons with TF-IDF values with each level of Accuracy, Precision, and Recall up to 76.44%, 82.43%, and 73.43%. The characterization without using TF-IDF, respectively, obtained Accuracy, Precision, and Recall values up to 97%, 96%, and 93%. The result is that the Naïve Bayes technique without TF-IDF creates a more favorable execution than TF-IDF. Keywords: pornographic story titles, classification, Naive Bayes
Pengelolaan Kelapa Pada Umkm Sinar Harapan Desa Bongohulawa Kecamatan Bongomeme Kabupaten Gorontalo Pelangi, Kartika Chandra; Haba, Abd Rahmat Karim; Olii, Nurhayaty; Zohrahayaty, Zohrahayaty
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.v8i1.21322

Abstract

UMKM Sinar Harapan di Desa Bongohulawa hanya memproduksi minyak kelapa karena ketersediaannya yang mudah, dan sistem penjualan produknya masih konvensional, yaitu dengan menjual produk minyak kelapa ke kios-kios terdekat. Namun, bahan baku ini dapat diolah menjadi sapu lidi selain minyak kelapa. Kegiatan pengabdian masyarakat ini telah meningkatkan pengetahuan dan keterampilan mitra dalam mengembangkan produk olahan kelapa seperti minyak kelapa dan sapu lidi. Selama pelaksanaan, 100% peserta mampu menghasilkan produk olahan kelapa, yaitu minyak kelapa murni tanpa bau tak sedap dan berwarna bening, serta membuat sapu lidi. Dari segi penjualan, mitra UMKM Sinar Harapan juga telah mampu memanfaatkan teknologi e-commerce, sehingga meningkatkan usaha di Desa Bongohulawa
Co-Authors Abd. Rahmat Karim Haba Muis Nanja, Muis Olii, Nurhayaty Tambung, Samsudin Yusrianto Malago Zohrahayaty