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All Journal Jurnal Minfo Polgan (JMP) SWARNA Jurnal Ilmu Komputer dan Sistem Informasi PUBLIDIMAS CSRID
Rita Novita Sari
Universitas Islam Negeri Sumatera Utara
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Social Sciences

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Klasifikasi Lonjakan Ekstrem Nilai Tukar USD/IDR Menggunakan Gaussian Naïve Bayes Meini Syakinah Ritonga; Rita Novita Sari
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 2 (2025): Mei 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i2.457

Abstract

The fluctuation of the Rupiah exchange rate against the US Dollar (USD/IDR) potentially triggers macroeconomic instability. This study aims to classify potential extreme surges in the USD/IDR exchange rate using data mining techniques with the Gaussian Naïve Bayes algorithm. A total of 502 daily historical observation data were extracted into four continuous predictor features: volatility, closing difference, upper bound difference, and lower bound difference. The evaluation was conducted using an 80% training and 20% testing data split. The results show that the model can identify "Normal" and "Extreme" classes with an accuracy of 96.04%, a precision of 62.50%, and a recall of 83.33%. The 5-Fold Cross Validation test yielded an average cumulative accuracy of 95.43%, confirming that the model's performance is stable and does not experience overfitting. In conclusion, the Gaussian Naïve Bayes algorithm is proven to be effective and reliable as an early warning system against the risk of extreme foreign exchange rate surges.
Analisis Pola Perilaku Penggunaan Game Online pada Remaja Menggunakan Algoritma K-Means Fitriana Harahap; Husin Sariangsah; Masri Wahyuni; Robiatul Adawiyah; Ermayanti Astuti; Rita Novita Sari
Jurnal Minfo Polgan Vol. 15 No. 1 (2026): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v15i1.16058

Abstract

Perkembangan game online yang semakin pesat telah memengaruhi pola perilaku remaja, baik dari aspek sosial, psikologis, maupun akademik. Intensitas penggunaan game online yang tidak terkontrol berpotensi menimbulkan berbagai permasalahan, sehingga diperlukan analisis berbasis data untuk mengidentifikasi pola perilaku penggunaan game online secara objektif. Penelitian ini bertujuan untuk menganalisis pola perilaku penggunaan game online pada remaja dengan menerapkan teknik clustering dalam data mining berbasis tools. Data penelitian diperoleh melalui kuesioner terstruktur yang melibatkan variabel id_responden, usia, jenis_kelamin, frekuensi_bermain, durasi_bermain, jenis_game, waktu_bermain, tujuan_bermain, tingkat_keterlibatan, dan pengeluaran_game. Tahapan penelitian meliputi data preprocessing yang mencakup pembersihan data, transformasi, dan normalisasi, dilanjutkan dengan penerapan algoritma clustering menggunakan tools data mining. Metode K-Means digunakan untuk mengelompokkan responden ke dalam beberapa klaster berdasarkan tingkat kemiripan pola perilaku bermain game online. Hasil penelitian menunjukkan terbentuknya beberapa klaster yang merepresentasikan karakteristik perilaku remaja, seperti klaster dengan intensitas bermain rendah, sedang, dan tinggi. Setiap klaster memiliki karakteristik yang berbeda, terutama pada variabel frekuensi_bermain, durasi_bermain, tingkat_keterlibatan, dan pengeluaran_game. Hasil pengelompokan ini diharapkan dapat memberikan gambaran yang komprehensif mengenai pola perilaku penggunaan game online pada remaja serta menjadi dasar bagi orang tua, pendidik, dan pemangku kebijakan dalam merancang strategi pencegahan dan pengendalian penggunaan game online yang lebih efektif dan berbasis data.
Pelatihan Penggunaan Sistem Informasi Perpustakaan Cerdas untuk Optimalisasi Layanan dan Pengadaan Koleksi Buku di Sekolah Faur Dilla Ananda Putri; Sri Lestari Rahayu; Fujiati Fujiati; Rita Novita Sari; Nur Anzelina Harahap; Soeheri
Publikasi Pengabdian Masyarakat Vol 6 No 1 (2026): PUBLIDIMAS Vol. 6 No. 1 MEI 2026
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/publidimas.6.1.2026.01-10

Abstract

Pengelolaan perpustakaan di SD Negeri 104208 saat ini masih menghadapi berbagai kendala karena sistem pencatatan buku, peminjaman, hingga pengembalian yang dilakukan secara manual. Hal ini mengakibatkan lambatnya pelayanan literasi bagi siswa dan sulitnya pihak sekolah dalam merencanakan pengadaan koleksi buku baru yang sesuai dengan minat siswa. Kegiatan Pengabdian kepada Masyarakat (PkM) ini bertujuan untuk memberikan solusi melalui pelatihan dan pendampingan penggunaan Sistem Informasi Perpustakaan Cerdas. Metode pelaksanaan kegiatan meliputi tiga tahap utama, yaitu: analisis kebutuhan dan instalasi sistem, workshop pelatihan teknis penggunaan fitur katalog digital, serta pendampingan langsung dalam pengoperasian fitur prediksi pengadaan buku. Hasil dari kegiatan ini menunjukkan adanya peningkatan keterampilan staf perpustakaan dalam mengelola data buku secara digital dan mempercepat proses transaksi layanan sebesar 70%. Selain itu, fitur prediksi cerdas dalam aplikasi ini membantu sekolah dalam menentukan prioritas pengadaan buku berdasarkan pola peminjaman siswa secara akurat. Melalui kegiatan PkM ini, manajemen perpustakaan di SD Negeri 104208 menjadi lebih efektif, efisien, dan siap mendukung program literasi sekolah berbasis digital.
Classification of Film Genres Based on Synopsis Using Support Vector Machine (SVM) Method with TF-IDF and N-Gram Rita Novita Sari; Dea Alya; Dodyk Fahlome
CSRID (Computer Science Research and Its Development Journal) Vol. 18 No. 2 (2026): Juni 2026
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.18.2.2026.381-394

Abstract

With the wide variety of film genres available, audiences often face difficulties in determining a movie’s genre solely based on its synopsis. Therefore, an automated system is needed to classify movie genres effectively. This study aims to classify movie genres based on film synopses using the Support Vector Machine (SVM) method combined with TF-IDF and N-Gram feature extraction techniques. The dataset used in this research was obtained from Kaggle and consisted of 10,000 movie records with multi-label characteristics, which were subsequently transformed into Single-label data. Four main genres were selected, namely Action, Comedy, Drama, and Horror, resulting in a final dataset of 6,000 records. The research process included data preparation, text preprocessing, TF-IDF feature extraction using unigram and bigram models, data splitting, and model evaluation. All data processing procedures were carried out in Google Colab using the Python programming language. The evaluation results indicate that the SVM model with a linear kernel achieved an accuracy of 83%. The Horror genre demonstrated the best performance, with a precision value of 91%, recall of 92%, and F1-score of 92%. These findings suggest that the combination of TF-IDF, N-Gram, and SVM provides satisfactory results for movie genre classification based on film synopses.
Penyuluhan Sertifikasi Halal untuk UMKM Berbasis Pariwisata di Era Digital: Inisiatif Keterlibatan Komunitas Internasional di Bukit Lawang, Indonesia: Halal Certification Education for Tourism-Based MSMEs in the Digital Era: An International Community Engagement Initiative in Bukit Lawang, Indonesia Ilka Zufria; Zulham; Zalina Zakaria; Suhardi; M. Ridwan; Nurhanifah; Achyar Zein; Tisna Handayani; Rita Novita Sari; Muhammad Siddik Hasibuan
SWARNA: Jurnal Pengabdian Kepada Masyarakat Vol. 5 No. 7 (2026): SWARNA : Jurnal Pengabdian Kepada Masyarakat, Juli, 2026
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi 45 Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/swarna.v5i7.3562

Abstract

Halal certification is important for improving the competitiveness of Micro, Small, and Medium Enterprises (MSMEs), especially in tourism destinations attracting Muslim travelers. However, many business owners in Bukit Lawang still have limited understanding of halal certification requirements and digital certification procedures. This community engagement program provided practical education on halal certification and introduced participants to digital-based certification services. Activities included presentations, interactive discussions, and question-and-answer sessions involving 32 tourism-based MSME owners in Bukit Lawang, North Sumatra, organized through international collaboration between the Faculty of Science and Technology, Universitas Islam Negeri Sumatera Utara, Indonesia, and Universiti Malaya, Malaysia. Participants showed strong enthusiasm, gaining better understanding of halal principles, certification procedures, and digital platforms, while recognizing the strategic value of halal certification in enhancing consumer confidence, expanding market opportunities, and improving competitiveness. A satisfaction survey completed by 15 of the 32 participants showed consistently high mean scores (3.73–4.00 on a 1–4 scale) across all evaluated aspects, and all respondents expressed interest in future similar programs. These findings suggest that community-based educational programs can support the sustainable development of tourism-based MSMEs in the digital era.
Co-Authors Achyar Zein Dea Alya Dodyk Fahlome Ermayanti Astuti Faur Dilla Ananda Putri Fitriana Harahap Fujiati, Fujiati Husin Sariangsah Ilka Zufria M. Ridwan Masri Wahyuni Meini Syakinah Ritonga Muhammad Siddik Hasibuan Nur Anzelina Harahap Nurhanifah Robiatul Adawiyah Soeheri Sri Lestari Rahayu Suhardi, Suhardi Tisna Handayani Zalina Zakaria Zulham