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All Journal Jurnal Informatika dan Teknik Elektro Terapan JOIV : International Journal on Informatics Visualization International Journal of Artificial Intelligence Research Journal of Information Technology and Computer Science (JOINTECS) Syntax Literate: Jurnal Ilmiah Indonesia JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Conference on Innovation and Application of Science and Technology (CIASTECH) J-SAKTI (Jurnal Sains Komputer dan Informatika) JURTEKSI Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jusikom: Jurnal Sistem Informasi Ilmu Komputer Jurnal Ilmu Komputer dan Bisnis Systematics Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Teknologi Dan Sistem Informasi Bisnis Buana Ilmu Buana Information Technology and Computer Sciences (BIT and CS) Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal) International Journal of Educational Review Journal of Applied Data Sciences Jurnal Cahaya Mandalika Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Djtechno: Jurnal Teknologi Informasi KLIK: Kajian Ilmiah Informatika dan Komputer Instal : Jurnal Komputer J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Minfo Polgan (JMP) Abdimas Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Jurnal Sistem Informasi STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Innovative: Journal Of Social Science Research Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal) Jurnal Ilmiah Pengabdian Kepada Masyarakat (Nyiur-Dimas) Informasi interaktif : jurnal informatika dan teknologi informasi
Priyatna, Bayu
Universitas Buana Perjuangan Karawang
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Public Health Social Sciences Other

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Implementasi Merdeka Belajar Pendidikan Agama Islam di Tingkat Sekolah Dasar/Madrasah Ibtidaiyah Dengan Memanfaatkan Teknologi Informasi Masruroh, Siti; Haerudin, Haerudin; Priyatna, Bayu
Jurnal Ilmiah Pengabdian Kepada Masyarakat (Nyiur-Dimas) Vol 3 No 1 (2023)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LP2M) IAIN Manado

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30984/nyiur.v3i1.424

Abstract

The purpose of study program-based community service is as an effort by lecturers to carry out the tridarma of higher education. In this case the Directorate General of Islamic Higher Religious Education (Diktis) provides a national level grant program for all lecturers under the ministry of religion. On this occasion, we propose a service with the theme Implementation of Freedom to Learn Islamic Religious Education at the Elementary School/Madrasah Ibtidaiyah Level by utilizing Information Technology, namely making an application "Islamic Smart Learning" for Madrasah Ibtidaiyah Al I'anah Dusun Kalihurip Duren Village, Klari District, Karawang Regency. This service activity is a contribution of the PAI Study Program to the world of elementary/Madrasah Ibtidaiyah education as a means of utilizing information technology in the independent learning program with the principle of independent learning, it is assumed that students are given freedom to access learning media that is more intelligent and enjoyable. So that the learning potential of students will grow more measurably and directed because there are more interactive learning media.
Assessment Decision Support System Best Teacher By Using Analytical Hierarchy Process (AHP) Method Hananto, April Lia; Priyatna, Bayu; Nurapriani, Fitria; Fauzi, Ahmad; Tukino, Tukino; Ahnaf, Naufal Zubdi
International Journal of Artificial Intelligence Research Vol 6, No 1.1 (2022)
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v6i1.1.572

Abstract

Assessment of teachers by the Principal of SMA Negeri 1 Kedungwaringin certainly needs to be done to determine the best teacher, so that teacher performance is in accordance with the specified competencies because the teacher is the most important and influential role in the world of education in the process of teaching and learning activities. The assessment was carried out not only for civil servants (PNS), including honorary teachers who also participated in the assessment process so that there were no limitations in evaluating teachers at SMA Negeri 1 Kedungwaringin. This assessment process uses the Analytical Hierarchy Process (AHP) Algorithm. The method used aims to determine the best teacher at SMA Negeri 1 Kedungwaringin who is in accordance with the assessment criteria prepared. The results of the ranking show that Dian Purwanti, S.Pd obtained the highest score of 0.342 out of 5 other teachers. This application is expected to assist school principals in determining the best teacher based on the criteria and weight of each existing value.
Implementasi Algoritma K-Means Untuk Klasterisasi Data Obat Puskesmas Kotabaru Kurniawan, Muhamad Dicky; Priyatna, Bayu; Nurapriani, Fitria
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 2 (2023): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i2.693

Abstract

Drug management is one of the things needed to manage drug supplies. Proper planning of drug needs makes drug procurement efficient and effective so that drugs are available in sufficient types and quantities as needed and easily obtained when needed. The purpose of this study was to classify drug data at the Kotabaru Health Center which can be used as a reference in making decisions in planning and controlling drug needs at the Health Center. The data used in this study are the Kotabaru Health Center annual report data from 2019 to 2021. Data processing in this study uses the K-means clustering method with rapidminer tools which is a data grouping technique by dividing the existing data into one or two forms. more clusters. The results of this study divide the drug data into 4 clusters, namely the first cluster (C0) with very low usage consisting of 27 drugs, the second cluster (C2) with low usage consisting of 6 drugs, the third cluster (C3) with high usage consisting of 1 drug, and the fourth (C2) with the highest usage consisting of 1 drug.
Analisis Sentimen Terhadap Opini Proyek Kereta Cepat Menggunakan Metode Naïve Bayes Classifier Jabar Sanjaya; Tukino; Priyatna, Bayu; Shofia Hilabi, Shofa
JURNAL FASILKOM Vol. 14 No. 1 (2024): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v14i1.6598

Abstract

Twitter merupakan satu dari banyaknya media sosial yang digunakan oleh hampir Sebagian besar masyarakat. Penggunaaan twitter umumnya digunakan untuk memposting sesuatu, seperti beropini tentang infrastruktur negara misalnya. Adapun salah satu infrastruktur negara yang sedang ramai diperbincangkan adalah proyek kereta cepat, masyarakat memiliki banyak pandangan tentang proyek ini. Untuk mengetahui opini masyarakat, tentang hal itu maka akan dilakukan Sentimen Analisis. Penelitian ini bertujuan untuk mengetahui penerapan Sentimen Analisis menggunakan metode Naïve Nayes Classifier pada opini masyarakat tentang proyek kereta cepat. Penelitian dimulai dari proses pengambilan data menggunakan teknik crawling dan mendapatkan kurang lebih 2007 tweet yang membahas proyek kereta cepat. Yang kemudian data dari hasil sentimen di preprocessing¸ lalu setiap data di labeling. Dari hasil labeling diterapkan metode naïve bayes classifier. Dari hasil penelitian ini menunjukan 57,23% masyarakat lebih dominan berkomentar atau beropini positif tentang proyek kereta cepat. Dan sisanya 42,77% beropini negatif. Adapun hasil evaluasi model Naïve Bayes yaitu, Presisi 81%, Recall 81%, F1-score 81%. dan kemudian Akurasi sebesar 81%.
Classification of Starling Images Using a Bayesian Network Hananto, April Lia; Rahman, Aviv Yuniar; Paryono, Tukino; Priyatna, Bayu; Hananto, Agustia; Huda, Baenil
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.423

Abstract

The classification of starling species is vital for biodiversity conservation, especially as some species are endangered. This research investigates the effectiveness of the Bayesian Network (BayesNet) for classifying starling species and compares its performance with Artificial Neural Networks (ANN) and Naive Bayes models. The dataset comprises 300 images of five starling species—Bali, Rio, Moon, Kebo, and Uret—captured under controlled conditions. Feature extraction focused on color, texture, and shape, while data augmentation through slight image rotations was applied to enhance model generalization. The BayesNet model achieved an accuracy of 96.29% using a 90:10 training-to-testing split, outperforming ANN (90.74%) and Naive Bayes variants. Precision, recall, F1-score, and AUC-ROC values further validated the robustness of the BayesNet model, with precision at 0.90, recall at 0.91, F1-score at 0.92, and AUC-ROC at 0.95. These results demonstrate the superior performance of multi-feature Bayesian Networks in starling classification compared to other machine learning models. The novelty of this study lies in its application of a probabilistic approach using Bayesian Networks, which enhances interpretability and performance, especially in scenarios with limited data. Future work may explore additional feature sets and advanced machine learning models to further improve classification accuracy and robustness.
Implementasi Algoritma K-Means Untuk Klasterisasi Data Obat Puskesmas Kotabaru Kurniawan, Muhamad Dicky; Priyatna, Bayu; Nurapriani, Fitria
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 2 (2023): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i2.693

Abstract

Drug management is one of the things needed to manage drug supplies. Proper planning of drug needs makes drug procurement efficient and effective so that drugs are available in sufficient types and quantities as needed and easily obtained when needed. The purpose of this study was to classify drug data at the Kotabaru Health Center which can be used as a reference in making decisions in planning and controlling drug needs at the Health Center. The data used in this study are the Kotabaru Health Center annual report data from 2019 to 2021. Data processing in this study uses the K-means clustering method with rapidminer tools which is a data grouping technique by dividing the existing data into one or two forms. more clusters. The results of this study divide the drug data into 4 clusters, namely the first cluster (C0) with very low usage consisting of 27 drugs, the second cluster (C2) with low usage consisting of 6 drugs, the third cluster (C3) with high usage consisting of 1 drug, and the fourth (C2) with the highest usage consisting of 1 drug.
Implementasi Metode K-Means Clustering Pada Penilaian Kinerja Karyawan PT Kopetri Citra Abadi: Metode K-Means Clustering Intan, Melani; Bayu Priyatna; Fitria Nurapriani; Shofa Shofia Hilabi
Informasi Interaktif : Jurnal Informatika dan Teknologi Informasi Vol 8 No 1 (2023): JII Volume 8, Number 1, Januari 2023
Publisher : Program Studi Informatika Fakultas Teknik Universitas Janabadra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37159/jii.v8i1.18

Abstract

Dalam dunia pekerjaan terdapat istilah karyawan terbaik yang menjadi tolak ukur kemajuan perusahaan itu sendiri. Penentuan tersebut dapat dilakukan dengan cara melihat kinerja karyawan sehari-hari seperti kedisiplinan, kerajinan dan prestasi lainnya yang mendukung pekerjaan tersebut. Selain itu, banyak juga aspek-aspek lain yang dapat menjadi bahan pertimbangan atasan dalam memberikan penilaian kepada karyawan. Pentingnya sumber daya manusia (SDM) dalam suatu perusahaan sebagai subyek pelaksana kebijakan serta segala kegiatan operasional perusahaan menjadikan perusahaan harus tetap berani dalam menghadapi tantangan dan perubahan serta memenangkan persaingan. Penguasaan aset manusia secara substansial mempengaruhi beragam perspektif pemenuhan tenaga kerja dalam suatu instansi. sumber daya manusia tersebut sangat mempengaruhi berbagai aspek penentu dalam keberhasilan kerja di suatu perusahaan. PT Kopetri Citra Abadi merupakan perusahaan jasa keamanan yang konsisten melakukan penilaian kinerja setiap bulannya, kemudian dilakukan rekapitulasi setiap tahun dengan akumulasi nilai yang diambil dari laporan penilaian bulanan. Dengan banyaknya karyawan dari perusahaan ini membutuhkan sebuah metode perhitungan yang akurat dan perlunya klasifikasi nilai berdasarkan beberapa kategori penilaian, melihat pentingnya hal tersebut maka proses penilaian karyawan perlu dilakukan secara rasional. Evaluasi ini akan berdampak pada pemberian  feed back antara atasan dan bawahan secara sinergis. Sehingga karyawan akan memahami objektivitas kerja dan mampu mendorong produktivitas usaha perusahaan. Maka dalam penelitian ini akan membahas perhitungan menggunakan metode K-Means Clustering secara manual dan menggunakan tools pada aplikasi Orange data mining dalam penilaian kinerja karyawan PT Kopetri Citra Abadi. Dari perhitungan tersebut menghasilkan pengelompokkan data 92 orang karyawan berdasarkan 3 kriteria yaitu sangat baik (C1) sebanyak 15 data, cukup baik (C2) sebanyak 44 data, dan kurang baik (C3) sebanyak 33 data. Keywords : K-Means, clustering,penilaian kinerja karyawan, prestasi kerja, klasifikasi
Penggunaan Algoritma K-Means Clustering CRISP-DM Dalam Mengelompokkan Drama Korea Sebagai Rekomendasi Film Fatlun, Aulia; Hilabi, Shofa Shofiah; Priyatna, Bayu; Hananto, April Lia
JATISI Vol 12 No 1 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i1.11347

Abstract

This study classifies Korean dramas based on popularity and ratings using K-Means Clustering within the CRISP-DM framework. The dataset from Kaggle includes title, release year, rating, vote count, duration, and genre. The Elbow Method determined that 2 clusters were optimal, with a Silhouette Score of 0.35, indicating a fairly good grouping. Recommended dramas have high ratings and vote counts, showing strong popularity, while less recommended dramas have lower ratings and fewer votes, indicating limited appeal. This model can enhance recommendation system accuracy, assist viewers in content selection, and help streaming platforms understand user trends and marketing strategies. Future improvements may involve alternative clustering methods (DBSCAN, Hierarchical Clustering) and additional features like actors, directors, and release year to refine accuracy.
Klasifikasi Genre dan Rating Konten di Netflix : Wawasan dari Analisis Chi-Square dan Clustering alzahra, alika aziza; Hananto, April Lia; Hananto, Agustia; Priyatna, Bayu
JATISI Vol 12 No 1 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i1.11354

Abstract

Streaming platforms like Netflix rely on genre classification and content rating to enhance user experience and develop more effective marketing strategies. This study aims to analyze the relationship between genre and content rating on Netflix using Chi-Square analysis and clustering techniques to group genres based on rating distribution patterns. The Chi-Square test results indicate a significant relationship between genre and content rating (p-value < 0.05), suggesting that certain types of content tend to receive specific ratings. Furthermore, clustering analysis identifies three main groups: genres with high ratings suitable for a broad audience, genres with varied ratings that are more subjective, and genres with lower ratings that often include adult or less popular content. These findings provide insights that Netflix can leverage to optimize its content catalog, develop personalized recommendations, and tailor marketing strategies based on user consumption patterns.
EVALUATION IT GOVERNANCE BASED ON COBIT 2019 FRAMEWORK AT BUANA PERJUANGAN UNIVERSITY Yazid, Muhammad Abi; Hananto, April Lia; Priyatna, Bayu; Paryono, Tukino
JURTEKSI (Jurnal Teknologi dan Sistem Informasi) Vol 11, No 2 (2025): Maret 2025
Publisher : Universitas Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i2.3791

Abstract

Abstract: The utilization of Information Technology (IT) in higher education institutions is crucial for supporting academic and administrative activities. The Data and Information Center (PUSDATIN) of UBP Karawang manages various IT services, such as Sistem Informasi Perguruan Tinggi (SIPT), e-learning Buana Online Course (BOC), and others. This study aims to evaluate the maturity level of IT governance at UBP Karawang to ensure alignment with the university's strategic goals and identify areas requiring improvement. The research employs a quantitative descriptive method based on COBIT 2019, with data collected from 92 respondents, analyzed through goals cascade mapping and maturity level measurement. The evaluation results across 14 COBIT 2019 domains indicate that the IT governance maturity level at UBP Karawang is at Level 4 (Quantitatively Managed) with a score of 3.86 and an average gap of 1.13 from the expected level. The findings suggest that while IT governance at UBP Karawang is well-managed, there is still room for improvement. Therefore, several recommendations are proposed to optimize IT governance effectiveness, ensure regulatory compliance, and support the achievement of the university's strategic objectives.            Keywords: COBIT 2019; IT evaluation; IT governance; maturity level. Abstrak: Pemanfaatan Teknologi Informasi (TI) di perguruan tinggi sangat krusial untuk mendukung aktivitas akademik dan administratif. Pusat Data dan Informasi (PUSDATIN) UBP Karawang mengelola berbagai layanan TI, seperti Sistem Informasi Perguruan Tinggi (SIPT), e-learning Buana Online Course (BOC) dan lain-lain. Penelitian ini bertujuan untuk mengevaluasi tingkat kematangan tata kelola TI di UBP Karawang guna memastikan keselarasan dengan tujuan universitas serta mengidentifikasi area yang memerlukan perbaikan. Penelitian ini menerapkan metode deskriptif kuantitatif berbasis COBIT 2019, dengan data diperoleh dari 92 responden, dianalisis melalui pemetaan goals cascade dan pengukuran maturity level. Hasil evaluasi pada 14 domain COBIT 2019 menunjukkan tingkat kematangan TI UBP Karawang berada di Level 4 (Terkelola secara Kuantitatif) dengan skor 3.86, serta rata-rata gap 1.13 dari tingkat yang diharapkan. Kesimpulan dari penelitian ini mengindikasikan bahwa meskipun tata kelola TI di UBP Karawang telah terkelola dengan baik, masih terdapat ruang untuk perbaikan. Oleh karena itu, beberapa rekomendasi diajukan guna mengoptimalkan efektivitas tata kelola TI, menjamin kepatuhan terhadap regulasi, serta mendukung pencapaian tujuan strategis universitas. Kata kunci: COBIT 2019; evaluasi TI; maturity level; tata kelola TI. 
Co-Authors AA Sudharmawan, AA Aang Alim Murtopo Abdullah Abdullah Adittia Agustian Afra, Alfina Fadhilah Ahnaf, Naufal Zubdi alzahra, alika aziza Angraeni, Rahmah Nur April Lia Hananto Aprilia Putri Nardilasari Arip Solehudin Asep Haris Aulia, Aldi Aviv Yuniar Rahman Baenil Huda Desfianthy, Fatiya Hanifah Diningrat, Cahya Fatlun, Aulia Fitria Nurapriani Florida Ivonia Manek Guntur, Muhamad Haerudin Haerudin Hananto, Agustia Handayani, Citra Heryana, Nono Hilabi, Shofa Shofia Hilabi, Shofa Shofia Hilabi, Shofa Shofiah Hoerudin Hoerudin Huda, Baenil Intan, Melani Ismail, Dennisa Avriel Jabar Sanjaya Julia, Ina Julifer P Manurung Juniardi Kurniawan, Muhamad Dicky Lutfiah, Siti Mohamad Ricky Firdaus Muhammad Nova Novalia, Elfina Nurapriani, Fitria Paryono, Tukino Pradana Rizki Maulana Reswara, Hadaya Abhista Rini Mayasari Sabrina Amanda Salsabila Saepul Aripiyanto Sari, Fitria Ratna Setiawan, Revi Shofa Shofia Hilabi Shofa Shofia Hilabi Shofa Shofiah Hilabi Shofia Hilabi, Shofa Sifa, Sifa Rismawati Siregar, Amril Mutoi Siti Masruroh Siti Masruroh Sutan Faisal Syahri Susanto Tatang Rohana Teresa Abuya Topan Setiawan Topan Trianto Tukino tukino, tukino Tukino, Tukino Tukino, Tukino Wahyu Aziz Ramadhani Yazid, Muhammad Abi Zahra, Nabila Zein, Selmia Aulia Zhalifunas, Satria Dawas