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All Journal Jurnal Ilmiah Informatika Komputer Jurnal Informatika dan Teknik Elektro Terapan InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JIKO (Jurnal Informatika dan Komputer) Information System for Educators and Professionals : Journal of Information System JITK (Jurnal Ilmu Pengetahuan dan Komputer) KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer Jurnal Teknik Informatika UNIKA Santo Thomas JOURNAL INFORMATICS, SCIENCE & TECHNOLOGY Jurnal ICT : Information Communication & Technology Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Jurnal Informatika dan Rekayasa Perangkat Lunak JATI (Jurnal Mahasiswa Teknik Informatika) MEANS (Media Informasi Analisa dan Sistem) Instal : Jurnal Komputer Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Journal of Artificial Intelligence and Engineering Applications (JAIEA) AMMA : Jurnal Pengabdian Masyarakat Jurnal Informatika: Jurnal Pengembangan IT Informasi interaktif : jurnal informatika dan teknologi informasi
Ade Rizki Rinaldi
STMIK IKMI Cirebon
Humanities Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing Other

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Clustering Data Penjualan Produk Makanan pada Toko Toserba Yogya Siliwangi dengan Menggunakan Metode K-Means Noviati; Mulyawan; Kurnia, Dian Ade; Rinaldi, Ade Rizki
MEANS (Media Informasi Analisa dan Sistem) Volume 7 Nomor 1
Publisher : LPPM UNIKA Santo Thomas Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (874.498 KB) | DOI: 10.54367/means.v7i1.1850

Abstract

Product availability is one of the important factors to increase sales and maintain customer satisfaction in meeting their needs. With this, the company needs to analyze sales data, both for the best-selling products or those that are not selling well from sales reports every month, especially for food products. Of course, this is not easy, especially for a large enough retailer such as the Yogya Siliwangi Toserba which has thousands of product items and thousands of sales data every month. The above problems can be solved by grouping the data using the k-means clustering algorithm on rapidminer with variables taken by the name of goods, incoming goods, outgoing goods and stock. The goal is to maximize sales and maintain product stock availability to meet the diverse needs of consumers. From the calculation of the k-means algorithm using the rapidminer application, the results obtained are in the form of three clusters, cluster_1 3 items, cluster_2 13 items and cluster_0 454 items with Devies Bouldin results being 0.478.
Pengembangan Layanan Informasi Akademik Menggunakan Metode Aglie Hartati, Tuti; Hayati, Umi; Basysyar, Fadhil M.; Rinaldi, Ade Rizki
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 6 No. 2 : Tahun 2021
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (326.996 KB) | DOI: 10.54367/jtiust.v6i2.1477

Abstract

Informasi perkembangan akademis biasanya hanya dapat diperoleh oleh wali murid pada saat pembagian raport, sehingga sulitnya orang tua dalam memantau kemajuan akademik anak-anak mereka setiap saat. Sedangkan saat ini orang tua sudah paham dengan perkembangkan alat komunikasi. Demikian pula, pihak sekolah sudah memiliki koneksi internet dan memanfaatkan dari kemajuan teknologi informasi untuk pengolahan data akademik. Oleh karena itu, muncullah gagasan untuk merancang suatu media informasi yang dapat dipergunakan pada smartphone dengan berbasis android. Aplikasi android ini dirancang dengan menggunakan metode aglie dengan pendekatan berorientasi objek di mana pengembangan perangkat dilakukan secara berurutan dari fase perencanaan, pemodelan, implementasi, dan pengujian. Kemudian aplikasi ini dibuat menggunakan PHP & HTML untuk sisi server sedangkan sisi client aplikasi dibuat menggunakan android studio untuk membangun aplikasi berbasis android. Dengan adanya aplikasi ini, sekolah memiliki media informasi perkembangan akademika siswa yang dapat membantu orang tua siswa dalam mengawasi perkembangan putra-putrinya.
KLASTERISASI DATA PRODUKSI PERTANIAN DI KABUPATEN CIREBON DENGAN ALGORITMA K-MEANS Septianto, Muhamad Arif; Faqih, Ahmad; Rinaldi, Ade Rizki
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 2 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i2.6174

Abstract

Kabupaten Cirebon merupakan salah satu daerah pertanian terpenting di Indonesia yang memiliki potensi besar di sektor pertanian. Namun pengelolaan data produksi pertanian di daerah ini sering kali tidak optimal sehingga mengakibatkan rendahnya efisiensi dan strategi pengelolaan sumber daya yang kurang tepat. Oleh karena itu, penelitian ini bertujuan untuk menerapkan algoritma K-Means dalam mengelompokkan data produksi pertanian berdasarkan hasil panen dari 40 kecamatan di Kabupaten Cirebon. Metode Knowledge Discovery in Database (KDD) digunakan dalam penelitian ini, meliputi tahap pemilihan data, preprocessing, transformasi, data mining, dan evaluasi hasil cluster. Data yang dianalisis meliputi hasil panen dari tiga komoditas utama, yaitu padi, jagung, dan melinjo. Hasil analisis menunjukkan bahwa data dapat dibagi menjadi empat klaster optimal dengan nilai Davies-Bouldin Index (DBI) sebesar 0,324, yang mengindikasikan bahwa klaster yang terbentuk memiliki kualitas yang baik. Setiap klaster mencerminkan karakteristik produksi yang berbeda-beda di setiap wilayah. Beberapa daerah menunjukkan keunggulan dalam hasil jagung, sementara daerah lain lebih unggul dalam memproduksi padi atau melinjo. Selain itu, terdapat daerah-daerah dengan tingkat produktivitas yang relatif rendah, yang membutuhkan lebih banyak perhatian dalam mengembangkan sektor pertanian. Temuan-temuan ini memberikan wawasan penting dalam merancang pengelolaan sektor pertanian yang lebih efisien dan berbasis data.
PENERAPAN METODE K-MEANS CLUSTERING DALAM PEMETAAN KEMISKINAN KABUPATEN/KOTA DI INDONESIA UNTUK PERENCANAAN KEBIJAKAN YANG TEPAT Amelia, Mita; Faqih, Ahmad; Rinaldi, Ade Rizki
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 2 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i2.6231

Abstract

Kemiskinan merupakan tantangan serius yang memerlukan pendekatan strategis berbasis data untuk mendukung kebijakan yang tepat sasaran. Penelitian ini bertujuan untuk mengelompokkan Kabupaten/Kota di Indonesia berdasarkan tingkat kemiskinan menggunakan algoritma K-Means dan mengevaluasi hasil pengelompokan untuk memberikan rekomendasi kebijakan. Metode analisis yang digunakan adalah Knowledge Discovery in Database (KDD) Process, yang melibatkan seleksi data, pra-pemrosesan, transformasi, penambangan data, dan evaluasi. Hasil analisis menunjukkan bahwa nilai k terbaik adalah 2 dengan nilai Davies-Bouldin Index sebesar 0,101. Klaster pertama (Cluster 0) mencakup wilayah dengan persentase penduduk miskin lebih rendah, rata-rata lama sekolah lebih tinggi, serta kondisi sosial ekonomi yang lebih baik dibandingkan klaster kedua. Sebaliknya, klaster kedua (Cluster 1) menunjukkan wilayah dengan tingkat kemiskinan signifikan, pendidikan rendah, dan minim infrastruktur dasar. Hasil penelitian ini menunjukkan bahwa pengelompokan menggunakan algoritma K-Means mampu mengidentifikasi wilayah prioritas untuk penanganan kemiskinan. Visualisasi klaster dan analisis karakteristik wilayah dapat mendukung perumusan kebijakan yang lebih efektif, terutama dalam peningkatan pendidikan, kesehatan, dan pengembangan infrastruktur.
Analisis Data Hasil Laporan Skripsi Berbasis Aspect Based Sentiment Analysis Menggunakan Algoritma K-Means Clustering Nana Suarna; Dadang Sudrajat; Umi Hayati; Ade Rizki Rinaldi; Agus Bahtiar
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

This study discusses the application of Aspect-Based Sentiment Analysis (ABSA) combined with the K-Means Clustering algorithm to analyze student thesis report data. The research scope includes text data processing from VAK (Visual, Auditory, Kinesthetic) learning style questionnaires to identify research aspects and automatically group thesis themes. The objective is to obtain a structured and representative mapping of students’ research themes based on their fields of study. The methodology involves several stages, including text preprocessing, TF-IDF weighting, aspect extraction using ABSA, and clustering with K-Means, validated through the Davies-Bouldin Index (DBI). The dataset consists of 976 textual entries derived from student questionnaire responses. The results indicate that the optimal cluster is achieved at k = 3 with a DBI value of 3.276, forming three main groups: (1) data mining, (2) statistical analysis, and (3) learning technology. The study concludes that the combination of ABSA and K-Means is effective in accurately classifying research themes and provides an analytical foundation for academic decision-making regarding student research trends.
Klasifikasi Telur Fertil dan Infertil Berbasis Hybrid MobileNetV3 dengan Mekanisme Attention dan Texture Fusion Bani Nurhakim; Dadang Sudrajat; Tati Suprapti; Ade Rizki Rinaldi; Agus Bahtiar
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Accurate fertile-infertile egg classification is crucial to improve hatching productivity and sorting efficiency. This study proposes MobileFusionV3, a MobileNetV3 architecture enriched with CBAM (Convolutional Block Attention Module) and Hybrid Texture Fusion (LBP and GLCM) to combine deep and texture features to be more robust to candling illumination variations. A dataset of 1,275 candling images (675 fertile, 600 infertile) was subjected to preprocessing (resizing, normalization, background enhancement) and realistic data augmentation (rotation, brightness/contrast changes, Gaussian noise, illumination variations). The model was trained using transfer learning, early stopping, and an evaluation scheme based on accuracy, precision, recall, F1-score, and AUC. The test results showed an accuracy of 97.2%, precision of 96.8%, recall of 97.5%, F1 of 97.1%, and AUC of 0.99, surpassing previous designs that did not use attention mechanisms and texture fusion. Grad-CAM++ analysis confirms the model's focus on physiologically relevant regions (embryonic shadow and air-cell), thus improving the reliability of interpretation. These findings indicate that lightweight, efficient designs based on attention and texture fusion have the potential to be implemented in smart hatchery systems and edge/mobile devices while maintaining high accuracy.
Mengoptimalkan Kinerja Naïve Bayes Pada Ancaman Modern Dengan Menggunakan PCA Pada Data Intrusion Detection System (IDS) Kevin Salsabil Arlandy; Ahmad Faqih; Ade Rizki Rinaldi
Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Vol 8, No 1 (2025): Januari
Publisher : Akademi Ilmu Komputer Ternate

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47324/ilkominfo.v8i1.303

Abstract

Abstrak: Intrusion Detection System (IDS) digunakan untuk mendeteksi serangan atau aktivitas mencurigakan dalam jaringan. Dengan meningkatnya ancaman siber modern, penelitian ini mengusulkan kombinasi metode Naïve Bayes dan Principal Component Analysis (PCA) untuk meningkatkan akurasi dan efisiensi deteksi. Metode tambahan PCA dapet mereduksi dimensi dataset menjadi 30 komponen utama tanpa kehilangan informasi penting, menggunakan dataset UNSW-NB15. Proses melibatkan standarisasi data dengan StandardScaler, reduksi dimensi menggunakan PCA, serta evaluasi model Naïve Bayes pada dataset dengan dan tanpa PCA. Analisis ini menggunakan program Python yang di eksekusi dengan Google Collab, dengan hasil menunjukkan bahwa model dengan PCA mencapai akurasi sebesar 96.65% dengan recall 1.00 untuk kelas ancaman, meskipun presisi masih rendah (0.49). Sebaliknya, tanpa PCA, akurasi hanya mencapai 92.72% dengan presisi 0.31 untuk kelas yang sama. Selain itu, penggunaan PCA berhasil mengurangi waktu komputasi dari 1 menit menjadi 30 detik. Kombinasi dengan teknik reduksi dimensi Principal Component Analysis (PCA) menunjukkan kinerja yang lebih baik dalam mengklasifikasikan data pada sistem Intrusion Detection System (IDS). PCA dan Naïve Bayes terbukti menjanjikan dalam mendeteksi ancaman modern, meskipun masih diperlukan perbaikan untuk mencapai kinerja yang lebih optimal.Kata kunci: Intrusion Detection System, Naïve Bayes, PCA, Keamanan JaringanAbstract:An Intrusion Detection System (IDS) is used to detect attacks or suspicious activities in the network. With the increase of modern cyber threats, this research proposes a combination of Naïve Bayes and Principal Component Analysis (PCA) methods to improve detection accuracy and efficiency. The additional PCA method can reduce the dataset dimension to 30 principal components without losing important information, using the UNSW-NB15 dataset. The process involves data standardization with Standard-Scaler, dimensionality reduction using PCA, and Naïve Bayes model evaluation on the dataset with and without PCA. This analysis used a Python program executed with Google Collab, with the results showing that the model with PCA achieved an accuracy of 96.65% with a recall of 1.00 for the threat class. However, the precision was still low (0.49). In contrast, without PCA, the accuracy only reached 92.72% with a precision of 0.31 for the same class. In addition, the use of PCA successfully reduced the computation time from 1 minute to 30 seconds combination with the Principal Component Analysis (PCA) dimension reduction technique shows better performance in classifying data in the Intrusion Detection System (IDS). PCA and Naïve Bayes proved promising in detecting modern threats, although improvements are still needed to achieve more optimal performance.Keywords: Intrusion Detection System, Naïve Bayes, PCA, Network Security
Diversifikasi Produk Dan Strategi Digital Marketing Bagi UMKM Oemah Singkong Untuk Daya Saing Berkelanjutan Ade Rizki Rinaldi; Sandy Eka Permana; Ahmad Najib Yahya; Luthfi Adianto
AMMA : Jurnal Pengabdian Masyarakat Vol. 3 No. 2 : Maret (2024): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

This community service program aims to enhance the competencies of vocational high school (SMK) students in web development through Junior Web Developer training. The activities were carried out at several SMKs in Cirebon Regency and Cirebon City as an effort to bridge the gap between school curricula and industry needs. The implementation methods included preparation and planning, training execution, monitoring and evaluation, as well as dissemination of results. The outcomes of this program showed a significant improvement in students’ understanding and skills in web development technologies, particularly in the use of HTML, CSS, JavaScript, and modern frameworks. In addition, the participating teachers also benefited from workshops designed to enhance their ability to teach industry-based materials. This program successfully produced several outputs such as learning modules, student web projects, and collaborations with industry partners to open job opportunities for graduates. Through this program, it is expected that vocational students will be better prepared to face the workforce and the digital industry. The sustainability of this program can be expanded by increasing the number of industry partners and broadening the scope of training participants.
Pelatihan Operator Komputer Madya Untuk Meningkatkan Keterampilan Teknologi Tenaga Pendidik Pondok Pesantren Di Kabupaten Cirebon Ade Irma Purnama Sari; Ade Rizki Rinaldi; Ahmad Najib Yahya; Ainun Nisa Sari
AMMA : Jurnal Pengabdian Masyarakat Vol. 2 No. 2 (2023): AMMA : Jurnal Pengabdian Masyarakat (INPRESS)
Publisher : CV. Multi Kreasi Media

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Abstract

This Community Service Program aims to improve the technological skills of educators at Islamic boarding schools (Pondok Pesantren) in Cirebon Regency through Intermediate Computer Operator Training. The main problem faced by educators is the limited knowledge and skills in operating computers, particularly in using office applications such as Microsoft Word, Excel, and PowerPoint. This condition affects the efficiency of pesantren administration and limits the utilization of technology in the learning process. This program was carried out through several stages, including needs identification, preparation of training materials, hands-on practice, evaluation, and mentoring. The materials provided covered basic computer operation, document management, data processing, digital presentation creation, and digital data management of students. The results of the training showed a significant improvement in participants' skills, especially in using office applications and managing digital-based administration. Several pesantren have started to implement digital systems for recording student data, finances, and lesson schedules. In addition, educators are now able to create more attractive and interactive technology-based learning materials. The outputs of this activity include digital training modules, tutorial videos, evaluation reports, and the formation of a technology-based educator community. This program is expected to continue to develop so that educators in Islamic boarding schools are increasingly ready to face the challenges of digitalization in education and are able to improve the quality of administrative management and learning processes within the pesantren environment.
Peningkatan Literasi Digital Guru Sekolah Dasar Dalam Menghadapi Pembelajaran Daring Ade Rizki Rinaldi; Agus Bahtiar; Arga Esa Putra; Arunika Wijaya
AMMA : Jurnal Pengabdian Masyarakat Vol. 2 No. 2 (2023): AMMA : Jurnal Pengabdian Masyarakat (INPRESS)
Publisher : CV. Multi Kreasi Media

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Abstract

This Community Service Program aims to improve digital literacy for elementary school teachers in facing the challenges of online learning in the digital era. The rapid development of information and communication technology has brought significant changes to learning methods, including demands for teachers to master various digital platforms. However, in reality, many elementary school teachers still face limitations in using technology, both in terms of skills, access to devices, and strategies for delivering learning materials online. This program was implemented through a series of activities, including training, workshops, mentoring, and evaluation. The training materials focused on the use of online learning platforms such as Google Classroom, Zoom, Canva, and the creation of engaging and interactive digital learning materials. In addition, participants received guidance in overcoming technical obstacles and strategies for building effective communication with students in online learning. The results of this program showed a significant improvement in teachers' understanding and skills in operating educational technology. Teachers became more confident in designing and delivering digital-based learning, online classroom management improved, and student participation in the learning process increased. The outputs of this activity included a digital literacy guide module, tutorial videos on the use of online learning platforms, program activity reports, and the establishment of a knowledge-sharing community among teachers. This program is expected to support the transformation of technology-based education, improve the quality of online learning, and create educators who are more adaptive and creative in facing future technological developments.
Co-Authors Ade Irma Purnama Sari Ade Irma Purnamasari Agung Saeful agus bahtiar Ahmad Asyraful Hijrah Ahmad Faqih Ahmad Faqih Ahmad Najib Yahya Ahmad Syaeful Ma’arief Ainun Nisa Sari Alfi Rizqi Falih Aliya Anisa Rahma Amelia, Mita Amida, Anggi Fitria Arga Esa Putra Aria Pratama Arif Rinaldi Dikananda Arunika Wijaya Asep Budiyanto Aziz Chairul Imam Bani Nurhakim Basysyar, Fadhil Muhammad Bima Anurgraha Djajnegara Cep Lukman Rohmat Cep Lukman Rohmat Dadang Sudrajat Dea Miftahul Huda Dian Ade Kurnia Dikananda, Arif Rinaldi Dodi Solihudin Edi Tohidi Fathrurrahman Fathurrohman Fathurrohman Fidya Arie Pratama Gifthera Dwilestari Hayati, Umi Heliyanti Susana Hery Widijanto Iin Iin Solihin Iin, Iin Indah Diniarti Indah Ratna Ningsih Irfan Ali Irma Agustina Jayawarsa, A.A. Ketut Kevin Salsabil Arlandy Kurnia, Dian Ade Lana Surlanto Luthfi Adianto Muhamad Abdurohman Muhamad Aditya Sunaryo Mulyawan Mulyawan Mulyawan, Mulyawan Nana Suarna Narasati, Riri Narasati Nining Rahaningsih Noviati Odi Nurdiawan Odi Nurdiawan Permana, Sandy Eka Pratama, Denni Pratama, Fidya Arie Raditya Danar Dana Ryan Hamonangan Sandy Eka Permana Septianto, Muhamad Arif Syarif Maulana Yaasin Tati Suprapti Tineka Handayani Tohidi, Edi Tuti Hartati Umi Hayati Wahyu Saputra Willy Prihartono