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All Journal JURNAL SISTEM INFORMASI BISNIS EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi CESS (Journal of Computer Engineering, System and Science) JURNAL PENGABDIAN KEPADA MASYARAKAT Jurnal Ilmiah KOMPUTASI Sistemasi: Jurnal Sistem Informasi Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JURNAL MEDIA INFORMATIKA BUDIDARMA SMARTICS Journal Indonesian Journal of Artificial Intelligence and Data Mining IJIS - Indonesian Journal On Information System JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Teknik Informatika UNIKA Santo Thomas JurTI (JURNAL TEKNOLOGI INFORMASI) Jiko (Jurnal Informatika dan komputer) ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA JISTech (Journal of Islamic Science and Technology) JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Teknologi Sistem Informasi dan Aplikasi IJISTECH (International Journal Of Information System & Technology) JOURNAL OF SCIENCE AND SOCIAL RESEARCH Simtek : Jurnal Sistem Informasi dan Teknik Komputer Jurnal Dedikasi Pendidikan Jurnal Teknologi Terpadu EDUMATIC: Jurnal Pendidikan Informatika METIK JURNAL Jurnal Mantik Progresif: Jurnal Ilmiah Komputer Jurnal Ilmiah Sains dan Teknologi (SAINTEK) Zonasi: Jurnal Sistem Informasi Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jatilima : Jurnal Multimedia Dan Teknologi Informasi Journal of Intelligent Decision Support System (IDSS) G-Tech : Jurnal Teknologi Terapan JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) INFOKUM Jurnal Sistem Komputer dan Informatika (JSON) TIN: TERAPAN INFORMATIKA NUSANTARA Brahmana : Jurnal Penerapan Kecerdasan Buatan Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Journal of Computer Networks, Architecture and High Performance Computing IJISTECH Journal La Multiapp Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Instal : Jurnal Komputer Jurnal Info Sains : Informatika dan Sains Decode: Jurnal Pendidikan Teknologi Informasi Simpatik: Jurnal sistem Informasi dan Informatika Journal of Dinda : Data Science, Information Technology, and Data Analytics Jurnal IPTEK Bagi Masyarakat Jurnal Mandiri IT Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Journal of Computer Science and Informatics Engineering Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Algoritma Edu Society: Jurnal Pendidikan, Ilmu Sosial dan Pengabdian Kepada Masyarakat Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) SENTRI: Jurnal Riset Ilmiah Malcom: Indonesian Journal of Machine Learning and Computer Science STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer SmartComp Jurnal Ilmu Komputer dan Sistem Informasi VISA: Journal of Vision and Ideas Da'watuna: Journal of Communication and Islamic Broadcasting Future Academia : The Journal of Multidisciplinary Research on Scientific and Advanced The Indonesian Journal of Computer Science Teknologi : Jurnal Ilmiah Sistem Informasi
Rakhmat Kurniawan R
Universitas Islam Negeri Sumatera Utara
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The Implementation of Digital Image Steganography in Identifying the Originality of Digital Certificates Using the Least Significant Bit (LSB) Method Kurniawan R, Rakhmat; Sriani; Ibsan, Muhammad Hanafi
Bahasa Indonesia Vol 15 No 02 (2023): Instal : Jurnal Komputer Periode (Juli-Desember)
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalkomputer.v15i02.130

Abstract

Technological developments mean that data and information are presented in digital form, such as the use of digital certificates. Digital certificates are widely used by agencies that hold online seminars or training, so seminar participants will be given digital certificates. The large number of uses of digital certificates can influence the misuse of these certificates by counterfeiting digital certificates, so it is necessary to secure digital certificate data using steganography. Steganography is not only used to hide information, but also to protect copyright and the authenticity of an image. The hidden secret data is in the form of images, audio, text or video. The image steganography process is carried out using the Least Significant Bit (LSB) method. LSB works by replacing the original image bits with information bits that will be hidden. LSB is a method that can be applied in cases of identifying the authenticity of digital certificates because the image of a digital certificate that has undergone steganography does not change much of the original image and cannot even be distinguished by the naked eye. However, LSB cannot be used on jpg format data, this is because LSB is unable to extract messages that have been inserted into digital certificate images in jpg format.
Sistem Pendukung Keputusan Penerima Bantuan Usaha Mikro Menggunakan Metode AHP dan SAW Berbasis Web Harahap, Nita Maharani; Kurniawan R, Rakhmat; Sinaga, Imam Adlin
JISTech (Journal of Islamic Science and Technology) Vol 10, No 1 (2025)
Publisher : UIN Sumatera Utara Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/jistech.v10i1.24159

Abstract

Peran masyarakat dalam pembangunan nasional, khususnya dalam pembangunan ekonomi, adalah Usaha Mikro, Kecil dan Menengah (UMKM). UMKM juga terbukti menyerap tenaga, dengan banyaknya pekerja yang terserap, sektor UMKM mampu meningkatkan pendapatan masyarakat. Pemerintah Kabupaten Padang Lawas Utara sudah sejak lama menggalakkan bantuan dana untuk pelaku UMKM khususnya usaha mikro agar terus berkembang, dan berinovasi. Akan tetapi, pemerintah mengalami beberapa kendala untuk mementukan prioritas usaha mikro yang memang layak untuk mendapatkan bantuan. Dalam menentukan prioritas usaha mikro yang layak mendapatkan bantuan pemerintah Kabupaten Padang Lawas Utara masih dilakukan secara manual dengan melakukan pemilihan secara acak usaha mana yang akan diberi bantuan.  Dengan cara tersebut, dana bantuan yang diberikan tidak tepat sasaran. Penelitian ini bertujuan untuk  membantu pemerintah Kabupaten Padang Lawas Utara dengan membangun sebuah sistem yang dapat memudahkan tim penyeleksi dalam menentukan prioritas pemberian bantuan untuk usaha mikro berdasarkan kriteria yang telah ditentukan. Penelitian ini menggunakan metode R&D (Reach and Developmenth) yang digunakan untuk menghasilkan produk tertentu, dan menguji keefektifan produk. Untuk melakukan analisis dan perencanaan sistem yang menyeluruh, diperlukan pemodelan sistem terdiri dari Use Case Diagram, Activity Sequence Diagram dan Class Diagram. Penelitian ini menghasilkan sebuah sistem pendukung keputusan dengan menggunakan kombinasi dari metode AHP dan SAW. Sistem ini memiliki beberapa fitur, diantarnya fitur kamera yang memungkinkan untuk melakukan perankingan terhadap usaha mikro yang layak untuk mendapatkan bantuan.
Clustering pada Sistem Informasi Pengaduan Masyarakat Fitur Geolokasi untuk Penanganan Kasus Kriminal Syarifudin, Zaini; Rakhmat Kurniawan R; Triase, Triase
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 1 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v9i1.1035

Abstract

The increasing crime rate in Medan City required structured handling and analysis efforts to prevent and reduce crime. This study aimed to group areas in Medan City based on crime rates using the K-Means Clustering algorithm. The data used were obtained from the Medan Police in 2021, covering various types of crimes in 14 sub-districts. The method applied was K-Means Clustering with 3 clusters to group areas based on crime rates, with the geolocation feature in the analysis system enhancing the accuracy of grouping and identifying crime patterns. The clustering process was carried out through two iterations, where the second iteration showed a more optimal ratio (0.0894) compared to the first iteration (0.0799). The analysis results showed the formation of three groups of areas, namely: the first cluster (high crime rate) included the Criminal Investigation area, the second cluster (moderate crime rate) covered 8 sub-districts, and the third cluster (low crime rate) consisted of 5 sub-districts. The results of this grouping could be used by Polrestabes Medan as a reference for allocating security resources and developing crime prevention strategies tailored to the characteristics of each region. This study proved that the K-Means algorithm was effective in analyzing and grouping regions based on crime rates.
Sistem Informasi Inventory Barang Pada CV. Delta Power Listrindo Menggunakan Metode Buffer Stock dan Reorder Point (ROP) Bisri, Cholil; Kurniawan, Rakhmat
SMARTICS Journal Vol 11 No 1 (2025): SMARTICS Journal (April 2025)
Publisher : Universitas PGRI Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/smartics.v11i1.11886

Abstract

The inventory information system is a system that is very necessary and must be owned by a business agency and company. This system uses the buffer stock and reorder point (ROP) method which functions to predict the stock of goods and the amount of reordering goods. The information system used is a website that functions to improve the efficiency and effectiveness of stock management to improve accuracy and save operational costs in the company. CV. Delta Power Listrindo is a company engaged in the production and provision of electrical products both in industry and housing. This can make it easier for an agency and company to manage stock. The system also contains data on incoming goods reports, outgoing goods and data on goods submission reports that can be printed and used for backup data that can be stored by the company. Therefore, with this system, the company is expected to be able to reduce the risk of shortages or excess stock and improve the quality and quantity of service to customers and minimize errors.
Penerapan Naive Bayes Classifier untuk Prediksi Kelayakan Penerima Bantuan Program Indonesia Pintar (PIP) Hidayat, Zulfy; Kurniawan. R, Rakhmat
EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Vol 15, No 1 (2025): June
Publisher : Universitas Bandar Lampung (UBL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/expert.v15i1.4326

Abstract

Penelitian ini dilatarbelakangi oleh ketidaktepatan dalam proses seleksi manual penerima bantuan Program Indonesia Pintar (PIP) di MTs Al-Hasanah, yang belum berbasis data objektif sehingga berpotensi menyalurkan bantuan tidak tepat sasaran. Berdasarkan masalah tersebut, rumusan penelitian ini adalah bagaimana penerapan algoritma Naïve Bayes dalam meramalkan kelayakan siswa sebagai penerima bantuan PIP, serta seberapa akurat metode ini dalam proses prediksi. Tujuan dari penelitian ini adalah untuk membangun model klasifikasi berbasis Naïve Bayes yang mampu memprediksi kelayakan siswa penerima bantuan berdasarkan atribut seperti status keluarga, kepemilikan KIP, jumlah tanggungan, dan penghasilan orang tua. Model dikembangkan menggunakan pendekatan data mining dengan algoritma Naïve Bayes pada platform Google Colab, dengan preprocessing menggunakan teknik Label Encoding dan pembagian data dengan rasio 80:20, menghasilkan 84 data latih dan 21 data uji. Hasil evaluasi menunjukkan nilai akurasi, presisi, recall, dan F1-score sebesar 1.0 atau 100%. Kinerja sempurna ini menunjukkan keberhasilan model dalam mengklasifikasikan seluruh data uji secara tepat. Namun demikian, nilai metrik yang sangat tinggi juga mengindikasikan potensi overfitting, mengingat ukuran dataset yang terbatas dan homogenitas data yang digunakan. Oleh karena itu, generalisasi model terhadap data yang lebih luas belum dapat dipastikan. Penelitian ini bermanfaat dalam mendukung pengambilan keputusan berbasis data dalam distribusi bantuan PIP secara lebih objektif dan adil, serta menjadi kontribusi awal dalam pengembangan sistem berbasis kecerdasan buatan untuk sektor pendidikan.
Analisis Sentimen Komentar Terhadap Kebijakan Pemerintah Mengenai Tabungan Perumahan Rakyat (TAPERA) Pada Aplikasi X Menggunakan Metode Naïve Bayes Eva Darwisah Harahap; Kurniawan, Rakhmat
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 9 No. 1 : Tahun 2024
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Sekarang ini masyarakat Indonesian telah di hebohkan dengan kebijakan terbaru pemerintah yaitu TAPERA, awal pembentukan tapera yaitu 15 februari 1993 sebelum namanya yang saat ini tapera dulu di kenal dengan nama Badan Pertimbangan Tabungan Perumahan Pegawai Negeri Sipil (BAPERTARUM-PNS), dan melalui pengumuman resmi di berbagai media pada tanggal 24 maret 2018 BAPERTARUM-PNS[1] pada kasus ini algoritma naïve bayes adalah metode yang di gunakan untuk melakukan klasifikasi pada penelitian ini, karena metode ini dapat mengelompokkan komentar komentar yang bersifat positif dan negatif, implementasi sistem menggunakan bahasa pemrograman python dengan menggunaka google collab, kesimpulan dari hasil penelitian ini menerangkan bahwasanya metode naïve bayes berhasil di terapkan pada pengelompokan kalimat positif dan negatif dengan mendapatkan hasil akurasi pada matriks yang behasil di jalankan pada sistem yang telah di buat
Analisis Sentimen Komentar Terhadap Kebijakan Pemerintah Mengenai Tabungan Perumahan Rakyat (TAPERA) Pada Aplikasi X Menggunakan Metode Naïve Bayes Eva Darwisah Harahap; Kurniawan, Rakhmat
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 9 No. 1 : Tahun 2024
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Sekarang ini masyarakat Indonesian telah di hebohkan dengan kebijakan terbaru pemerintah yaitu TAPERA, awal pembentukan tapera yaitu 15 februari 1993 sebelum namanya yang saat ini tapera dulu di kenal dengan nama Badan Pertimbangan Tabungan Perumahan Pegawai Negeri Sipil (BAPERTARUM-PNS), dan melalui pengumuman resmi di berbagai media pada tanggal 24 maret 2018 BAPERTARUM-PNS[1] pada kasus ini algoritma naïve bayes adalah metode yang di gunakan untuk melakukan klasifikasi pada penelitian ini, karena metode ini dapat mengelompokkan komentar komentar yang bersifat positif dan negatif, implementasi sistem menggunakan bahasa pemrograman python dengan menggunaka google collab, kesimpulan dari hasil penelitian ini menerangkan bahwasanya metode naïve bayes berhasil di terapkan pada pengelompokan kalimat positif dan negatif dengan mendapatkan hasil akurasi pada matriks yang behasil di jalankan pada sistem yang telah di buat
Classification eligibility recipient BPJS in ward sendang sari using the naive bayes method Prayoga, Dio; Kurniawan, Rakhmat
Jurnal Mandiri IT Vol. 14 No. 1 (2025): July: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i1.405

Abstract

Study This done for classify eligibility BPJS recipients in the sub-district Sendang Sari with use Naive Bayes method, which is relevant in support transparency and efficiency distribution benefit guarantee social at the level sub-district. Problems main in study This is Still its use manual system in the classification process, which causes the decision-making process decision become slow, subjective and vulnerable error. Research methods involving collection of 1000 citizen data Ward Sendang Sari which consists of from attributes like type gender, employment status, ownership house, income, and amount liability. Data then through preprocessing stage, including conversion variable categorical use LabelEncoder and determination of eligibility labels based on threshold income and amount liability. Next, the data is divided into training data and test data with 80:20 ratio. Classification model built use Gaussian Naive Bayes algorithm and evaluated use confusion matrix metrics which include accuracy, precision, and recall. Evaluation results show that the model achieves accuracy of 0.97 or 97%, precision of 0.95 or 95%, and recall of 0.90 or 90%, and F1-Score of 0.93 or 93 % which to signify that this model Enough effective For classify eligibility BPJS recipients. Research This conclude that The Naive Bayes method is capable of give accurate and consistent classification, which can increase efficiency administration ward as well as speed up distribution benefit to entitled community.
Port Risk Mitigation with FMEA Method on Port Operational Information System at PT. Pelindo (Persero) Sibolga Branch: Case Study at Port of Sibolga Novita Jambak, Indah; Kurniawan R, Rakhmat
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 9 No. 1 (2025): Issues July 2025
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v9i1.15400

Abstract

Port operations face challenges in the form of potential risks such as delays in data recording, data inconsistencies between units, and lack of system integration that can hinder logistics distribution. This study identified 20 potential operational risks using the Failure Mode and Effect Analysis (FMEA) method to help map mitigation priorities through the calculation of the Risk Priority Number (RPN). The results of the risk mapping were used as a basis for designing the functional requirements of a web-based port operational information system. The system was developed using PHP, Laravel, and MySQL to support structured recording of loading and unloading activities, ship scheduling, and logistics monitoring. Although the RPN values were used to understand risk priorities, they did not directly determine the system features. Instead, the risk analysis served to provide an overall understanding for designing a system that better matches operational needs. The validation of system benefits at this stage remains conceptual, and future implementation is needed to test its effectiveness in actual port operations.
Sentiment analysis towards naturalization of Indonesian National Team Players on social media x using the Naive Bayes method Lubis, Fahrian Zibran; Kurniawan, Rakhmat
Jurnal Mandiri IT Vol. 14 No. 1 (2025): July: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i1.412

Abstract

This study analyzes public sentiment toward naturalized players in the Indonesian National Team on social media platform X (formerly Twitter) using the Naïve Bayes method. Data were collected via Python's snscrape library through web crawling, encompassing 700 tweets from January 2023 to May 2024. The research methodology included data preprocessing (cleaning, case folding, tokenizing, stopword removal, and stemming), feature extraction with TF-IDF (Term Frequency-Inverse Document Frequency), and sentiment classification. Results revealed a dominant negative sentiment (87.5%) compared to positive sentiment (12.5%), with a model accuracy of 88%. The most frequent keyword, "main" (play), reflected public focus on player performance.The study contributes to the field in three key aspects: (1) It addresses a gap in literature by specifically examining sentiment toward naturalization policies in Indonesian football using social media data; (2) It demonstrates the effectiveness of Naïve Bayes in handling informal Indonesian language, achieving high accuracy despite linguistic complexities; (3) It provides actionable insights for policymakers, highlighting the need for greater transparency in naturalization processes. Limitations include potential bias due to imbalanced data and challenges in interpreting sarcasm. Recommendations for future research include expanding datasets to multiple platforms and testing advanced models like BERT for improved contextual analysis.
Co-Authors Abdul Halim Hasugian Adnan Buyung Nasution Agung Firmansyah Agung Pratama Ahmad Fauzi Ahmad Taufik Al Afkari Siahaan Aidil Halim Aidil Halim Lubis Aidil Halim Lubis Aidil Halim Lubis Alhafiz, Akhyar Alwy Azyari Harahap Amanda Zachra Harahap Amelia, Dara Andre Gusli Agus Riadi Armansyah Armansyah Armansyah Armansyah Arrafiq, Muhammad Sunni Asnawi, Azi Ayyina, Ayyina Nurhidayah Azhari, Fajar Bahari, Mhd Raja Doly Bayhaqi, Abdullah Bisri, Cholil Br Rambe, Indri Gusmita Dandi, Muhammad Khairil Dasopang, Buyung Satrio Dian Putri Kinanti Dimas Andrean Andrean Dwisyahputra, Achmad Adbillah Eva Darwisah Harahap Fadhlun Nazry Luthfy Fadiga, Muhammad Fahmi Maulana Fahrul Afandi Fakhriyah, Mardhiyah Fakhrizal, Fiqri Fatwa, Nursalimah Isnaina Fikri Aulia Habibie, Alief Fathul Haliem, Alexander Hanafi, Muhammad Rizky Harahap, Nita Maharani Harahap, Rina Syafiddini Harahap, Shopiah Henni Melisa Hidayat, Zulfy Hidayatullah, Catur HP, Kiki Iranda Hsb, Khoiri Sutan Ibsan, Muhammad Hanafi Ilham Rizki Ananda Ilka Zufria Imam Sodik Imam Zaki Husein Nst Indah Wahyuni, Utari Ivan Prayuda Julianti, Miranda Jusli, Dara Taqa Assajidah Kesuma Dwi Ningtyas Khairin Nadia Khairunissabina, Khairunissabina Khoiriah, Miftahul Krisdantoro, Rino Lubis, Fahrian Zibran Lubis, Farhan Rusdy Asyhary M Haziq Annabil M. Teguh wijaya Masdaliva, Fita Meilina, Indah Mey Hendra Putra Sirait Mhd Furqan Mhd Furqan Mhd. Furqan Furqan Mhd.Furqan Mohd. Wildan Qasthari Muhammad Abi Muzaki Muhammad Fahri, Muhammad Muhammad Ikhsan Muhammad Ikhsan Aji Muhammad Rizki Madani Muhammad Siddik Hasibuan Muhammad Sowban Adilla Nasution, Fitri Handayani Nasution, Raihan Hafiz Noor Azizah Novita Jambak, Indah Nur Aini, Sakina Nurjanah, Trya Nurwana Nazla Saragih Padang, Bermiko Kasah Pravda, Michellia Delphi Isfahan Prayoga, Dio Prayoga, Hafizh Putri Hanifah Putri, Raissa Ramanda Rafli Bima Sakti Rahmad Syuhada Rahmatsyah Ananta Putra Ginting Raissa Amanda Putri Ramadhan, Alfan Ramadhan, Nuzul Ramadhan, Rio Fadli Ramadhan, Rizky Syahrul Reza Muhammad Rifansyah, Mhd. Roji Rifqi Alwanu Akmal Rina Filia Sari Rina Syafiddini Harahap Rini Halila Nasution Ritonga, Larasati Rince Pratita Rizki Ananda Putra Fajar Rizky Barus Rizky Pratama Putra Rudi Riyandi Salsabillah, Ayna Sandira, Sri Delwis Saragih, Khoirul Azmi Saragih, Rafif Aprizki Sari, Desliana Sihombing, Rizki Andika Silva Ukhti Filla Silvi Joya Arditna Br Bukit Sinaga, Imam Adlin Sinaga, Muhammad Nabil Siregar, Muharram Soleh Siti Afifah Siregar Siti Ayu Hadisa Siti Nurul Aini, Siti Nurul Siti Sarah Harahap Siti Sumita Harahap Sri Marwah Badrin Sriani Sriani Sriani Stephani Silalahi Suhardi Suhardi Suhardi Suhardi, Suhardi Sultan Azka El Husein Lubis Syahira, Melani Alka Syahputra, Pii Syahputra, Zidhane Syarifudin, Zaini Tbn, Ahmad Fauza Anshori Tri Asyura Mashuri Triase Triase Triase Triase, Triase Wahyu Kurniawan Wini Istya Sari Lubis Yahya, Arfigo YENI SAFITRI Yudha, Muhammad Yudha Pratama Zahron, Almeranda Haryaveda Nurul