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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 Simpatik: Jurnal sistem Informasi dan Informatika Journal of Dinda : Data Science, Information Technology, and Data Analytics Jurnal Mandiri IT Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) 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 International Journal of Science and Environment 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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Implementasi Algoritma Knuth Morris Pratt Dalam Pencocokan String Pada Kamus Indonesia–Korea Rakhmat Kurniawan R; Aidil Halim Lubis; Siti Ayu Hadisa
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 1 (2023): September 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i1.6149

Abstract

Currently, South Korean culture is very popular with many Indonesians, and the rapid development of Korean culture in Indonesia is currently very widespread and very popular. Many Indonesians even learn Korean to keep up with current trends, but due to the different structure of the language, learning Korean becomes more difficult for most people. The dictionary is an effective guide for translating foreign languages/terms. Conceptually, dictionaries are arranged alphabetically, along with explanations of definitions, uses or translations. This is also required for Indonesian to Hangul Korean translation. Many Indonesian-Korean dictionaries are currently published in printed form, but it is still difficult to use because users have to look up the meanings manually. We need practical and effective new media such as smartphone media. There are many algorithmic methods that can be used to create dictionary applications, one of which is using the Knuth Morris Pratt (KMP) algorithm. With this algorithm, every text to be translated is checked for word search and then a match is found with the appropriate word from the desired word. In this study, the final results of the study found differences in the use of the word hangul in formal and informal forms. In this study, the authors tested the application of the algorithm on an Android-based Indonesian-Korean dictionary application.
Prediksi Harga Tandan Buah Segar dengan Algoritma K-Nearest Neighbor Silvi Joya Arditna Br Bukit; Rakhmat Kurniawan R.
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 1 (2023): September 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i1.6818

Abstract

Palm oil and its derivative products are a source of foreign exchange for this country, because efforts are needed to maintain and develop the sustainability of palm oil as a potential natural resource. The company carries out statistical analysis on the factors inhibiting the previous month's harvest with a correction value of 5% – 12%. However, this kind of analysis still produces inaccurate prediction results, this is because the calculation process still involves estimation techniques from personal experience, looking at previous production patterns and other determining factors such as land area, principal amount and planting age. As a result, prediction targets often experience errors and production results are excessive or less than the target. Therefore, better predictive calculations are needed in determining palm oil production targets. Accurate predictions can help companies make decisions to increase production output. To carry out forecasting, it is necessary to apply the K-Nearest Neighbor Algorithm which can be used to predict palm oil prices in the future. Based on the results of data mining calculations using palm oil FFB prices from 2018 to 2023 (May 2023), it was concluded that the prediction of palm oil FFB prices in the 67th month (July 2023) had an accuracy level of 10,667 with k=3 and 19,200 with k=5.
Penerapan Text Mining Pada Sistem Rekomendasi Pembimbing Skripsi Mahasiswa Menggunakan Algoritma Naive Bayes Classifier di Program Studi Ilmu Komputer UIN Sumatera Utara Medan Kurniawan. R, Rakhmat; Ikhsan, Muhammad
The Indonesian Journal of Computer Science Vol. 12 No. 6 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i6.3500

Abstract

Penunjukan dosen pembimbing skripsi oleh program studi akan disesuaikan dengan rumpun keilmuan dosen dengan topik dari judul proposal skripsi mahasiswa. Selain rumpun keilmuan, program studi juga harus berusaha mendistribusikan dosen pembimbing secara proporsional, sehingga potensi terjadinya kelebihan beban kerja pada dosen pembimbing dapat dihindari. Hal ini berlaku untuk dosen pembimbing I dan dosen pembimbing II. Selanjutnya dirasa perlu melakukan penelitian untuk mengatasi masalah tersebut. Dengan harapan memudahkan pengelola program studi dalam menentukan Pembimbing Skripsi yang sesuai antara topik dengan keilmuan dosen. Selanjutnya mempercepat proses penentuan judul skripsi mahasiswa dan tentunya juga akan mempercepat proses penyelesaian studi mahasiswa strata 1. Maka dirancanglah sebuah sistem yang mampu merekomendasi dosen pembimbing yang sesuai dengan topik skripsi yang diajukan melalui teknologi text mining menggunakan algoritma NBC. Algoritma NBC mampu untuk mendeteksi topik yang ada pada suatu koleksi dokumen beserta besarnya kemunculan topik tersebut.
Implementasi Metode Canny dalam Sistem Penempatan Foto Kartu Identitas Siswa Otomatis Sodik, Imam; Kurniawan, Rakhmat
TIN: Terapan Informatika Nusantara Vol 6 No 11 (2026): April 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i11.9674

Abstract

The manual creation of student identity cards often encounters several challenges, including inaccurate photo placement, inconsistent sizing, and lengthy processing time. These issues reduce efficiency and result in non-uniform document outputs. This study aims to develop a client-side web-based system capable of detecting empty rectangular areas in identity card templates and automatically embedding student photos using OpenCV.js. The system applies the Canny Edge Detection method combined with contour analysis to identify empty box regions, while image interpolation techniques are used to proportionally adjust photo dimensions according to the detected area. Experimental results show that the proposed system has been successfully implemented and is capable of accurately detecting empty regions in high-quality documents. Based on evaluation using the Intersection over Union (IoU) method, the system achieves an average accuracy of 98.67%, indicating that the Canny method is effective in detecting photo areas. The automatic photo adjustment process produces proportionally correct and ready-to-use digital outputs. Therefore, the system improves efficiency, accuracy, and consistency in the student identity card creation process.
IMPLEMENTATION OF THE FUZZY TIME SERIES METHOD FOR FORECASTING BLOOD NEEDS IN THE INDONESIAN RED CROSS (PMI) MEDAN Rina Syafiddini Harahap; Rakhmat Kurniawan R
JIKO (Jurnal Informatika dan Komputer) Vol 7 No 2 (2024)
Publisher : Program Studi Teknik Informatika Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v7i2.8614

Abstract

The primary issue faced by PMI (Indonesian Red Cross) about blood requirements is often associated with insufficient blood supplies to satisfy the demand of patients, particularly during emergencies or significant catastrophes such as natural calamities. Hence, it is essential to use appropriate methodologies to forecast blood requirements accurately and determine the quantity of blood bags required in the future. When forecasting calculations using fuzzy time series, the interval length is established at the start of the calculation procedure. The duration of the gap significantly affects the establishment of fuzzy associations, which in turn affects the difference in forecast computation outcomes. The investigation reveals that Group AB has the lowest Root Mean Square Error (RMSE) value of 136.90, indicating that your model demonstrates superior accuracy in predicting blood group AB compared to other blood groups. The RMSE score for Group O is 819.5, which suggests that your model's accuracy in predicting blood group O is lower compared to other blood groups
Sistem Pendukung Keputusan Penerimaan Dana Bantuan Sosial Menggunakan Algoritma Decision Tree (C5.0) Di Kantor Desa Blankahan Dian Putri Kinanti; Rakhmat Kurniawan R; Adnan Buyung Nasution
Simpatik: Jurnal Sistem Informasi dan Informatika Vol. 6 No. 1 (2026): Juni 2026
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/simpatik.v6i1.12598

Abstract

Perkembangan teknologi informasi telah membawa transformasi signifikan dalam penyelenggaraan pelayanan publik, termasuk dalam penyaluran bantuan sosial. Namun, pelaksanaannya masih menghadapi berbagai tantangan, seperti yang terjadi di Desa Blankahan, Kabupaten Langkat, khususnya dalam proses pengambilan keputusan yang belum berbasis sistem dan kriteria yang terstandar. Proses penentuan penerima bantuan selama ini masih dilakukan secara konvensional tanpa dukungan sistem terkomputerisasi, sehingga berpotensi menimbulkan ketidaktepatan dan kurangnya transparansi. Metode yang digunakan adalah algoritma decision tree C5.0 untuk mengklasifikasikan data warga berdasarkan tujuh kriteria, yaitu status DTKS, penerima bantuan lain, kehilangan mata pencaharian, penyakit kronis, jumlah tanggungan, penghasilan, dan pekerjaan. Sistem dikembangkan berbasis web menggunakan Laravel, PHP, JavaScript, dan MySQL. Hasil pengujian menunjukkan tingkat akurasi sebesar 100%, yang menandakan bahwa sistem mampu memberikan hasil klasifikasi dengan sangat baik. Dengan demikian, sistem ini dapat digunakan sebagai alat bantu dalam proses pengambilan keputusan secara lebih akurat, efisien, dan transparan.
Analisis Sentimen Publik Terhadap Revisi UU TNI 2025 Menggunakan Algoritma Naïve Bayes Rizky Barus; Rakhmat Kurniawan
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.v5i2.380

Abstract

The development of public opinion regarding the revision of the 2025 Indonesian National Armed Forces Law (UU TNI) on social media has generated various responses that are difficult to analyze manually due to the large and unstructured amount of data. This condition requires a computational approach that is able to systematically identify public sentiment trends. This study aims to analyze public sentiment towards the revision of the 2025 TNI Law using the TF-IDF-based Naïve Bayes algorithm and evaluate the performance of the classification model used. The research data was obtained through crawling techniques from YouTube user comments related to the revision of the 2025 TNI Law. The data processing stages include cleaning, case folding, tokenizing, normalization, stopword removal, and stemming before TF-IDF weighting and the classification process using Naïve Bayes. The results of the study of 1826 data show that public sentiment is dominated by the neutral category at 79.8%, while positive sentiment is 13.1% and negative sentiment is 7.0%. The model evaluation yielded an accuracy of 77.11%, but the model showed a bias toward the majority class, resulting in suboptimal classification of positive and negative sentiments. Based on these results, the Naïve Bayes method is quite effective as an initial approach in sentiment analysis, but it still has limitations in handling imbalanced datasets and the complex characteristics of social media language. Therefore, the development of more adaptive methods is needed to improve the quality of sentiment classification results.
Penerapan Algoritma K-Means Dalam Pengelompokan UMKM Berdasarkan Potensi Pertumbuhan Berbasis Web Tri Asyura Mashuri; Rakhmat Kurniawan; Rahmad Syuhada
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 5 No. 1 (2026): Juni 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v5i1.1037

Abstract

Penelitian ini bertujuan untuk menerapkan algoritma K-Means dalam mengelompokkan Usaha Mikro, Kecil, dan Menengah (UMKM) berdasarkan potensi pertumbuhan serta merancang sistem informasi berbasis web yang mampu melakukan proses tersebut secara otomatis. Permasalahan yang diangkat adalah proses pengelompokan UMKM pada Dinas Perindustrian dan Perdagangan Provinsi Sumatera Utara yang masih dilakukan secara manual, sehingga kurang efisien dan berpotensi menghasilkan analisis yang tidak konsisten. Metode yang digunakan dalam penelitian ini adalah Research and Development (R&D) dengan model pengembangan sistem Waterfall. Data yang digunakan terdiri dari data primer dan sekunder UMKM dengan variabel omzet, aset, jumlah tenaga kerja, lama usaha, status digitalisasi, dan jangkauan pasar. Proses clustering dilakukan menggunakan algoritma K-Means untuk mengelompokkan data berdasarkan tingkat kemiripan karakteristik. Hasil penelitian menunjukkan bahwa algoritma K-Means mampu mengelompokkan UMKM ke dalam beberapa klaster yang merepresentasikan tingkat potensi pertumbuhan, yaitu rendah, sedang, dan tinggi. Sistem informasi berbasis web yang dikembangkan mampu melakukan pengolahan data secara otomatis, menampilkan hasil clustering secara terstruktur, serta meningkatkan efisiensi dan akurasi dalam proses pengelompokan UMKM. Dengan demikian, sistem yang dihasilkan dapat digunakan sebagai alat bantu dalam pengambilan keputusan strategis terkait pembinaan dan pengembangan UMKM secara lebih tepat sasaran.
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 Amelia, Dara Andre Gusli Agus Riadi Annabil, M Haziq Armansyah Armansyah Armansyah Armansyah Arrafiq, Muhammad Sunni Asnawi, Azi Ayyina, Ayyina Nurhidayah Azhari, Fajar Azka El Husein Lubis, Sultan Bahari, Mhd Raja Doly Bayhaqi, Abdullah Bisri, Cholil Br Rambe, Indri Gusmita Dandi, Muhammad Khairil Dasopang, Buyung Satrio Dian Putri Kinanti Dwisyahputra, Achmad Adbillah Eva Darwisah Harahap Fadiga, Muhammad 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 Zaki Husein Nst 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. Teguh wijaya Masdaliva, Fita Maulana, Fahmi Meilina, Indah Mey Hendra Putra Sirait Mhd Furqan Mhd Furqan Mhd. Furqan Furqan Mhd.Furqan Muhammad Abi Muzaki Muhammad Fahri, Muhammad Muhammad Ikhsan Muhammad Ikhsan Aji Muhammad Rizki Madani Muhammad Siddik Hasibuan Nasution, Fitri Handayani Nasution, Raihan Hafiz Nazry Luthfy, Fadhlun Noor Azizah Novita Jambak, Indah Nur Aini, Sakina Nurjanah, Trya Nurwana Nazla Saragih Padang, Bermiko Kasah Pravda, Michellia Delphi Isfahan Prayoga, Dio Putri Hanifah Putri, Raissa Ramanda Qasthari, Mohd. Wildan Rafli Bima Sakti Rahmad Syuhada Ramadhan, Alfan Ramadhan, Nuzul Ramadhan, Rio Fadli Ramadhan, Rizky Syahrul Ratna Dewi, Sri Reza Muhammad Rifansyah, Mhd. Roji Rifqi Alwanu Akmal Rina Filia Sari Rina Syafiddini Harahap Rini Halila Nasution 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 Sodik, Imam Sri Marwah Badrin Sriani Sriani Sriani Stephani Silalahi Suhardi Suhardi Suhardi Suhardi, Suhardi Syahira, Melani Alka Syahputra, Pii Syahputra, Zidhane Syarifudin, Zaini Tbn, Ahmad Fauza Anshori Tri Asyura Mashuri Triase Triase Triase Triase, Triase Wahyu Kurniawan wijaya, M. Teguh Wini Istya Sari Lubis Yahya, Arfigo YENI SAFITRI Yudha, Muhammad Yudha Pratama Zahron, Almeranda Haryaveda Nurul