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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 EDUMATIC: Jurnal Pendidikan Informatika METIK JURNAL Jurnal Mantik Progresif: Jurnal Ilmiah Komputer Jurnal Ilmiah Sains dan Teknologi 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 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 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 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
Department Of Computer Science, Faculty Of Science And Technology State Islamic University Of North Sumatera
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Sentiment analysis of privacy issues in the digital era using the naïve bayes method Ramadhan, Rio Fadli; Kurniawan, Rakhmat
Jurnal Mandiri IT Vol. 14 No. 2 (2025): Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i2.450

Abstract

The development of information technology has triggered public concern about data privacy issues, especially on social media such as X (formerly Twitter). The rampant leaks of personal data have driven the need for a deeper understanding of public opinion. This study aims to analyze public sentiment towards data privacy issues by applying the Naïve Bayes algorithm. The formulation of the problem includes how the public perceives data privacy, how the algorithm performs in classifying sentiment, and how the evaluation results of the model used are. This study uses a quantitative method with a text mining and machine learning approach. Data were taken through crawling techniques on 1,500 tweets related to data privacy. The pre-processing stages were carried out through cleaning, tokenizing, normalization, stopword removal, and stemming. Furthermore, the data was labeled using the InsetLexicon dictionary and weighted using the TF-IDF method. The classification model was built using the Naïve Bayes algorithm and evaluated using accuracy, precision, recall, and f1-score metrics. The results showed that the majority of public opinion on data privacy issues was negative, reflecting concerns over the weak protection of personal data. The Naïve Bayes model performed quite well in sentiment classification. This research is useful in providing insight to the government and digital service providers in developing data protection policies that are more responsive to public opinion.
Optimasi Rute Terdekat Dalam Pencarian Bengkel Sepeda Motor di Kota Medan dengan Pendekatan Algoritma Floyd Warshall Harahap, Shopiah; Kurniawan, Rakhmat; Suhardi, Suhardi
EDU SOCIETY: JURNAL PENDIDIKAN, ILMU SOSIAL DAN PENGABDIAN KEPADA MASYARAKAT Vol. 5 No. 2 (2025): June-September 2025
Publisher : Association of Islamic Education Managers (Permapendis) Indonesia, North Sumatra Province

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56832/edu.v5i2.1686

Abstract

Pencarian bengkel motor terdekat secara efisien merupakan tantangan bagi pengendara, terutama dalam kondisi mendesak. Tulisan ini berusaha memberikan solusi dengan metode pendekatan Algoritma Floyd Warshall untuk mengidentifikasi rute terpendek dalam sistem pencarian bengkel sepeda motor. Mekanisme kerja algoritma ini adalah menghitung jarak terpendek antar semua pasangan node (lokasi) dalam graf dengan membandingkan jalur langsung dan jalur melalui intermediate node, secara iteratif. Pemodelan jaringan jalan dan lokasi bengkel sepeda motor dilakukan sebagai graf berbobot, di mana node merepresentasikan lokasi dan edge merepresentasikan segmen jalan dengan bobot jarak atau waktu. Variabel utama yang digunakan adalah matriks jarak antar node yang diperbarui secara progresif. Hasil penelitian menunjukkan bahwa Algoritma Floyd Warshall berhasil 95 % untuk menentukan rute optimal ke bengkel sepeda motor terdekat dari posisi pengguna. Hasil pengujian menunjukkan sistem mampu mengidentifikasi rute terpendek, meskipun waktu komputasi akan meningkat seiring pertambahan jumlah node dan edge. Pengaruh variabel jarak antar node memberi pengaruh nilai bobot secara langsung dalam hasil perhitungan rute terpendek.
Naïve bayes algorithm for early diagnosis of non-communicable diseases Ramadhan, Nuzul; Ramli, Rakhmat Kurniawan
Journal of Intelligent Decision Support System (IDSS) Vol 8 No 3 (2025): September: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v8i3.306

Abstract

Non-communicable diseases such as heart disease, diabetes mellitus, hypertension, stroke, asthma, rheumatism, and GRED are still the main causes of illness and death in Indonesia. This problem is more serious in rural areas with limited health services, such as Lubuk Palas Village, Asahan Regency, which faces obstacles in distance, road infrastructure, and a limited number of medical personnel, so early diagnosis is often neglected. This research aims to apply the Naïve Bayes method in a non-communicable disease diagnosis expert system and develop web and mobile-based applications to support the community and medical personnel in early detection. The research method combines primary data from observations and interviews with health workers and secondary data from medical literature. Each symptom is given a probability weight of 0.00–1.00 according to medical consultation, then processed using the Naïve Bayes algorithm with two approaches, namely direct calculation and gradual filtering. The results show that the system produces a posterior probability of 99.32% in the heart disease scenario with typical symptoms and 90.00% in the stroke scenario with partial symptoms. The findings of this research are that the application of two Naïve Bayes inference pathways is proven effective in producing an initial diagnosis that is adaptive to variations in symptoms, relevant for rural conditions with limited health services, and capable of providing fast, practical, and widely accessible medical decision support.
Bird Sound Quality Analysis for Chirping Masters Using Mel Frequency Cepstrum Coefficiens (MFCC) and Svm Classification Algorithm Zahron, Almeranda Haryaveda Nurul; Kurniawan, Rakhmat
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 6, No 2 (2025)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v6i2.26410

Abstract

Birds play an important role in ecosystems as indicators of environmental health and biodiversity. In Indonesia, there are approximately 1,531 bird species, including songbirds that are popular for their melodious chirps. Bird sounds are used for communication, territorial marking, and are a key attraction in bird song competitions. However, obtaining a bird with high-quality vocalization requires specific training, one of which is the mastering method using recordings of champion bird songs. Additionally, the Support Vector Machine (SVM) algorithm has proven effective in classifying bird species based on sound, achieving 77% accuracy after noise reduction. The combination of MFCC and SVM allows for more systematic and accurate analysis of bird vocalizations. This research is expected to contribute to the field of ornithology, the development of songbird husbandry techniques, and serve as a guide for bird enthusiasts in selecting high-quality master bird sounds.
Sistem Rekomendasi Pemilihan Saham Blue-Chip di Bursa Efek Indonesia Menggunakan Fuzzy Mamdani Dandi, Muhammad Khairil; Kurniawan, Rakhmat
TIN: Terapan Informatika Nusantara Vol 6 No 5 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i5.8465

Abstract

The Indonesian capital market plays an important role in supporting national economic growth, particularly through stock investments. Blue-chip stocks are considered stable and have the potential to provide long-term returns, yet selecting the right ones remains a challenge for investors. This study aims to develop a recommendation system for selecting blue-chip stocks on the Indonesia Stock Exchange (BEI) using the Fuzzy Mamdani method. The research data were collected from a set of actively traded blue-chip stocks within a specific period and analyzed using four main variables: stock price, trading volume, market capitalization, and financial ratios. The recommendation process involves fuzzification, the formulation of 15 rule bases established through expert consultation with market analysts, Mamdani inference, and defuzzification to produce recommendation scores. The implementation results show that the system achieved an accuracy level of 84.65%, indicating stable consistency with actual market conditions. These findings confirm that the Fuzzy Mamdani method is effective in generating objective and systematic recommendations for blue-chip stock selection. The developed system successfully meets the research objective by assisting investors in identifying suitable stocks based on data-driven analysis.
Penerapan Text Mining Pada Sistem Penyeleksian Judul Skripsi Menggunakan Algoritma Latent Dirichlet Allocation(LDA) Kurniawan R, Rakhmat; Zufria, Ilka
The Indonesian Journal of Computer Science Vol. 11 No. 3 (2022): 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.v11i3.3120

Abstract

Dalam proses pengajuan judul proposal skripsi, banyak mahasiswa yang judulnya ditolak dikarenakan adanya kesamaan judul atau tema penelitian yang telah dilakukan sebelumnya. Proses ini dilakukan secara manual dimana judul skripsi direkapitulasi dengan menggunakan aplikasi Microsoft Excel, sehingga membuka peluang kekeliruan dalam pemeriksaan yang disebabkan oleh tim penyeleksi memeriksa judul secara manual baris per baris. Selanjutnya dirasa perlu melakukan penelitian untuk mengatasi masalah tersebut. Dengan harapan memudahkan pengelola program studi dalam menentukan judul skripsi yang potensial dan berkualitas pada mahasiswa. 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 kelayakan judul skripsi yang diajukan melalui teknologi text mining menggunakan algoritma LDA. Algoritma LDA mampu untuk mendeteksi topik yang ada pada suatu koleksi dokumen beserta besarnya kemunculan topik tersebut.
Analisis Sentimen Mengenai Childfree Menggunakan Metode Naïve Bayes: Analisis Sentimen Mengenai Childfree Menggunakan Metode Naïve Bayes Yeni Safitri; Rakhmat Kurniawan; Suhardi
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4136

Abstract

The emergence of the issue of childfree has become a trending topic on Twitter since the beginning of 2020 until now, which has given rise to many positive and negative opinions from various groups, especially on Twitter social media. This sentiment analysis research aims to determine the responses given regarding childfree in the form of positive, neutral or negative opinions by collecting Twitter data. The number of datasets used is 700 data, divided into 630 training data and 70 test data. This research uses the Naïve Bayes algorithm classification and confusion matrix as a performance evaluation of the system being built. The test results show an accuracy value of 64.29%, precision of 68.25%, recall of 64.29% and fi-score of 55.69%.
Pencarian Rute Terpendek Dalam Pendistribusian Darah di Palang Merah Indonesia (PMI) dengan Algoritma Dijkstra Hidayatullah, Catur; R, Rakhmat Kurniawan; Armansyah, Armansyah
TIN: Terapan Informatika Nusantara Vol 4 No 11 (2024): April 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v4i11.5028

Abstract

The Indonesian Red Cross (PMI) is an independent and neutral organization in Indonesia engaged in humanitarian activities. One of the departments within the Indonesian Red Cross is the blood donor unit. The Blood Donor Unit (UDD) of PMI Deli Serdang is one of the Indonesian Red Cross offices in the Deli Serdang district, which deals with social humanitarian activities such as blood donation, volunteer recruitment, emergency response, and others. One common issue in blood distribution is the numerous routes that need to be taken, resulting in wasted time and delayed blood deliveries. Due to this issue, the implementation of artificial intelligence is needed to determine the shortest route for optimal and fast blood delivery. The application of artificial intelligence in problem-solving in the field of computer science has seen rapid development over the years in line with the advancement of artificial intelligence itself. In determining the shortest route, several algorithms can be used, one of which is the Dijkstra algorithm. It is used to solve problems in a graph to determine the shortest route. In the process, the Dijkstra algorithm determines the points that will become the distance weights connected from one point to another, resulting in the desired nodes. Therefore, an application is needed to find the nearest route to make blood delivery more time-efficient. In manual calculations using the algorithm, it was found that the shortest route from UDD (PMI Deli Serdang Blood Donation Unit) to GM (Grand Medistra Hospital) is through the route UDD → A → B → C → D → GM = 0 + 300 m + 250 m + 1,500 m + 35 m + 90 m with a total distance of 2,175 meters or 2.1 kilometers in 5 minutes. Thus, the use of the Dijkstra algorithm can assist in determining the fastest and optimal route for blood distribution, saving time and improving delivery efficiency.
Hyperparameter Optimization of Naive Bayes for Supervisor Recommendation in Computer Science Sinaga, Muhammad Nabil; Kurniawan R, Rakhmat
TIN: Terapan Informatika Nusantara Vol 6 No 5 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i5.8478

Abstract

The increasing number of students in the Department of Computer Science at UIN Sumatera Utara has made the process of selecting thesis supervisors more complex and time-consuming. This study aims to develop a system that automatically recommends the most suitable supervisor based on the similarity between thesis titles and lecturers’ areas of expertise. The proposed model applies text preprocessing techniques such as case folding, tokenization, stopword removal, and keyword extraction to transform thesis titles into meaningful features. These features are then classified using the Naive Bayes algorithm to predict the probability of each lecturer being the most relevant supervisor. The dataset consists of 794 thesis titles and 25 lecturers collected from 2019–2024. The model was evaluated using an 80:20 data split, achieving an accuracy of 87.3% with stable precision and recall scores, demonstrating reliable performance in supervisor recommendations. This enhanced Naive Bayes model can assist academic departments in ensuring a fairer and more efficient supervisor assignment process.
SISTEM INFORMASI PERSEDIAAN BERAS DI CV XYZ MENGGUNAKAN METODE PERIODIC REVIEW SYSTEM (PRS) BERBASIS WEB Rudi Riyandi; Kurniawan R, Rakhmat
ZONAsi: Jurnal Sistem Informasi Vol. 6 No. 2 (2024): Publikasi Artikel ZONAsi: Periode Mei 2024
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/zn.v6i2.20023

Abstract

Beras, sebagai komoditas pangan pokok yang vital dalam kehidupan sehari-hari, memainkan peran sentral dalam industri makanan di berbagai negara, termasuk Indonesia. Manajemen persediaan beras yang efektif adalah kunci untuk memastikan ketersediaan dan distribusi yang lancar. Penelitian ini bertujuan untuk mengembangkan Sistem Informasi Persediaan Beras di CV XYZ dengan metode Periodic Review System (PRS) berbasis web. Dalam konteks ini, PRS diterapkan sebagai pendekatan untuk meningkatkan efisiensi dan ketepatan dalam pengelolaan persediaan beras. Evaluasi sistem menunjukkan peningkatan yang signifikan dalam optimisasi level persediaan, penurunan biaya penyimpanan, serta peningkatan responsibilitas staf dalam manajemen persediaan. Selain itu, peningkatan akurasi dalam perkiraan permintaan dan ketersediaan produk juga diamati. Implikasi praktis dari penelitian ini menyediakan panduan berharga bagi perusahaan dalam menerapkan solusi berbasis web untuk meningkatkan manajemen persediaan.
Co-Authors Abdul Halim Hasugian Agung Firmansyah 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 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 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 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 Siddik Hasibuan 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 Putri Hanifah Putri, Raissa Ramanda Qasthari, Mohd. Wildan Rafli Bima Sakti Ramadhan, Alfan Ramadhan, Nuzul Ramadhan, Rio Fadli Ramadhan, Rizky Syahrul Ratna Dewi, Sri Reza Muhammad Rifansyah, Mhd. Roji Rifqi Alwanu Akmal Rina Filia Sari Rini Halila Nasution Rizki Ananda Putra Fajar 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 Sriani, S Stephani Silalahi Suhardi Suhardi Suhardi Suhardi, Suhardi Syahira, Melani Alka Syahputra, Pii Syahputra, Zidhane Syarifudin, Zaini Tbn, Ahmad Fauza Anshori 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