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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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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.
Forecasting building permit submissions with fuzzy time series at DPMPTSP Medan Dasopang, Buyung Satrio; 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.v14i1.444

Abstract

Public service is a vital part of government performance, including how the Investment and One-Stop Integrated Services Agency (DPMPTSP) handles building permit applications (IMB). This study aims to estimate the number of IMB applications in Medan City using a method called Fuzzy Time Series (FTS). The forecast is intended as a preliminary step to support better spatial planning, especially as urban building density continues to rise. The FTS method was chosen for its ability to process time series data containing uncertainty. The forecasting process involves several stages: identifying the dataset, setting interval ranges, performing fuzzification, forming fuzzy logical relationships (FLR), grouping fuzzy logical relationship groups (FLRG), applying defuzzification, and measuring accuracy using Mean Absolute Percentage Error (MAPE). The data used include IMB applications from 2022 to 2023, with predictions made for 12 months in 2024. The results show that the FTS model closely follows historical data patterns, evidenced by a MAPE value of 1.99%, which indicates excellent accuracy as it is well below the 10% threshold. A comparative graph between actual and predicted data further supports this, revealing similar trends. In conclusion, the Fuzzy Time Series method is effective for forecasting IMB application volumes and can serve as a valuable reference for urban planning decisions and future time series-based forecasting research involving uncertainty.
Implementation of the K-Nearest Neighbor Algorithm for Birth Rate Prediction Alhafiz, Akhyar; Kurniawan R., Rakhmat
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9886

Abstract

This study aims to predict the monthly birth rate using the K-Nearest Neighbor (KNN) regression algorithm. The dataset consists of historical data from 2010 to 2020, covering six districts and including variables such as total population, number of couples of reproductive age, family planning participation rate, and monthly birth rate as the prediction target. Data preprocessing involved handling missing values and applying Min-Max normalization. To maintain the time-series nature of the data, a chronological split was used, with 576 records from 2010 to 2018 for training and 216 records from 2019 to 2020 for testing. The model was evaluated using Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R-squared (R²). The best performance was achieved at K = 7, with MAE = 19.94, RMSE = 30.91, and R² = 0.34. Additionally, the KNN model was compared with Linear Regression and Decision Tree, where KNN outperformed both alternatives. The final model was implemented in a web-based application to facilitate demographic data management and automatic birth rate prediction per district. This system is expected to support policy planning in the fields of population control and public health.
Clustering Data Penjualan Kopi Sidikalang Menggunakan Metode K-Means Padang, Bermiko Kasah; Kurniawan, Rakhmat
SENTRI: Jurnal Riset Ilmiah Vol. 4 No. 8 (2025): SENTRI : Jurnal Riset Ilmiah, Agustus 2025
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/sentri.v4i8.4400

Abstract

This study aims to analyze the sales patterns of Sidikalang coffee using the K-Means clustering method to optimize stock management and marketing strategies. Three months of sales data were analyzed based on the attributes of sales volume, price, and season. The results showed that the data could be grouped into four clusters with distinct characteristics: low sales (52 data points), medium sales (50 data points), high sales (21 data points), and high stock with sporadic sales (77 data points). Evaluation using the Davies-Bouldin Index (DBI) yielded a score of 0.52, indicating good clustering quality. These findings provide valuable insights for business actors in developing more targeted marketing strategies and efficient stock management. This research also contributes to the literature on the application of machine learning in analyzing local product sales, particularly Sidikalang coffee.
Sentiment Analysis Of Public Enthusiasm Towards Electric Motorcycles Using The Naïve Bayes Algorithm Ratna Dewi, Sri; Kurniawan R, Rakhmat
International Journal of Science and Environment (IJSE) Vol. 5 No. 3 (2025): August 2025
Publisher : CV. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51601/ijse.v5i3.217

Abstract

Electric motorcycles have emerged as an alternative to reduce dependence on fossil fuels and support environmentally friendly transportation. In Indonesia, the local brand Polytron has introduced several electric motorcycle products at affordable prices. However, public responses remain varied, influenced by price, infrastructure, and awareness. This study aims to analyze public enthusiasm for Polytron electric motorcycles using the Naïve Bayes Classifier (NBC), which has been proven effective in text classification [1]. A dataset of 1000 comments was collected from social media platform X through web crawling. The preprocessing included case folding, cleaning, tokenizing, normalization, stopword removal, and stemming[2]. Sentiment labeling was conducted using the InSetLexicon, and TF-IDF weighting was applied before classification in Python using Google Colab [3]. The results indicated that most public opinions expressed positive sentiment, highlighting benefits such as cost savings and environmental friendliness [4]. Negative sentiments focused on limited charging infrastructure and higher purchase prices. The Naïve Bayes model achieved reliable performance, confirming its suitability for Indonesian sentiment analysis tasks [5]. This study contributes to understanding public perception of local electric vehicles and provides useful insights for policymakers and manufacturers in promoting sustainable transportation.
Implementasi Metode Fuzzy Mamdani Untuk Pemilihan Keramik Rumah Bangunan Nasution, Raihan Hafiz; Rakhmat Kurniawan R
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 03 (2025): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i03.1644

Abstract

Pemilihan keramik merupakan salah satu aspek penting dalam konstruksi bangunan karena berpengaruh pada kenyamanan, keamanan, dan estetika hunian. Variasi produk serta perbedaan karakteristik teknis seperti harga, kualitas, daya serap air, dan kekasaran permukaan sering menyulitkan konsumen dalam menentukan pilihan yang tepat. Penelitian ini bertujuan untuk mengembangkan sistem pendukung keputusan pemilihan keramik rumah bangunan berbasis metode Fuzzy Mamdani. Metode penelitian yang digunakan adalah Research and Development (R&D) dengan melibatkan proses fuzzifikasi, inferensi fuzzy, dan defuzzifikasi. Data penelitian mencakup 120 jenis keramik dari berbagai merek ternama di Indonesia. Hasil pengujian menunjukkan bahwa empat produk keramik, yaitu Indogress Batu Alam Lux, Roman Batu Alam Lux, Granito Batu Alam Lux, dan Platinum Kayu Eksklusif, memperoleh skor 80 dengan kategori “Sangat Direkomendasikan”, sementara Kia Marmer Classic hanya memperoleh skor 50 dengan kategori “Cukup Direkomendasikan”. Temuan ini mengindikasikan bahwa harga dan kualitas menjadi faktor dominan dalam penentuan rekomendasi, sedangkan daya serap air dan kekasaran berperan sebagai variabel pendukung. Dengan demikian, sistem yang dikembangkan mampu membantu konsumen memilih keramik secara lebih objektif dan akurat.
Sistem Informasi Rekam Medis Pada Puskesmas Dengan Menerapkan Algoritma K-Means Berbasis Web Nasution, Fitri Handayani; Kurniawan, Rakhmat; Putri, Raissa Ramanda
Jurnal Ilmiah Sains dan Teknologi Vol. 9 No. 2 (2025): Jurnal Ilmiah Sains dan Teknologi
Publisher : Teknik Informatika Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5555/a13zp055

Abstract

Medical record management at Puskesmas is one of the important aspects in efficient health services. However, the manual system that is still widely used often causes various problems such as recording errors, and the slow process of making medical decisions. this study aims to design and build a web-based medical record information system that can facilitate digital patient data management. This system is also equipped with the application of the K-Means algorithm to categorize the types of diseases suffered by patients. The patient's disease will be categorized into 3 categories, namely very severe, severe, and not severe by the system. The system development method used is the waterfall method and Unified Modeling Language tools and the system development process using the PHP programming language and MySQL database. With this information system, it is hoped that it can facilitate medical record officers in recapitulating patient data and providing good service.
IMPLEMENTASI METODE SMART dan WP UNTUK MENENTUKAN SISWA KELAS UNGGULAN BERDASARKAN PRESTASI AKADEMIK BERBASIS WEBSITE Nurjanah, Trya; R, Rakhmat Kurniawan
IJIS - Indonesian Journal On Information System Vol 10, No 2 (2025): SEPTEMBER
Publisher : POLITEKNIK SAINS DAN TEKNOLOGI WIRATAMA MALUKU UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36549/ijis.v10i2.421

Abstract

Pemilihan siswa berprestasi di sekolah memerlukan sistem yang objektif dan terukur agar prosesnya berjalan adil dan transparan. Penelitian ini bertujuan untuk membangun sistem pendukung keputusan berbasis web yang mampu menentukan siswa berprestasi dengan menggunakan metode SMART (Simple Multi-Attribute Rating Technique) dan metode WP (Weighted Product). Penelitian ini menggunakan Metode RAD (Rappid Aplication Development) dalam proses pengembangan sistem, mulai dari analisis kebutuhan, perancangan antarmuka, hingga implementasi sistem berbasis web menggunakan PHP dan MySQL. Data yang digunakan berasal dari kriteria penilaian siswa seperti nilai akademik, keaktifan, kepribadian, dan prestasi. Hasil pengujian menunjukkan bahwa sistem yang dibangun mampu menampilkan hasil perhitungan alternatif siswa secara akurat, baik melalui metode SMART maupun WP, serta menghasilkan rekomendasi terbaik melalui kombinasi keduanya. Dengan sistem ini, sekolah dapat lebih mudah mengambil keputusan yang tepat dalam menentukan siswa berprestasi.Kata Kunci: Sistem Pendukung Keputusan, SMART, WP
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