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All Journal International Journal of Reconfigurable and Embedded Systems (IJRES) TEKNIK INFORMATIKA Jurnal TIMES Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Informatika dan Teknik Elektro Terapan Scientific Journal of Informatics Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Teknologi Informasi MURA Jurnal Telematika JOURNAL OF SCIENCE AND SOCIAL RESEARCH Journal of Applied Science, Engineering, Technology, and Education U-NET Jurnal Teknik Informatika Jurnal Teknik Informatika (JUTIF) JPM: JURNAL PENGABDIAN MASYARAKAT Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Jurnal Pengabdian Pada Masyarakat METHABDI Majalah Ilmiah METHODA Jurnal Abdimastek (Pengabdian Masyarakat Berbasis Teknologi) PUBLIDIMAS CSRID SISFOTENIKA
Rika Rosnelly, Rika
Unknown Affiliation
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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Rancang Bangun dan Implementasi Sistem Antrian Customer Pada PT. Infomedia Solusi Humanika Rosnelly, Rika; Sari, Dian Maya; Paramitha, Cindy
Jurnal Pengabdian Masyarakat Berbasis Teknologi Vol 2 No 1 (2021): VOLUME 2. NO 1. APRIL 2021
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/abdimastek.v2i1.1109

Abstract

The service process carried out at the customer care center is currently still using a manual service system. Therefore, the researcher tries to implement a customer queuing system at the care center to simplify the service process. In this final result the researcher will use the ATMega 16 microcontroller minimum system module for the design and manufacture of a minimum system to simplify the customer queuing service process at the care center. Microcontroller programming is widely used for service system display functions on seven segment displays as well as print out queue no. The process begins with the visitor pressing the push button which then the system will issue a print out of the visitor queue no. If the customer care servant presses the push button in the system used by the customer service, it is used for seven segment displays. Then the data from the push button results will be sent by the microcontroller to print out the queue no on the printer, and then enter the data into the Personal Computer. After that the waiter at the customer care presses the button then the data is sent by the microcontroller to be output on the seven segment display.
Optimalisasi Pembelajaran Coding Berbasis Kecerdasan Buatan untuk Meningkatkan Literasi Digital Siswa Wahyuni, Linda; Rizal, Chairul; Rosnelly, Rika; Sari, Rita Novi; Hardianto, Hardianto; Harahap, Charles Bronson
JPM: Jurnal Pengabdian Masyarakat Vol. 6 No. 3 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jpm.v6i3.2785

Abstract

This community service program aims to enhance the professional capacity of teachers through mastery of modern educational technologies. The implementation of this program is based on several issues identified within the partner institution, including teachers’ limited understanding of artificial intelligence, their low ability to integrate coding into learning activities, and the suboptimal use of digital tools and media in the classroom. These challenges contribute to students’ low digital literacy and the insufficient application of project-based learning that aligns with current technological developments. The training program was designed to strengthen teachers’ competencies in implementing AI-based coding instruction through participatory approaches and hands-on practice. The learning modules were developed contextually to meet the specific needs of the partner school, enabling teachers to adapt them easily into their teaching practices. The results of the program indicate significant improvements in teachers’ understanding of fundamental AI concepts, their ability to integrate coding into the learning process, and their capacity to apply digital technologies ethically and effectively. Enhanced student engagement was also observed, as learners became more enthusiastic and active in participating in project-based learning activities involving AI applications. Although the program faced several limitations, such as inadequate technological equipment and limited implementation time, it has established a strong foundation for the development of more structured and sustainable follow-up activities. Overall, the outcomes demonstrate that strengthening teachers’ competencies in artificial intelligence plays a crucial role in fostering an innovative digital learning ecosystem aligned with the demands of 21st-century education.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN SUPPLIER MENGGUNAKAN METODE SAW PADA APOTEK HALOMOAN Lubis, Dela Aventi Oktavia Br; Rosnelly, Rika
Jurnal Informatika dan Teknik Elektro Terapan Vol. 14 No. 1 (2026)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v14i1.8358

Abstract

Proses pemilihan supplier pada banyak instansi farmasi sering dilakukan secara manual sehingga keputusan menjadi subjektif, memakan waktu, dan berisiko menimbulkan masalah seperti keterlambatan pengiriman atau ketidaksesuaian kualitas barang. Kondisi ini menunjukkan perlunya sistem evaluasi yang lebih objektif dan terstruktur. Penelitian ini menerapkan metode Simple Additive Weighting (SAW) dalam Sistem Pendukung Keputusan (SPK) untuk menilai dan menentukan supplier terbaik berdasarkan beberapa kriteria terukur. Enam kriteria digunakan dalam penelitian ini, yaitu waktu pengiriman, harga, kualitas produk, ketersediaan stok, tempo pembayaran, dan layanan keluhan. Sistem dikembangkan menggunakan PHP dan MySQL, kemudian diuji secara fungsional untuk memastikan akurasi perhitungan dan performa sistem. Hasil penelitian menunjukkan bahwa metode SAW mampu menghasilkan rekomendasi supplier secara objektif, dengan salah satu alternatif memperoleh nilai tertinggi sebesar 0,913. Temuan ini membuktikan bahwa penerapan SAW efektif dalam meningkatkan kualitas pengambilan keputusan, mempercepat proses evaluasi, serta memastikan keputusan yang dihasilkan dapat dipertanggungjawabkan secara transparan.
Optimized KNN Performance with PCA and K-Fold Cross-Validation for Colorectal Cancer Survival Prediction Manza, Yuke; Rosnelly, Rika; Furqan, Mhd; Riza, Bob Subhan
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 1 (2026): JUTIF Volume 7, Number 1, February 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.1.5422

Abstract

Colorectal cancer remains a leading cause of global mortality, necessitating effective predictive tools for patient survival. While Machine Learning algorithms like K-Nearest Neighbors (KNN) utilize patient data for prediction, standard KNN implementations often suffer from the curse of dimensionality and overfitting, leading to unreliable performance on complex medical datasets. This study aims to evaluate and optimize the performance of the KNN algorithm by integrating Principal Component Analysis (PCA) for dimensionality reduction and K-Fold Cross-Validation (KFCV) to enhance model stability. The research utilized a quantitative approach on a global colorectal cancer dataset, processing demographic and clinical features through a rigorous pipeline of imputation, encoding, and normalization. Three model configurations were systematically compared: Standard KNN, KNN combined with PCA, and an optimized KNN model utilizing both PCA and KFCV across various neighbor values. The results demonstrate a distinct trade-off between predictive sensitivity and model stability. While the Standard KNN and PCA-enhanced models achieved higher recall, indicating a strong ability to identify survivors in a single data split, the fully optimized KNN+PCA+KFCV model provided the most stable and generalized accuracy with minimal deviation. These findings indicate that while PCA effectively reduces computational complexity without information loss, the integration of cross-validation is crucial for obtaining an honest assessment of model performance. This research contributes to clinical informatics by highlighting the necessity of prioritization between high sensitivity and generalization stability when developing survival prediction models for complex, inseparable medical data.
Long Short Term Memory and Gradient Boosting Model for One Day Ahead Forecasting of ANTAM Gold Bar Prices Ashari, Annisa; Situmorang, Zakarias; Rosnelly, Rika
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 2 (2026): JUTIF Volume 7, Number 2, April 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.2.5630

Abstract

This study develops and optimizes a hybrid LSTM-XGBoost forecasting model for daily ANTAM gold bar prices. The model utilizes historical time-series data of ANTAM gold prices, enriched with macroeconomic variables including the USD/IDR exchange rate and Brent oil prices, as well as derived features such as returns, lags, rolling statistics, and calendar effects. The LSTM component captures medium-term sequential patterns from the price series and macroeconomic variables, while the XGBoost component exploits a rich set of tabular features to model nonlinear relationships and volatility dynamics. Both models are trained and tuned separately, then combined through a weighted ensemble scheme in which the optimal weight is selected by minimizing Mean Absolute Percentage Error (MAPE) on the validation set. Experimental results on the test set show that the proposed hybrid model achieves Mean Squared Error (MSE) of 26,891,172.36, Root Mean Squared Error (RMSE) of 16,398.53, MAPE of 0.0058 (approximately 99.42% accuracy), and coefficient of determination \mathbit{R}^\mathbf{2} of 0.9971, outperforming a naïve baseline that assumes “tomorrow’s price equals today’s price”. The optimized LSTM-XGBoost hybrid model proves highly effective for short-term ANTAM gold price forecasting, providing reliable decision support for Indonesian gold market stakeholders.
Co-Authors Agung Rizky, Muhammad Dipo Agus Fahmi Limas Ptr Aji, Eko Setyo Budi Putra Akbar, Muhammad Barkah Alkhairi, Putrama Ammar Yasir Nasution Amrullah Amrullah Ashari, Annisa Batubara, Ela Roza Bob Subhan Riza, Bob Subhan Chairul Rizal Daifiria Dian Maya Sari ElisaBeth S, Noprita ElisaBeth S Fahriyani, Tasya Finis Hermanto Laia Gea, Muhammad Nasri Habib Satria Habib, Nurhayati Harahap, Charles Bronson Harahap, Sarwedi HARDIANTO - Hartono Hartono Hartono Hartono Haryanto S., Edy Victor Heru Satria Tambunan, Heru Satria Ilmi R.H. Zer, P.P.P.A.N.W. Fikrul Indra Kelana Jaya Junaidi Junaidi Kelvin Leonardi Kohsasih Khairi, Ibni Krismona, Lumi Limas, Agus Fahmi Lubis, Dela Aventi Oktavia Br Manza, Yuke Margolang, Khairul Fadhli MARIA BINTANG Mega Christin Morys Lase Mhd Furqan Mochammad Imron Awalludin Muhammad Sadikin Mulkan Azhari Nasution, M. Irfan Aldy Naswar, Alvinur Nursie, Aly Paramitha, Cindy Putra, Reza Ananda Rahma, Intan Dwi Rahmadi, Diky Ramadhan, Muhammad Yakub Rambe, Lima Hartima Rambe, Lima Hartimar Rofiqoh Dewi Roslina Roslina, Roslina Sagala, Tamado Simon Sari, Rita Novi Sari, Rita Novita Setiawan, Adil Simanullang, Maradona Jonas Siregar, Kiki Putri Ani Situmorang, Zakaria sri lestari rahayu Subhan, Zhafira Nur Sugeng Riyadi Sukriatna Sumantri, Ekoliyono Wahyu Suyono Suyono Syahrian, Achmad Tambunan, Fazli Nugraha Tarigan, Dede Ardian Teddy Gunawan, Teddy Teddy Surya Gunawan Veronica Wijaya, Veronica Wahyudi, Diky Wahyuni, Linda Wanayaumini, W Wanayumini Zai, Andreas Zakarias Situmorang Zer, P.P.P.A.N.W. Fikrul Ilmi R.H.