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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) JAIS (Journal of Applied Intelligent System) SISFOTENIKA Jurnal Teknologi Informasi MURA Voice Of Informatics Zero : Jurnal Sains, Matematika, dan Terapan JOURNAL OF SCIENCE AND SOCIAL RESEARCH JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) CSRID (Computer Science Research and Its Development Journal) Jurnal Informatika Kaputama (JIK) Jurnal Mantik IT (INFORMATIC TECHNIQUE) JOURNAL ICIT (Innovative Creative and Information Technology) Journal REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Journal of Computer Networks, Architecture and High Performance Computing Jurnal Generic JUDIMAS (Jurnal Inovasi Pengabdian Kepada Masyarakat) Journal of Applied Computer Science and Technology (JACOST) DEVICE Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) INFOSYS (INFORMATION SYSTEM) JOURNAL Jurnal Ipteks Terapan : research of applied science and education International Journal of Research in Vocational Studies (IJRVOCAS) Jurnal Teknologi Informasi Mura Jurnal Abdimastek (Pengabdian Masyarakat Berbasis Teknologi) CSRID
Rika Rosnelly
Uiversitas Potensi Utama
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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

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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.
Decision Support System Application Evaluation of Transformer Isolation Condition with Simple Additive Weighting (SAW) Method Rika Rosnelly; Teddy Gunawan; Cindy Paramitha; Muhammad Sadikin
Jurnal Pengabdian Masyarakat Berbasis Teknologi Vol 1, No 1 (2020): APRIL 2020
Publisher : ISB Atma Luhur

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Abstract

The use of computer technology has spread among workers and companies. Therefore researchers recommend a system that can overcome the problem of assessing the conditions of transformer insulation at PT. Electricity System Cemerlang uses a computer system. The system that researchers use is a decision support system. Decision Support System or often called Decision Support System (DSS) is a model-based system that consists of procedures in data processing and consideration to assist managers in making decisions. In order to succeed in achieving its objectives, the system must be simple, robust, easy to control, easily adaptable to important things and easy to communicate with. Implicitly also means that this system must be computer-based and used as an addition to someone's problem solving capabilities. But to be able to use a decision support system properly, a method or an appropriate method is needed to get the right results. Therefore researchers recommend the method of Simple Additive Weighting (SAW). Simple Additive Weighting (SAW) method is often also known as the weighted sum method. The basic concept of the method of Simple Additive Weighting (SAW) is to find a weighted sum of performance ratings on each alternative on all attributes.
Utilization of Digital Image and Convolution Neural Network Algorithm in Customer Satisfaction Survey with Facial Expressions Tri Andre Anu; Rika Rosnelly; Dedi Irawan; Progresif Bulolo; Ubaidullah Hasibuan
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 4, No 2 (2023)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v4i2.15915

Abstract

The human face provides us with a lot of information about a person, and arguably the two most important pieces of information in a face are a person's identity and their emotional state. Judgments of identity and emotion facilitate social interactions. Services are a crucial part of the activities of all organizations, especially those in the service sector. Good services support customer satisfaction and ultimately impact the progress of the organization. The Convolutional Neural Network algorithm has become the most widely used neural architecture in various tasks, including image classification, audio pattern recognition, machine translation of text, and speech recognition. The data groups (angry, fearful, happy, neutral, sad, and surprised) tested with a threshold value of 30 epochs achieved a loss (error) accuracy of 1.5146 on the test data. The accuracy on the test data is 0.61. The proposed Convolutional Neural Network algorithm and digital image utilization achieved high accuracy performance to assist in evaluating a service-related field.
DETEKSI PENGENALAN WAJAH ORANG BERBASIS AI COMPUTER VISION Finis Hermanto Laia; Rika Rosnelly; Alvinur Naswar; Karuniaman Buulolo; Mega Christin Morys Lase
Jurnal Teknologi Informasi Mura Vol 15 No 1 (2023): Vol 15 No 1 (2023): Jurnal Teknologi Informasi Mura Juni
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jti.v15i1.2024

Abstract

Teknologi kecerdasan buatan (AI) telah menjadi perhatian utama dalam penerapan Personal Identification (PI). Visi komputer sebagai subkategori AI bertujuan untuk mengekstrak informasi yang berguna dari gambar. Pengenalan wajah menjadi penting karena kompleksitas wajah manusia yang memiliki ciri-ciri berbeda. Penelitian ini berfokus pada pengenalan dan verifikasi wajah menggunakan computer vision dengan tujuan mendeteksi dan mengenali citra wajah seseorang secara akurat. Algoritma Histogram of Oriented Gradients (HOG) digunakan sebagai solusi praktis untuk meningkatkan efisiensi dan efektivitas dalam bidang keamanan dan aplikasi lainnya. Penelitian ini berkontribusi dalam mengembangkan teknik dan metode yang lebih baik untuk deteksi wajah dan pengolahan gambar dalam bidang teknologi informasi, khususnya dalam aplikasi pengenalan wajah. Hasil dari perancangan dan pengujian deteksi pengenalan dan verifikasi wajah berbasis computer vision menunjukkan bahwa program yang dibuat dari model algoritma HOG dengan fitcecoc multiclass SVM mampu mendeteksi citra wajah orang dengan baik setelah melewati proses testing, dengan tingkat akurasi mencapai 98.5714%.
DETEKSI PENGENALAN WAJAH ORANG BERBASIS AI COMPUTER VISION Finis Hermanto Laia; Rika Rosnelly; Alvinur Naswar; Karuniaman Buulolo; Mega Christin Morys Lase
Jurnal Teknologi Informasi Mura Vol 15 No 1 (2023): Jurnal Teknologi Informasi Mura Juni
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jti.v15i1.2024

Abstract

Teknologi kecerdasan buatan (AI) telah menjadi perhatian utama dalam penerapan Personal Identification (PI). Visi komputer sebagai subkategori AI bertujuan untuk mengekstrak informasi yang berguna dari gambar. Pengenalan wajah menjadi penting karena kompleksitas wajah manusia yang memiliki ciri-ciri berbeda. Penelitian ini berfokus pada pengenalan dan verifikasi wajah menggunakan computer vision dengan tujuan mendeteksi dan mengenali citra wajah seseorang secara akurat. Algoritma Histogram of Oriented Gradients (HOG) digunakan sebagai solusi praktis untuk meningkatkan efisiensi dan efektivitas dalam bidang keamanan dan aplikasi lainnya. Penelitian ini berkontribusi dalam mengembangkan teknik dan metode yang lebih baik untuk deteksi wajah dan pengolahan gambar dalam bidang teknologi informasi, khususnya dalam aplikasi pengenalan wajah. Hasil dari perancangan dan pengujian deteksi pengenalan dan verifikasi wajah berbasis computer vision menunjukkan bahwa program yang dibuat dari model algoritma HOG dengan fitcecoc multiclass SVM mampu mendeteksi citra wajah orang dengan baik setelah melewati proses testing, dengan tingkat akurasi mencapai 98.5714%.
Klasifikasi Citra Cuaca Menggunakan Inception-V3 dan K-Nearest Neighbors Iqbal Giffari Ritonga; Rika Rosnelly; Pius Deski Manalu; Teresa Tamba; Kristine Wau
JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Vol. 6 No. 2 (2023): Jutikomp Volume 6 Nomor 2 Oktober 2023
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jutikomp.v6i2.4052

Abstract

Weather imagery has a crucial role in various sectors, such as aviation, maritime and agriculture. Weather conditions have a big impact on activities in these fields and greatly influence operations. Classifying weather images can be done by analyzing weather image data, which can be used to predict the type of weather that may occur. The results of these weather predictions have significant value in daily decision making in these various sectors. One method for classifying weather images can be done by first extracting weather image features using Inception-V3 which is then calculated using the K-Nearest Neighbors method. This research uses 1748 weather images with 4 categories to carry out training which produces a model with Accuracy 91%, F1 91%, Recall 91%, Precision 91%, and uses 8 weather images with 4 categories to carry out testing which produces classifications with all correct values. every image.
Sentiment Analysis on Cyanide Case After 'Ice Cold' Aired with NLP Method using Naïve Bayes Algorithm Rahmatika Hizria; Sarwadi Sarwadi; Rabiatul Adawiyah Hasibuan; Ramadhani Ritonga; Rika Rosnelly
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3408

Abstract

Information technology is developing increasingly rapidly, and the reach of the Internet has expanded even to remote areas. The public increasingly uses social media as a source of information that discusses all aspects of people's lives. Social media has a vital role for most people, one of which is the news of the cyanide coffee case. The Cyanide Coffee case was discussed again by netizens after Netflix raised this case in a documentary film entitled Ice Cold, which made the public even more convinced of the irregularities of the case. Based on this, sentiment analysis is needed to extract comments to obtain public opinion information. The sentiment analysis aims to create a sentiment model to determine public comments on this case. Therefore, this research was conducted to find out and classify public sentiment on the Cyanide Coffee Case using the Natural Language Processing (NLP) method, which is a text preprocessing process followed by the tokenization stage. Data filtering was used using Indonesian Stopwords, and then normalization was continued using Porter Stemmer. In this study, data collection was carried out based on public comments on Ice Cold shows on the TikTok platform using TikTok Comments Scraper. The test results show that the classification using naïve Bayes obtained the results of 22 negative comments, 4052 neutral comments and 34 positive comments. The classification results of this study are 87% accuracy, 97.6% precision, 87% recall, and 91.9% F-Score.
Rancang Bangun Sistem Keamanan Pintu Rumah Menggunakan Arduino Berbasis Android Eko Setyo Budi Putra Aji; Rika Rosnelly
Computer Science Research and Its Development Journal Vol. 15 No. 1: February 2023
Publisher : LPPM Universitas Potensi Utama

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Abstract

Many people still find it difficult to secure their doors with the current technological orientation. Many people look for safety devices for their doors on various websites, but they are still constrained by the price and how to install the equipment purchased on their door. The existence of tools and applications for designing a home door security system is made with the aim of helping people to secure their door in an easier and more efficient way. The design of the home door security system with the available Android-based Arduino makes it easier for people to secure their home doors, of course, with guides and understanding of the tools described by the author. Tools made using Arduino and applications are made using the Java programming language. The system development, method for making this application uses the MIT App Inventor.
PERBANDINGAN ALGORITMA SUPPORT VECTOR MACHINE DAN K-NEAREST NEIGHBORS PADA KEMATANGAN BUAH SAWIT Syawaluddin Kadafi Parinduri; Rika Rosnelly; Anton Purnama; Ameliana Sihotang; Mimi Chintya Adelina
Device Vol 13 No 2 (2023): November
Publisher : Fakultas Teknik dan Ilmu Komputer (FASTIKOM) UNSIQ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32699/device.v13i2.5400

Abstract

Berdasarkan pengamatan dan hasi dari observasi, buah kelapa sawit memiliki suatu warna buah yang hampir sama yaitu berwarna hitam pekat atau hitam agak kekuning-kuningan saat mentah, dan berwarna merah tua saat matang. Sangat sulit untuk membedakan buah kelapa sawit yang matang dan mentah. Tandan buah kelapasawit memiliki jumlah buah yang banyak, dalam satu tandan diperkirakan beratnya mencapai kurang lebih 20 sampai 30 Kilogram. Untuk dapat mengetahui kematangan buah sawit tersebut, dibutuhkan suatu sistem untuk melakukan klasifikasi kematangan buah secara otomatis. Metode Support Vector Machine (SVM) dan K-Nearest neighbors (K-NN) dapat digunakan untuk klasifikasi buah kelapa sawit yang matang dan mentah. Kedua Metode ini akan digunakan untuk melihat kelebihan akurasi tertinggi. Sehingga Kedua metode ini, akan dibandingkan. dan bekerja baik dangan ruang dimensi yang tinggi dengan menggunakan bantuan aplikasi Orange data mining. Hasil yang diperoleh pada metode Support Vector Machine (SVM) skenario satu, mendapatkan nilai akurasi yang sangat baik, yaitu 100%. Pada skenario dua, dengan menggunakan metode K-Nearest neighbors (K-NN) mendapatkan nilai akurasi yang sangat baik juga sebesar 100%.. Hal ini membuktikan bahwa kedua metode tersebut dapat digunakan untuk mengklasifikasikan kematangan buah kelapa sawit dengan hasil yang sangat baik.
Feature Selection Analysis for Diagnosing Narcissistic Personality Disorder (NPD) Using Principal Component Analysis and the Naïve Bayes Model Sarwadi, Sarwadi; Rosnelly, Rika; Triandi, Budi
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 1 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i1.24086

Abstract

The mental health illness known as narcissistic personality disorder (NPD) affects a person's capacity to preserve harmonious social interactions. Early diagnosis plays a crucial role in providing timely intervention and treatment. This study examines the effectiveness of Principal Component Analysis (PCA) for feature selection in diagnosing NPD using the Naïve Bayes algorithm. The dataset utilized in this research was sourced from Open Psychometrics via Kaggle, followed by preprocessing, including data cleaning and dimensionality reduction through PCA. This study compares the performance of three Naïve Bayes models, Gaussian, Bernoulli, and Multinomial, to identify the most suitable classification approach. The findings reveal that Gaussian Naïve Bayes, when integrated with PCA, achieves the highest accuracy (91%), surpassing Bernoulli Naïve Bayes (80%) and Multinomial Naïve Bayes (69%). Implementing PCA significantly enhances computational efficiency and improves classification performance by eliminating irrelevant features and reducing data dimensionality. These results suggest combining PCA with Gaussian Naïve Bayes is a promising strategy for automating NPD diagnosis. Additionally, this study highlights the potential of machine learning in mental health evaluation and establishes the framework for further studies on hybrid models or other methods to improve prediction accuracy.
Co-Authors Abwabul Jinan Aditia Rangga Agung RM Alam Agus F Nduru Agus Fahmi Akbar Idaman Alan Prayogi Alesia Lorenza Sinaga Alvinur Naswar Alvinur Naswar Ameliana Sihotang Anton Purnama Arselan Ashraf B. Herawan Hayadi Batubara, Muhammad Akbarri Bob Subhan Riza Cindy Paramitha Cindy Paramitha Dedi Irawan Dedi Irawan Della Syahrani Desi Irfan Dian Maya Sari Diky Wahyudi Edy Victor Haryanto, Edy Victor Eko Setyo Budi Putra Aji Elly Veronika Sihite Elsa Aditya Eri Triwanda Esmawaty Sinaga Finis Hermanto Laia Gusti Firanda Hardianto Hardianto Hardianto Hardianto Hartono Hartono Hetty Zahrani IQBAL GIFFARI RITONGA Jaka Kusuma Jaka Tirta Samudra Jazmi Hadi Matondang Junaidi Junaidi Karuniaman Buulolo Kristine Wau Linda Wahyuni Linda Wahyuni Linda Wahyuni Lubis, Cindy Paramitha M Suhada WD M. Agung Oki Prayugo Maradona Jonas Simanullang MARIA BINTANG Masri Wahyuni Mega Christin Lase Mega Christin Morys Lase Mega Marisani Ziraluo Mimi Chintya Adelina Mira Kartiwi Muhammad Fachrurrozi Nasution Muhammad Sadikin Muhammad Zulkarnain Lubis Mutiara S. Simanjuntak Pius Deski Manalu Progresif Bulolo Progresif Bulolo5 Puji Sari Ramadhan Rabiatul Adawiyah Hasibuan Rahmatika Hizria Rais Affaruq Zunnurain Ramadhani Ritonga Ridha Maya Faza Lubis Ritonga, Iqbal Giffari Rofiqoh Dewi Rohima, Rohima Rony, Zahara Tussoleha Roslina, Roslina Rubianto Rubianto Rubianto Sartika Mandasari Sarwadi Sarwadi Sarwadi, Sarwadi Setiawan, Adil Syawaluddin Kadafi Parinduri Teddy Gunawan Teddy Surya Gunawan Teddy Surya Gunawan Teresa Tamba Tri Andre Anu Triandi, Budi Ubaidullah Hasibuan Wahyuni, Linda Wanayumini Wulandari, Wulandari Yuni Franciska Zakarias Situmorang Zuriati Janin