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All Journal Riau Journal of Computer Science Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JITK (Jurnal Ilmu Pengetahuan dan Komputer) METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi MIND (Multimedia Artificial Intelligent Networking Database) Journal Jurnal Informatika Kaputama (JIK) Jurnal Sistem Informasi Kaputama (JSIK) Jurnal Mantik Jusikom: Jurnal Sistem Informasi Ilmu Komputer INFOKUM Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Journal of Computer Networks, Architecture and High Performance Computing Journal of Artificial Intelligence and Engineering Applications (JAIEA) TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Mardi Turnip, Mardi
Universitas Prima Indonesia
Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media

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APLIKASI SISTEM PENDUKUNG KEPUTUSAN ANALISA KELAYAKAN PERPANJANGAN KONTRAK Aisyah, Siti; Cahyadi, Andika; Wijaya, Benny; Turnip, Mardi
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 2 (2019): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (431.261 KB) | DOI: 10.34012/jusikom.v2i2.391

Abstract

Karyawan merupakan sumber daya yang paling berharga didalam sebuah organisasi. Kemajuan dari perusahaan salah satunya didukung dari kualitas karyawan yang baik. BCA salah satu instansi yang bergerak dibidang jasa perbankan. Tidak semua karyawan yang bekerja sudah menjadi karyawan tetap, ada beberapa diantaranya masih tercatat sebagai karyawan kontrak. Masalah yang sering dihadapi selama ini adalah sulitnya memilih karyawan yang akan dilakukan perpanjangan kontrak karena konsep penilaian masih bersifat konvensional. Sistem pendukung keputusan (SPK) merupakan salah satu aplikasi yang dapat membantu dalam proses pengambilan keputusan. SPK telah banyak digunakan sebagai alat bantu pemecahan masalah dalam sebuah keputusan didalam sebuah organisasi. Dengan melihat permasalahan yang dihadapi oleh Bank BCA dalam melakukan penilaian terhadap perpanjangan kontrak, maka perlu dibuat sebuah aplikasi yang dapat membantu dalam proses pengambilan keputusan agar sistem penilaian karyawan untuk perpanjangan kontrak menjadi lebih optimal. Dengan menerapkan metode topsis sebagai metode yang multikriteria, didapatkan penilaian terhadap data yang diuji adalah Christina Yaputra dengan nilai 0.7875, Andre Gumora dengan nilai 0.7694, Fendy Saputra dengan nilai 0.5018, Carvany dengan nilai 0.1462. Dengan kata lain, Christina Yaputra dan Andre Gumora akan mendapat perpanjangan kontrak karyawan diantara beberapa karyawan lain.
SISTEM PENCATATAN KEGIATAN PENELITIAN DAN PENGABDIAN BERBASIS WEB MENGGUNAKAN MODEL PROTOTYPE Marbun, Advent Toras; Turnip, Mardi; Pulungan, Jurmida; Purba, Joice Angelina; Dharma, Abdi
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 5 No. 1 (2021): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v5i1.1898

Abstract

Perkembangan Teknologi saat ini sangat pesat dalam segala bidang termasuk dalam bidang Pendidikan. Namun sampai saat ini masih banyak Kampus atau Perguruan Tinggi yang menggunakan sistem konvensional dalam kegiatan Penelitian dan Pengabdian. Berdasarkan hal tersebut diatas dibutuhkan Sistem Pencatatan Kegiatan Penelitian Pengabdian Masyarakat. Sistem yang dirancang menggunakan Model Prototype. Dengan adanya sistem ini  akan mempermudah proses atau kegiatan pelaksanaan penelitian di Perguruan Tinggi dan Universitas. Hasil persentase pada web yang dirancang yaitu penilaian desain kinerja diperoleh 89%, tampilan desain pada sistem persentase 90% , pengolahan data pada sistem 80%,  keamanan data 85% dan desain tampilan 95% Sehingga dinyatakan layak sebagai sistem pencatatan kegiatan penelitian berbasis web.
IMPLEMENTATION OF SMART IRRIGATION SYSTEM ON CARROT PLANTATION USING INTERNET OF THINGS Perangin-Angin, Despaleri; -, Yoga Tri Nugraha; -, Evta Indra; Turnip, Mardi; Situmorang, Andreas; Sitompul, Daniel Ryan Hamonangan; -, Ruben
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 5 No. 2 (2022): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v5i2.2347

Abstract

Agriculture is one of the main sectors in Karo Regency, North Sumatra. One of the commodities produced by farmers in Karo Regency is carrot. The inability of farmers to control soil moisture may cause crop damage to a lack of productivity. This research aims to create a monitoring & control system that is integrated with the website to make it easier for farmers to prevent problems that occur. The method used in the research is the design, installation, monitoring, and deactivation. The results obtained from this research are that farmers can now monitor the field conditions in real-time using a web-based monitoring & control system.
Utilization of Artificial Intelligence in Predicting Crime Carissa, Joan Stacia; Turnip, Mardi
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.v6i1.3208

Abstract

The problem of crime in Indonesia is an urgent issue, with crime rates continuing to increase. High crime rates have serious impacts on societal security, social stability, and economic development. Amidst the complexity of types of crime, motives and methods of handling them, Artificial Intelligence (AI) and Machine Learning (ML) technology has emerged as a promising solution. Through analysis of a literature review with the keywords "AI and crime," this research aims to understand the differences between the use of AI in crime prediction and traditional methods. The literature review method will identify and analyze the latest knowledge regarding the use of AI technology in overcoming crime problems. The use of AI in analyzing crime data, identifying complex patterns, and providing accurate predictions will be emphasized. The research will also explain how AI is able to overcome problems that are difficult to solve with conventional methods. It is hoped that the results of this literature review will provide deeper insight into the potential of AI in reducing crime rates and c reating a safer environment for people in Indonesia.
APPLICATION OF KNN METHOD FOR CLASSIFICATION OF ARRHYTHMIA TYPES BASED ON ECG DATA Manao, Sonatafati; Sitanggang, Delima; Sagala, Albert; Oktarino, Ade; Turnip, Mardi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6010

Abstract

World Health Organization (WHO) data from June 2024 shows that 31% of adults worldwide or 1.8 billion people do not do physical activity. With that, adults are at higher risk of developing cardiovascular disease and causing an economic and social burden on people with heart disease. K-Nearest Neighbor (KNN) is a machine learning method that can be used to classify or predict heart disease conditions. KNN works by finding the closest data point in the training dataset and then using the class labels of those neighbors to classify new data points. In the context of heart disease, this can be used to predict the likelihood of someone having heart disease. Recording the electrical activity of the heart using a 3-led ECG to determine heart health as well as being material for classification. Exploring the use in the diagnosis of heart disease by focusing on screening and classification of heart disease. By utilizing the KNN method, it has the potential to produce a model that can assist in clinical decision making. Improving the prevention of heart disease and accelerating diagnosis through more sophisticated and technology-based analysis of patient health data.
Application of the ANFIS Method to Predict Satisfaction with Facilities and Infrastructure Turnip, Mardi; Priambodo, Ganang Reza; Sihaloho, Theresia Delima; Ndruru, Jonathan Haris P.; Sigalingging, Josepta; Salsabillah; Panjaitan, Haposan Daniel
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.283

Abstract

Facilities and infrastructure are all movable or immovable objects or objects that are used to support every aspect of human life. Students, lecturers and office workers at least spend about half of their active hours at work. Therefore it is very important to pay attention to the high level of comfort, security, completeness in a building. There fore we need a way to predict satisfaction with facilities and infrastructure. To provide solutions to existing problems, the authors create applications that can predict the satisfaction of facilities and infrastructure. In this article, a satisfaction prediction approach based on a data-driven technique, representing system behavior using the Takagi-Sugeno model is developed. The Adaptive Neuro Fuzzy Inference System method is used to build a predictive model. The research was conducted by interview, observation and literature study. Data were taken from 92 respondents consisting of lecturers, students, and staff/employees in the research area. The test results using this method showed satisfactory results, indicating a success rate with an accuracy of 97.2%.
Aplikasi Sistem Informasi Manajemen Sekolah Terintegrasi dengan Pendekatan Rational Unified Process Hulu, Yosefa; Simbolon, Naftalia; Venta Br.Tarigan, Emma; Bunawolo, Methina; Turnip, Mardi
Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Vol. 3 No. 1 (2020): Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI)
Publisher : Utility Project Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9767/jikomsi.v3i1.77

Abstract

Perkembangan Teknologi Informasi dalam era globalisasi saat ini berkembang dengan sangat pesat. Hal tersebut berpengaruh terhadap berbagai bidang, salah satunya pada bidang pendidikan. Pendidikan saat ini dituntut harus dapat mengikuti dan mengimplementasikannya. Dalam penelitian ini akan dikembangkan Sistem Informasi Manajemen Sekolah Terintegrasi (SIMST) dengan pendekatan Rational Unified Process. Dengan adanya SIMST ini akan memberikan informasi yang cepat, akuntabel dan tepat guna. Selain berfungsi untuk meringankan kinerja guru dan staf-staf sekolah, sistem informasi yang dikembangkan juga akan sangat bermanfaat bagi siswa. Dengan adanya sistem akademik ini membantu para pengguna dalam melakukan pekerjaannya dan mengakses informasi sekolah.
ECG-BASED ARRHYTHMIA DETECTION USING THE NARROW NEURAL NETWORK CLASSIFIER Chandra, Angelia Ayu; Sunnia, Cecilia; Wijaya, Kenrick Alvaro; Dharma, Abdi; Turnip, Arjon; Turnip, Mardi
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 2 (2025): JITK Issue November 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i2.7121

Abstract

Electrocardiograms (ECG) are important for detecting arrhythmias. Conventional models such as CNN and LSTM are accurate but require large amounts of computation, making them difficult to use on wearable devices and for real-time monitoring. This study evaluates the Narrow Neural Network Classifier (NNNC) as a lightweight and efficient alternative. The dataset consists of 21 subjects with 881 ECG samples, categorized based on walking, sitting, and running activities, and processed through bandpass filtering, normalization, and P-QRS- T wave segmentation. The data is divided into training (70%), validation (15%), and test (15%) sets. The NNNC has 11 convolutional layers, a ReLU activation function, a Softmax output, and 120,000 parameters. The model was trained using the Adam optimizer, a batch size of 32, and a learning rate of 0.001 for 100 epochs and compared with SVM, CNN, and LSTM using accuracy, precision, recall, F1-score, and ROC-AUC. The results show that NNNC achieves an accuracy of 98.9%, a precision of 99.2%, a recall of 99.2%, and an F1-score of 99.2%, higher than SVM and comparable to CNN/LSTM, with lower computational consumption. The model is capable of reliably detecting early arrhythmias. These findings support the potential of NNNC for ECG-based automatic diagnostic systems, including real-time implementation on wearable devices, although further research is needed for large-scale validation
APPLICATION OF RANDOM FOREST ALGORITHM FOR ARRHYTHMIA DETECTION BASED ON ELECTROCARDIOGRAM DATA Turnip, Mardi; Situmorang, Fransido; William, David; Patterson, Jennifer; Ardila, Niki
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 2 (2025): JITK Issue November 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i2.7136

Abstract

Arrhythmia is a common cardiac disorder that requires early detection to prevent serious complications. This study applied the Random Forest algorithm to enhance electrocardiogram (ECG) analysis and enable accurate arrhythmia classification. Unlike prior studies that focused primarily on resting ECG signals, this research incorporated dynamic data collected from 26 participants performing three physical activities for three minutes each, capturing physiological variations across multiple activity states. The Random Forest model was constructed and evaluated using ECG-derived temporal and morphological features to detect potential arrhythmias. Experimental results showed that the model achieved an accuracy of 97.4%, with precision, recall, and F1-score each reaching 98%, and an AUC of 0.97. However, several limitations remain, including the relatively small and homogeneous sample, as well as the short recording duration. Nonetheless, the proposed approach demonstrates strong potential to support early cardiac screening and real-time monitoring, particularly in portable and resource-limited healthcare applications
Co-Authors -, aditya perdana -, Evta Indra -, Ruben Abdi Dharma Ade Irma Suryani Aditya Perdana aditya perdana - ADVENT TORAS MARBUN Albert Sagala, Albert Amri , Ahmad Alfauzan Ananda, Debby Andreas Theo Pilus Alista Teles Siahaan Ardila, Niki Arjon Turnip Astri Milleniar Marbun Banjarnahor, Jepri Bolon, Debby Novriyanti Br Tp. Bunawolo, Methina Cahyadi, Andika Carissa, Joan Stacia Chandra, Angelia Ayu Cindy Cynthia Debby Novriyanti Br Tp.Bolon Dedy Ristanto Hulu Delima Sitanggang, Delima Denny Irvan Sinuhaji Ester Ayu S. Marpaung Evta Indra Felix Widarko Hulu, Dedy Ristanto Hulu, Yosefa Intan Susanti Simarmata Joan Stacia Carissa Johan Libby JOICE ANGELINA PURBA JURMIDA PULUNGAN Kelvin M. Arif Almahdi Manao, Sonatafati MARBUN, ADVENT TORAS Marlince N.K Nababan Nababan, Marlince N.K Ndruru, Jonathan Haris P. Oktarino, Ade Owen Owen Panjaitan, Haposan Daniel Patterson, Jennifer Perangin-angin, Despaleri Priambodo, Ganang Reza PULUNGAN, JURMIDA PURBA, JOICE ANGELINA Roshan, Rohit Salmiati Salsabillah Saragi, Yosua Morales Saut Parsaoran Tamba Sigalingging, Josepta Sihaloho, Theresia Delima Simbolon, Naftalia Sinuhaji, Denny Irvan Sitanggang, Wahyu Adventus Andreas Siti Aisyah Sitompul, Daniel Ryan Hamonangan Sitorus, Dedi Setiadi Situmorang, Andreas Situmorang, Fransido Solly Aryza Sonia Novel Lase Sukhbir Singh Sunnia, Cecilia Tarigan, Julio Putra Tarigan, Richard Fernando Timi Tampubolon Venta Br.Tarigan, Emma Wijaya, Benny Wijaya, Kenrick Alvaro William, David Winarti Pasaribu Wong, Yano Sabar M Yenny Yenny Yoga Tri Nugraha