cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Delima Sitanggang
Contact Email
djoshlimasitanggang@gmail.com
Phone
-
Journal Mail Official
jusikom@unprimdn.ac.id
Editorial Address
Gedung Universitas Prima Indonesia, Medan Fakultas Teknologi dan Ilmu Komputer Jurusan Sistem Informasi Jl. Sekip Simpang Sikambing
Location
Kota medan,
Sumatera utara
INDONESIA
Jusikom: Jurnal Sistem Informasi Ilmu Komputer
Published by Universitas Prima Indonesia
ISSN : -     EISSN : 25802879     DOI : 10.34012
Core Subject : Science,
Decision Sciences, Operations Research & Management
This journal is about information systems and computer science.
Arjuna Subject : -
Articles 222 Documents
 19   20   21   22   23 
Application Of Support Vector Machine Method To Predict Heart Disease Simatupang, Golfrid Heraldi; Ompusunggu, Elvis
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 8 No. 1 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Heart attack disease is when the arteries are blocked by fatty deposits This results in symptoms like chest discomfort and dyspnea. Furthermore, Damage to the heart muscle can result from obstructed or reduced blood flow to the heart. Heart attack disease remains Indonesia’s greatest cause of death as of right now. The current problem is that it is very difficult to predict heart disease and identify heart disease. The right method is needed to predict heart disease. The purpose of this study was to calculate the level of accuracy of the Support Vector Machine method in predicting heart attack disease. The research findings and data analysis conducted utilizing the Support Vector Machine algorithm yielded an accuracy rate of 91.8%. Thus, it can be said that in comparison to the K-Nearest Neighbor approach, the support vector machine algorithm is superior in predicting the development of heart attack disease, which achieved an accuracy of 88%, and Logistic Regression, which achieved 83% accuracy. Keywords: Heart Attack, Support Vector Machine, Prediction.
Implementation Of The ARIMA Method In Predicting LQ 45 Stock Prices (UNTR Issuer) Hadiyanto, Tegas; Defit, Sarjon; Sovia, Rini
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 8 No. 1 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v8i1.5656

Abstract

The implementation of technology is used in running businesses or activities that generate profits, such as predicting investments on the stock exchange through transaction data in the transaction data base. Machine learning is an algorithm that produces an approximation function that connects input variables so that it has the potential to be implemented in stock predictions. Stock investment has the characteristics of high risk - high return. Losses are caused by investors' lack of knowledge. Stock value analysis is divided into two, namely fundamental analysis and technical analysis. Technical analysis uses data or records about the market to try to access the demand and supply of a particular stock or the market as a whole. Based on the problems found by investors or bankers, this research will use the autoregressive integrated moving average (ARIMA) method to predict stock price movements. The Arima method consists of four stages, namely identifying time series methods, estimating parameters for alternative methods, testing methods and estimating time series values. Based on these problems, the ARIMA method will be used to predict stock movements. The Arima model (1,0,2) with RMS: 2200.576849857124 successfully predicted for the next 180 days
Analysis and Design of Web-Based Inventory Receipt and Management Information Systems at Heycaps.Co Stores Using the Prototype Method Ni Putu Tia Ananda; Putri, I Gusti Agung Pramesti Dwi; Kusuma, Ni Putu Noviyanti
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 8 No. 2 (2025): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v8i2.5965

Abstract

Effective inventory management is crucial for Heycaps.co to ensure smooth operations and customer satisfaction. However, the current manual system results in inventory data inconsistencies, delays in the receipt of goods, and challenges in inventory tracking. This study aims to design a web-based inventory receipt and management information system to address these issues. The system is developed using a prototype approach, incorporating Flowcharts, Data Flow Diagrams (DFD), Entity Relationship Diagrams (ERD), Table Relations, and Database Table Structures. The interface design employs the Bootstrap framework to ensure a responsive and user-friendly display. The findings of this study present a system design that can be utilized by the owner, warehouse staff, and store staff to enhance inventory data management, streamline the receipt process, and improve the accuracy of inventory reporting. User evaluations indicate that the proposed system meets user requirements and offers ease of use. Keywords: Information System, Inventory, Prototype Method, Heycaps.co, Inventory  Management.
Current Trends and Future Directions of Big Data in Commerce: A Bibliometric Analysis Based on Scopus Almagribi, Ahmad Bilal; Putranto, Bambang Purnomosidi Dwi
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 8 No. 2 (2025): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v8i2.6098

Abstract

Big data provides significant benefits across various sectors, including commerce. However, there remained a gap in bibliometric studies examining big data within the context of commerce, leaving research development in this field unclear. This study aimed to address this gap by conducting a bibliometric investigation into researchers' contributions to big data in commerce, including their affiliations and countries of origin. Additionally, the study sought to identify the most productive journals and highlight relevant and under-researched topics within this field. A bibliometric analysis approach was employed, analyzing 396 Scopus-indexed documents and using VOSviewer visualization to identify major recurring issues in the literature. The findings revealed that in 2021, the number of publications on big data in commerce peaked at 97 documents. Maalla, A., from Guangzhou College of Technology and Business, China, emerged as the most prolific author, while China led in publication output with 308 documents. The Journal of Physics Conference Series was identified as the most productive source. Computer Science was the most explored discipline, indicating a strong integration of technology with commerce. Keyword analysis divided research focus into four main clusters: analytical technology, platform optimization, supply chain management, and marketing strategy optimization. These findings provide a foundation for future research to explore areas such as Customer Experience Management, Blockchain Technology, Cloud Computing, Predictive Analytics, and Customer Segmentation, thereby enriching the academic literature and offering practical contributions to data-driven commerce.
The Impact of Incremental Innovation at Gojek Startup on Users in Batam City Using the Expectation Confirmation Model Vincent, Vincent; Deu, Indasari; Eryc, Eryc
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 8 No. 2 (2025): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v8i2.6205

Abstract

In this modern era, the world has witnessed a phenomenal explosion in the growth of startups in various countries. Startups have become the main drivers of innovation and economic growth. Startup businesses are currently experiencing significant and rapid growth, especially in Indonesia. Currently, there are many new startup companies, so innovation is needed to compete with other competitors. Startup development requires creative ideas to attract investors. In addition to innovative ideas, product quality must also be a priority to attract consumer interest. Therefore, this study aims to examine the impact of incremental innovation on startups from the perspective of users in Batam City. The purpose of this study is to examine the impact of incremental innovation on the Gojek application. The author uses the Structural Equation Model (SEM) with the Partial Least Squares method, then the researcher applies the Extended Expectation Confirmation Model (ECM) from the perspective of Gojek application users to analyze the effect of incremental innovation efforts on the Gojek application. The author collects data by distributing questionnaires to people who have made transactions with Gojek. A total of 264 samples have been collected, and the results show that confirmation has a positive effect on the perception of enjoyment, satisfaction, and customer engagement. The results show that the perception of enjoyment and satisfaction has a positive impact on the user's intention to continue using the Gojek application. However, customer engagement does not significantly affect the user's intention to continue using the Gojek application.
Comparative Analysis of the Customer Satisfaction Index and Service Quality Methods in Measuring BPJS Patient Satisfaction at Royal Prima Hospital Zevanya, Ria Putri; Sari , Christine Ester Novita; MPH, Rafael Crisman; Batubara, Muhammad Rusdi; Nasution, Donni
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 8 No. 2 (2025): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Patient satisfaction is an important indicator for assessing the quality of healthcare services, especially for hospitals serving BPJS patients. By understanding the level of patient satisfaction, hospitals can identify what is performing well and what needs improvement in their services. The objective of this study is to compare two methods, namely the Customer Satisfaction Index (CSI) and Service Quality (Servqual), in measuring BPJS patient satisfaction at Royal Prima Hospital. The CSI method quantitatively measures overall patient satisfaction, while the Servqual method evaluates satisfaction based on four service quality dimensions. This research was conducted through questionnaires distributed to 300 BPJS patients who had received medical services at Royal Prima Hospital. The research findings indicate that the Servqual method produced an average satisfaction score of 2.74, while the CSI method achieved a satisfaction score of 0.69, which falls into the "Good" or "Satisfied" category. These findings demonstrate that both methods complement each other, providing a more effective and comprehensive understanding of patient satisfaction.
Exploratory Data Analysis Historical Cryptocurrency Panjaitan, Ezra Christina Septiana; Indra, Evta
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 8 No. 2 (2025): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini menganalisis data historis cryptocurrency menggunakan metode Exploratory Data Analysis (EDA) untuk membantu investor pemula memahami pergerakan harga mata uang kripto. Cryptocurrency, sebagai uang digital yang tidak berwujud fisik, memiliki tingkat volatilitas tinggi yang sering menyebabkan kerugian bagi investor yang kurang berpengalaman dalam menganalisis data historis. Menggunakan dataset dari CoinMarketCap yang terdiri dari 679.183 baris dan 13 kolom periode 2017-2022, penelitian ini menerapkan metodologi EDA dengan pendekatan visualisasi data. Prosedur penelitian mencakup analisis masalah, data acquisition melalui web scraping, data cleaning, dan exploratory data analysis. Hasil analisis menunjukkan persaingan antara Bitcoin dan Ethereum. Berdasarkan marketval, Bitcoin mencapai $140.000.000.000, sementara Ethereum $80.000.000.000. Volume Bitcoin mencapai $8.000.000.000, sedangkan Ethereum $4.000.000.000. Analisis price movement menunjukkan Ethereum mencapai $140.000, sementara Bitcoin $1. Dalam analisis moving average, Ethereum menunjukkan performa lebih baik dengan grafik mencapai $105.000, dibandingkan Bitcoin yang hanya mencapai $0,8. Penelitian ini berkontribusi dalam membantu investor pemula memahami dinamika pasar cryptocurrency melalui analisis data historis. Hasil visualisasi dan analisis dapat digunakan sebagai acuan pengambilan keputusan investasi dan meminimalisir risiko kerugian. Studi ini merekomendasikan penggunaan data historis sebagai alat prediksi dibandingkan pengambilan keputusan berbasis intuisi dalam investasi cryptocurrency.
Core Banking Testing Pada Fitur Customer Transaction di BPR Lestari Bali Ni Putu Yuliawati, Putu Arya Novianingsih; Widya Utami, Nengah; Dwi Putri, I Gusti Agung Pramesti
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 8 No. 2 (2025): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

BPR Lestari Bali adalah salah satu Bank Perkreditan Rakyat (BPR) terbesar di Bali yang dikenal sebagai pelopor dalam memberikan layanan keuangan kepada masyarakat lokal. Saat ini, BPR Lestari tengah merumuskan strategi untuk meningkatkan kualitas layanan dan efisiensi aktivitas perbankan melalui implementasi sistem terintegrasi, yaitu Core Banking System (CBS). CBS merupakan platform yang dirancang untuk mengelola berbagai operasi inti perbankan, seperti penyimpanan data nasabah, transaksi harian, dan layanan digital. Penelitian ini dilakukan dengan tujuan untuk menguji CBS yang telah dikembangkan menggunakan metode BlackBox Testing dengan teknik Equivalence Partitioning, yang menekankan evaluasi fungsionalitas sistem tanpa menganalisis struktur internal kode. Pengujian dilakukan fokus pada fitur Customer Transaction, yang terdiri dari enam modul utama, yaitu: Transaction, Deposit, Customer, Collateral, Account & Wallet, serta Lending. Hasil pengujian menunjukkan tingkat keberhasilan mencapai 98,38%. Lima dari enam modul berhasil menunjukkan tingkat keberhasilan sebesar 100%, sedangkan modul Customer mencapai tingkat keberhasilan 87,5% akibat adanya bug yang memerlukan penyelesaian lebih lanjut oleh developer. Dari pengujian ini, dapat disimpulkan bahwa metode BlackBox Testing dengan teknik Equivalence Partitioning efektif dalam memastikan fungsionalitas CBS, mengurangi risiko gangguan layanan, dan meningkatkan kepercayaan pengguna terhadap sistem.
Analisis dan Perancangan Sistem Keuangan Universitas Primakara Menggunakan Unified Modeling Language (UML) dengan Metode Agile Djohan, Hananindita; Dwi Putri, I Gusti Agung Pramesti; Suyasa, I Putu Buda
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 8 No. 2 (2025): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Perkembangan teknologi informasi mendorong efisiensi dalam pengelolaan informasi, termasuk implementasi sistem informasi. Universitas Primakara membutuhkan sistem informasi keuangan untuk mengatasi pengelolaan tagihan UKT mahasiswa yang masih manual dan kurang terintegrasi. Penelitian ini bertujuan merancang pemodelan sistem keuangan menggunakan Unified Modeling Language (UML) dengan metode Agile. Pemodelan dilakukan melalui use case diagram, activity diagram, sequence diagram, dan desain database menggunakan Entity Relationship Diagram (ERD). Hasil penelitian menunjukkan bahwa metode Agile dengan kerangka kerja Scrum efektif dalam menghasilkan pemodelan sistem yang sesuai dengan kebutuhan pengguna. Pemodelan ini mempermudah pengelolaan tagihan UKT secara terintegrasi. Kesimpulannya, metode Agile dan UML terbukti adaptif dan komprehensif untuk perancangan sistem informasi keuangan Universitas Primakara.
Analisis Akurasi Algoritma K-Nearest Neighbor Untuk Diagnosis Penyakit Jantung Pada Lansia Sipayung, David Sebastian; Syarifah Atika
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 8 No. 2 (2025): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penyakit jantung adalah salah satu penyebab utama kematian di dunia, terutama pada populasi lansia, yang sering kali sulit dideteksi pada tahap awal karena gejala yang tidak spesifik. Oleh karena itu, diperlukan metode diagnosis yang lebih cepat dan efisien, seperti penerapan algoritma pembelajaran mesin. Penelitian ini bertujuan untuk mengevaluasi akurasi algoritma K-Nearest Neighbor (KNN) dalam mendiagnosis penyakit jantung pada lansia, dengan menggunakan dataset yang diperoleh dari Kaggle dan terdiri dari 918 data pasien. Data tersebut disaring untuk usia lansia (60 tahun ke atas), menghasilkan 253 data yang digunakan dalam klasifikasi. Empat nilai k (3, 5, 7, dan 9) diuji untuk menentukan nilai k terbaik dalam mengklasifikasikan penyakit jantung. Hasil evaluasi menunjukkan bahwa model dengan k = 9 memiliki performa terbaik dengan nilai recall tertinggi (0.93) dan F1-Score sebesar 0.81, meskipun dengan akurasi yang sedikit lebih rendah (0.68). K = 5 memberikan keseimbangan terbaik antara precision (0.72) dan recall (0.85), dengan F1-Score 0.78. Berdasarkan hasil ini, K = 9 lebih efektif untuk aplikasi medis yang mengutamakan deteksi lebih banyak kasus positif, meskipun mengorbankan sedikit precision. Penelitian ini dapat memberikan kontribusi untuk pengembangan sistem diagnosis penyakit jantung yang lebih cepat, efisien, dan akurat pada lansia, dengan harapan dapat meningkatkan deteksi dini penyakit jantung.

Page 22 of 23 | Total Record : 222

 19   20   21   22   23 

Filter by Year

2017 2025


Reset
Filter By Issues
All Issue Vol. 8 No. 2 (2025): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER Vol. 8 No. 1 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER Vol. 7 No. 2 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER Vol. 7 No. 1 (2023): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER Vol. 6 No. 2 (2023): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP) Vol. 6 No. 1 (2022): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP) Vol. 5 No. 2 (2022): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP) Vol. 5 No. 1 (2021): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP) Vol. 4 No. 2 (2021): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP) Vol. 4 No. 1 (2020): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP) Vol. 3 No. 2 (2020): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP) Vol. 3 No. 1 (2019): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP) Vol. 2 No. 2 (2019): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP) Vol. 2 No. 1 (2018): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP) Vol. 1 No. 2 (2018): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP) Vol. 1 No. 1 (2017): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP) More Issue