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INDONESIA
Jurnal Sistem Informasi
Published by Institut Teknologi dan Bisnis Ahmad Dahlan Jakarta
ISSN : 27978516     EISSN : 27978516     DOI : 10.32546
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Content-Based Multimedia Retrieval, Cultural Heritage Applications, Data Mining, Distance Learning, E-Business/E-commerce, E-Government, E-Health, Enterprise Architecture Design & Management, Geographic Information System (GIS), Human-Computer Interaction, Information Assurance & Intelligent, Information Security & Risk Management, IS Operations Management, IS Organization & Human Resource Management IS Strategic Planning, Web Science, Social Media in Business, Multimedia Application, Big Data Research, New Technology Acceptance and Diffusion, Green Information Systems, Innovation Management/Technopreneurship Dan lain-lain
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 52 Documents
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OPTIMASI ALGORITMA RANDOM FOREST UNTUK MENINGKATKAN AKURASI PREDIKSI INDEKS MASSA TUBUH (BMI) Juliani, Eva; Voutama, Apriade
Jurnal Sistem Informasi (JUSIN) Vol 6 No 1 (2025): Jurnal Sistem Informasi
Publisher : ITB Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/jusin.v6i1.3021

Abstract

Accurate Body Mass Index (BMI) prediction is essential for detecting obesity risks and related diseases. This study optimizes the Random Forest algorithm to enhance BMI prediction accuracy through hyperparameter tuning and feature selection. The dataset used is Obesity: Raw and Synthetic Data, which includes demographic and lifestyle variables. After undergoing subsetting, label encoding, and data imbalance handling using SMOTE, the model was trained using Random Forest and evaluated with accuracy, precision, recall, and F1-score metrics. The results indicate that the optimized model achieved 90% accuracy, with precision and recall of 0.89. Additionally, the feature importance analysis identified weight, height, and dietary habits as the most influential factors in BMI prediction. These findings confirm that optimizing the algorithm enhances model reliability in BMI classification and can be applied in data-driven health monitoring systems. This research is expected to contribute to the development of digital health applications and more accurate early obesity detection systems.
OPTIMALISASI SISTEM INFORMASI BERBASIS AGILE UNTUK PENGELOLAAN BIAYA VARIABEL DAN EXCHANGE RATE DI INDUSTRI FMCG Saputra, Muhammad Rizky; Voutama, Apriade
Jurnal Sistem Informasi (JUSIN) Vol 6 No 1 (2025): Jurnal Sistem Informasi
Publisher : ITB Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/jusin.v6i1.3039

Abstract

In the Fast Moving Consumer Goods (FMCG) industry, managing variable costs and exchange rates is a major challenge that affects operational efficiency and business decision-making. This study aims to develop an Agile-based information system that enables real-time data integration to improve transparency and accuracy in recording variable costs and exchange rates. The system was developed using the Agile Software Development methodology, consisting of Product Backlog, Sprint Planning, Daily Scrum, Development, Testing, and User Acceptance Testing (UAT). Key features include a variable cost and exchange rate dashboard, which provides structured data presentation, and an input form that facilitates users in entering and managing data according to operational needs. Testing was conducted through UAT involving the System Developer, IT Product team, and production team users. The results indicate that the system enhances cost recording efficiency, provides better visibility of exchange rate fluctuations, and accelerates data validation processes.
PENGELOMPOKAN PENJUALAN PRODUK DENGAN MENGGUNAKAN K-MEANS CLUSTERING : STUDI KASUS ANALISIS PENJUALAN COFFEE SHOP OLEH KAGGLE.COM Sifa, Sifa Rismawati; Shofa Shofiah Hilabi; Bayu Priyatna; Agustia Hananto
Jurnal Sistem Informasi (JUSIN) Vol 6 No 1 (2025): Jurnal Sistem Informasi
Publisher : ITB Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/jusin.v6i1.3078

Abstract

This study aims to group sales products in a coffee shop based on transaction data using the K-Means Clustering algorithm. The dataset from Kaggle.com includes the attributes product_id, transaction_qty, and unit_price. This method was chosen because of its ability to identify sales patterns in grouping products into three main clusters including high, medium, and low sales. The research process includes data collection, pre-processing, normalization, determining the optimal number of clusters, to evaluating the results using a Silhouette Score of 0.65. These results indicate that the K-Means method is effective in providing product segmentation that can be used as a basis for making business decisions, in optimizing stock and data-based marketing strategies.
ANALISIS FAKTOR SOSIAL EKONOMI YANG MEMPENGARUHI RENDAHNYA CAPAIAN PENDIDIKAN DI INDONESIA MENGGUNAKAN KOMBINASI METODE DATA MINING Yusuf, Diana; Razi, Fahrul
Jurnal Sistem Informasi (JUSIN) Vol 6 No 1 (2025): Jurnal Sistem Informasi
Publisher : ITB Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/jusin.v6i1.3115

Abstract

Educational inequality remains a persistent issue in Indonesia, particularly in regions with challenging socio-economic conditions. This study aims to analyze how various socio-economic factors influence the average years of schooling across Indonesian provinces using a combination of K-Means Clustering and Decision Tree algorithms. The dataset includes indicators such as poverty rate, gross regional domestic product (GRDP), per capita expenditure, and life expectancy, obtained from official national statistics. K-Means Clustering was employed to segment provinces into three distinct groups based on socio-economic similarities. The clustering revealed clear disparities among regions, where the most disadvantaged cluster showed significantly lower education levels. Subsequently, the Decision Tree algorithm was used to classify the average years of schooling, identifying per capita expenditure, life expectancy, and socio-economic cluster as the most influential variables. The combined approach allows for both segmentation and interpretation, providing data-driven insights that are accessible and actionable for policymakers. The findings highlight the importance of targeting socio-economic improvements as a strategy to enhance educational outcomes. Ultimately, this study underscores the value of integrating unsupervised and supervised machine learning models in addressing complex social issues in education.
PENGEMBANGAN APLIKASI BERBASIS WEB UNTUK PERAWATAN MOBIL DAN PENGELOLAAN BENGKEL DENGAN METODE PROTOTIPE Jondya, Aisha Gemala; Alva Davian Trisanto; Azizah Dinda Yukadifa; Muhammad Rizky Noval
Jurnal Sistem Informasi (JUSIN) Vol 6 No 1 (2025): Jurnal Sistem Informasi
Publisher : ITB Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/jusin.v6i1.3121

Abstract

This study presents the development of CekMobilmu.com, a web-based application designed to support car owners and automotive workshop in Jakarta by facilitating the digital recording of vehicle maintenance and repair activities. In response to the increasing technological advancement and rising demand for efficient service documentation, the application provides features for logging service history, monitoring vehicle condition, and managing workshop operations. Employing the Prototype Method, the research was conducted through sequential stages of data collection, system design, implementation, and evaluation. Data were obtained using questionnaires, interviews, and comparative analysis with existing similar applications. The evaluation phase demonstrated that the application effectively assists users in tracking maintenance schedules and enables workshops to record and manage repair tasks more efficiently. CekMobilmu.com addresses the communication gap between vehicle owners and service providers, offering a centralized and practical solution for vehicle maintenance management.
PENGARUH TIKTOK ADS DAN BLACK CAMPAIGN TERHADAP PERILAKU PEMBELIAN KONSUMEN DI KOTA BATAM R. Ilham Ramizan Fahris; Madison, Felix; Putra, Andiko Damar; Birra, Bimo; Ababil, Aelwen
Jurnal Sistem Informasi (JUSIN) Vol 6 No 1 (2025): Jurnal Sistem Informasi
Publisher : ITB Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/jusin.v6i1.3143

Abstract

The use of social media platforms such as TikTok as a tool for digital marketing continues to grow along with the increasing number of users, both for building brand awareness through TikTok Ads and indirectly through black campaigns. This study aims to analyze the influence of TikTok Ads and Black Campaigns on consumer purchasing behavior in Batam City. A quantitative method was employed by distributing online questionnaires to active TikTok users using stratified disproportional random sampling. Data analysis was conducted using SPSS software, including validity and reliability tests, multiple linear regression, and classical assumption testing. The results show that both TikTok Ads and Black Campaigns have a positive and significant influence on consumer purchasing behavior, with B coefficients of 0.360 and 0.390, respectively. These findings indicate that although black campaigns are negative in nature, their exposure can trigger consumer curiosity about the highlighted product. The implications of this study suggest that business actors need to be more selective and adaptive in developing digital marketing strategies, as consumer perceptions are influenced not only by positive promotions but also by the negative narratives circulating online. Therefore, ethical and fact-based communication strategies are key to maintaining consumer trust and brand reputation in the digital era.
RANCANG BANGUN SISTEM INFORMASI MONITORING PENCAPAIAN TARGET KINERJA PEGAWAI PADA PT. LABDA ANUGERAH TEKSTIL BERBASIS WEB MENGGUNAKAN METODE WATERFALL Putra, Komang Saskara; I Gede Juliana Eka Putra; Nengah Widya Utami
Jurnal Sistem Informasi (JUSIN) Vol 6 No 2 (2025): Jurnal Sistem Informasi
Publisher : ITB Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/jusin.v6i2.3225

Abstract

Kemajuan teknologi informasi berperan penting dalam berbagai sektor, termasuk manajemen kinerja pegawai. PT. Labda Anugerah Tekstil menghadapi permasalahan dalam pencatatan pekerjaan harian pegawai yang masih dilakukan secara manual, sehingga rawan terhadap kesalahan dan ketidakefisienan. Untuk mengatasi hal tersebut, penelitian ini merancang dan membangun sistem informasi monitoring pencapaian target kinerja pegawai berbasis web menggunakan framework Laravel dan metode Waterfall. Sistem ini mencakup fitur pencatatan aktivitas kerja pegawai, pengelolaan data tugas oleh admin, serta laporan pencapaian kinerja. Perancangan sistem dilakukan menggunakan Visual Studio Code, dengan HTML, CSS, Bootstrap, dan JavaScript untuk antarmuka pengguna, Laravel sebagai backend framework, dan TablePlus sebagai basis data. Pengujian dilakukan menggunakan metode Black Box Testing untuk memastikan semua fungsi sistem berjalan sesuai spesifikasi. Hasil penelitian menunjukkan bahwa sistem mampu meningkatkan efisiensi, akurasi, dan validitas pencatatan kinerja pegawai. Dengan data yang terstruktur dan terintegrasi, sistem ini mendukung pengambilan keputusan manajerial secara lebih cepat dan efektif.
ANALISIS PERBANDINGAN FRAMEWORK BACKEND NODE.JS DAN SPRINGBOOT MENGGUNAKAN METODE GRAPHQL barkah, affu; I Nyoman Yudi Anggara Wijaya; Nengah Widya Utami
Jurnal Sistem Informasi (JUSIN) Vol 6 No 2 (2025): Jurnal Sistem Informasi
Publisher : ITB Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/jusin.v6i2.3226

Abstract

As the demand for fast, responsive, and scalable web applications grows, API technologies have rapidly evolved. GraphQL offers efficient data management and transfer, with Node.js and Spring Boot being two widely used frameworks for its implementation. This study aims to compare the performance of GraphQL APIs built with these frameworks. Performance testing focused on response time, throughput, error rate, and concurrent user capacity, using dummy data under varying loads via Postman. Results show that under low loads (10 virtual users), both frameworks perform similarly. However, at higher loads (50 virtual users), Spring Boot demonstrates better performance with faster response time (514 ms vs. 1,766 ms), higher throughput (53.64 rps vs. 18.46 rps), and no errors, while Node.js records a 1.79% error rate. In Spike and Peak scenarios, Spring Boot consistently outperforms Node.js. These findings provide valuable insights for developers in selecting the most suitable framework based on application needs.
PERANCANGAN SISTEM RESERVASI DAN KASIR RESTORAN BERBASIS WEBSITE STUDI KASUS NYOMAN CAFE Abdullah, Mikail; I Nyoman Purnama; Ni Putu Noviyanti Kusuma
Jurnal Sistem Informasi (JUSIN) Vol 6 No 2 (2025): Jurnal Sistem Informasi
Publisher : ITB Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/jusin.v6i2.3230

Abstract

The advancement of information technology has driven various business sectors, including the culinary industry, to adopt digital systems to enhance operational efficiency and customer satisfaction. This study aims to design a web-based reservation and cashier system for Nyoman Cafe, a renowned seafood restaurant in Bali. The system addresses challenges in manual reservations and transaction recording, which often lead to errors, delays, and data inaccuracies. Utilizing the Prototipe method, the research involves stages of requirement gathering, interface design using Figma, and Prototipe evaluation to ensure the system aligns with user needs. The resulting system enables customers to make online table reservations with real-time availability access while simplifying transaction management through automated record-keeping features. This system is expected to improve operational efficiency, minimize errors, enhance customer experiences, and strengthen Nyoman Cafe's competitiveness in the culinary industry.
ANALISIS SENTIMEN OPINI MASYARAKAT TERKAIT PENGGUNAAN MOBILE JKN PADA MEDIA SOSIAL X MENGGUNAKAN ALGORITMA K-NEARESTNEIGHBOR (KNN) DAN LOGISTIC REGRESSION (LR) Hematang, Kelvin
Jurnal Sistem Informasi (JUSIN) Vol 6 No 2 (2025): Jurnal Sistem Informasi
Publisher : ITB Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/jusin.v6i2.3232

Abstract

BPJS Kesehatan launched the Mobile JKN application in 2017 to enhance healthcare accessibility and simplify membership management. As of September 2024, 98.67% of Indonesia’s population has joined the JKN program, highlighting the importance of public opinion in the application’s development. This study analyzes public sentiment toward Mobile JKN through the social media platform X using the K-Nearest Neighbor (KNN) and Logistic Regression (LR) algorithms. From 4,777 reviews, 4,648 clean data were obtained after preprocessing and labeled using IndoBERT, resulting in 2,066 positive reviews and 2,581 negative reviews. The evaluation results show that KNN achieved an accuracy of 83.87%, while LR performed better with 87.85% along with higher precision, recall, and f1-score. The findings reveal the dominance of negative sentiment in user reviews and provide insights for BPJS Kesehatan to improve Mobile JKN into a more responsive application that meets users’ needs and feedback.

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