cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Muhammad Amanulloh Mz
Contact Email
top.rampublisher@gmail.com
Phone
+628557068499
Journal Mail Official
top.rampublisher@gmail.com
Editorial Address
Beji, Sawiji, Kec. Jogoroto, Kabupaten Jombang, Jawa Timur, Indonesiadex
Location
Unknown,
Unknown
INDONESIA
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan
Published by RAM PUBLISHER
ISSN : -     EISSN : 30323991     DOI : -
Core Subject : Humanities, Science, Engineering,
Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan or in English the publication title Information Systems, Engineering and Applied Technology is an open access journal committed to publishing high quality research articles in the fields of Information Systems, Informatics, Digital Communication Information Technology, Tourism Technology, Transportation Technology, Agricultural Technology, Plantations, Fisheries, Marine, Environmental Technology, Artificial Intelligence, Mechanical Engineering, Electrical Engineering, Industrial Engineering and Civil Engineering. Published 4 X (Times) a year in January, April, July, and October. SITEKNIK accepts and selects quality articles and focuses on providing the best service for writers. SITEKNIK is committed to being a leading platform for researchers to share their innovative findings. We also provide a fast and transparent review process to ensure the quality and originality of each published article.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 44 Documents
 1   2   3   4   5 
Optimization of Stress Classification Among Students Using Random Forest Algorithm Raffa Nur Listiawan Dhito Eka Santoso; Kusnawi
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 2 No. 2 (2025): April
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15130385

Abstract

Stress is a condition of physical and psychological discomfort experienced by students due to academic pressure, demands from parents and teachers, and schoolwork. This stress can lead to physical tension, behavioral changes, and mental health problems if not handled properly.  Random Forest is a promising approach to analyze and classify student stress. The aim of this study is to classify stress among students to enable the development of targeted interventions to support student well-being and academic success. The dataset used was sourced from Kaggle and included 1100 datasets with 21 columns. The research stages included data preprocessing, exploratory data analysis, modeling, Decision tree classification and evaluation of the confusion matrix model and Deployment as a measure of stress level. Classification results were evaluated by calculating accuracy, precision, recall and f1-score for stress classes (low, medium and high). The results of this study resulted in an accuracy value before tuning of 87.27% and after tuning of 88.64%. This research can provide insights for schools, parents, and government to develop more effective strategies in addressing the problem of stress among students. The use of Random Forest algorithm is proven to be effective in analyzing and classifying stress, so that it can help in decision making and appropriate welfare interventions to tackle before stress reaches critical levels.
Trends and Innovations in CRM for Patient Management: A Literature Review Muhdiantini, Cindy; Fitri Yani, Mega; Ibnu Zulkarnain
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 2 No. 2 (2025): April
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15180642

Abstract

Customer Relationship Management (CRM) in healthcare services has evolved rapidly with advancements in information technology. CRM not only functions as a patient relationship management tool but also as a solution to enhance data-driven care, service personalization, and operational efficiency. Current trends in CRM involve the utilization of Artificial Intelligence (AI) and Machine Learning (ML), integration with wearable devices for real-time health monitoring, the use of Big Data for analyzing population health trends, as well as the adoption of telemedicine and mobile health applications connected to CRM. This study aims to review the latest developments in CRM for patient management and its impact on healthcare systems.
Customer Relationship Management (CRM) Strategy of PT ASDP Indonesia Ferry (Persero): A Customer Satisfaction and Digital Transformation Approach Hasan Abdullah Muhammad; Fitri Adini Firdaus; Ni Ketut Mega Diana Putri
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 2 No. 2 (2025): April
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15191978

Abstract

This study evaluates the CRM strategy of PT ASDP Indonesia Ferry through a mixed-methods approach combining survey data from 2,000 customers and in-depth interviews with company directors. The 2023 Customer Satisfaction Index score of 5.34 reveals improved but uneven performance, with walk-on passengers (5.39) significantly more satisfied than vehicle users (5.31). While digital initiatives like the Ferizy platform and service standardization programs show promise, key challenges emerge in three areas: persistent offline transaction preferences (80% among vehicle users), inconsistent service quality across branches (CSI range 5.13-5.41), and growing competitive pressures. The analysis identifies successful CRM pillars including digital transformation, service excellence programs, and targeted engagement strategies, but highlights the need for more segmented approaches to address distinct customer needs. Strategic recommendations emphasize enhanced digital integration with real-time tracking capabilities, operational improvements in fleet management, and continuous performance monitoring systems. These findings contribute practical insights for transportation service providers operating in archipelagic environments, demonstrating how CRM implementation must balance technological innovation with operational realities to achieve sustainable customer satisfaction improvements.
Optimization of Random Forest Algorithm Using Random Search for Alzheimer's Disease Detection Wahyudi, Hasyim Sri; Ferian Fauzi Abdulloh
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 2 No. 3 (2025): July
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.16554889

Abstract

Alzheimer's disease is a type of neurodegenerative disorder that causes a decline in cognitive function. Early detection is crucial to enable more effective interventions and slow the progression of the disease. However, the diagnosis of Alzheimer's disease often faces challenges, particularly in detecting the early stages of the disease from complex and diverse medical data. This study aims to optimize the Random Forest algorithm using the Random Search method for detecting Alzheimer's disease. The Random Forest algorithm was applied as the primary model in this research, while hyperparameter optimization was performed using the Random Search method to improve model performance. The results showed that the Random Forest model without optimization achieved an accuracy of 96%. After performing hyperparameter optimization, the model's accuracy increased to 97%. In conclusion, the application of hyperparameter optimization using the Random Search method successfully enhanced the performance of the Random Forest model. The resulting model provides more accurate predictions, making it a reliable tool for the early detection of Alzheimer's disease.
Random Search Optimization Using Random Forest Algorithm For Liver Disease Prediction BAYU SATRIYA, RIYAN; Kusnawi, Kusnawi
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 2 No. 3 (2025): July
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15468679

Abstract

The liver is a vital human organ with complex and diverse functions. One of the diseases that affect the liver is hepatitis or liver disease. Early detection is crucial to enable more effective intervention and slow the progression of the disease. However, diagnosing liver disease often faces challenges, especially in detecting the early stages of the disease from complex and diverse medical data. This study aims to optimize the Random Forest algorithm using the Random Search method for liver disease detection. The Random Forest algorithm is applied as the primary model in this research, while hyperparameter optimization is performed using the Random Search method to enhance model performance. The results show that the Random Forest model without optimization achieves an accuracy of 93%. After hyperparameter optimization, the model's accuracy increases to 94%. In conclusion, applying hyperparameter optimization using the Random Search method successfully improves the performance of the Random Forest model. The resulting model provides more accurate predictions.
Analysis of Digital Governance Framework Implementation to Enhance Digital Transformation Farhana Zahra
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 2 No. 3 (2025): July
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15400843

Abstract

Digital transformation (DT) is increasingly crucial for public and private organizations seeking agility and efficiency. However, many entities pursue DT initiatives without first establishing a structured digital governance framework, resulting in fragmented implementation and strategic misalignment. This study aims to analyze how the absence of governance mechanisms affects transformation effectiveness and identify foundational elements necessary to initiate governance in such contexts. The novelty of this research lies in its analytical focus on organizations lacking pre-existing governance structures. Unlike prior studies that assume the presence of governance, this research offers insights for institutions starting from zero. Using a qualitative descriptive method through literature review and document analysis, this study investigates key governance gaps, risks, and challenges in low-governance environments. The findings reveal that the absence of digital governance leads to inefficiencies, redundant systems, poor risk management, and low accountability. By synthesizing best practices and proposing phased implementation strategies, the research provides practical guidance to build governance capabilities from the ground up. This study offers both theoretical contributions and actionable recommendations for sustainable digital transformation.
Increasing the Turnover of MSMEs in Healthy Beverages Through Digital Marketing Strategies: A Case Study of Shuguci and WHF MSMEs Dr. Mochamad Teguh Kurniawan, ST., MT; Fadilah, Samia
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 2 No. 3 (2025): July
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15537420

Abstract

This study aims to analyze the effectiveness of applying Digital Marketing strategies in increasing the revenue and brand awareness of the Healthy Beverage MSMEs, Shuguci and WHF. The method used is qualitative with a case study approach, where data were collected through observation, in-depth interviews, and documentation of the MSMEs' digital marketing activities.The results show that after the mentoring program, the MSMEs' revenue increased by 50%, accompanied by improved understanding among owners and employees regarding digital marketing strategies. They are now more adept at using hashtags, determining optimal posting times, segmenting markets, and utilizing trending music in digital content. Additionally, customer interaction significantly improved, as indicated by the growing number of customers reaching out via direct messages during promotions and actively participating in live sessions on social media. The referral program offering discounts to customers who recommended the products also proved effective in increasing the number of new customers. It can be concluded that implementing Digital Marketing strategies can be an effective solution for MSMEs to increase their revenue and brand awarene
A Comparative Study of Lean Startup and Design Thinking to Accelerate Startup Market Adaptation Diki , Diki Wahyudi
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 2 No. 3 (2025): July
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15537556

Abstract

This study aims to compare two popular innovation approaches, namely Lean Startup and Design Thinking, in the context of speed of responding to market needs. Lean Startup is known for its focused scientific method that encourages hypothesis testing and product validation through the Build-Measure-Learn cycle, while Design Thinking emphasizes deep understanding of users and the creation of innovative solutions through the process of research, problem definition, ideation, prototyping, and evaluation. Through literature analysis and comparison of the two approaches, this study found that although both have the same goal of creating relevant products, they have different methods and focuses. Lean Startup is more efficient in a dynamic and competitive environment, while Design Thinking produces solutions that are more in line with user needs. This study recommends that companies and innovators consider the specific context of the innovation project being implemented and combine elements of both approaches to achieve optimal results. These findings provide valuable insights into the application of Lean Startup and Design Thinking in product development and innovation.
Business Model for Effectiveness of Human-AI Collaboration Patterns in Digital Fiction Storytelling: A Systematic Literature Review Thamrin, Daffa Shidqi
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 2 No. 3 (2025): July
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15788175

Abstract

The unavoidable pace of Artificial Intelligence (AI) is changing its role from a simple tool to a potential thought partner in various creative fields, including digital storytelling. This research discusses the effectiveness of human-AI collaboration patterns specifically in the aspect of fictional storytelling, for which creativity, narrative structure, and imagination are crucial. By a Systematic Literature Review (SLR), this research synthesizes results from published article research from 2020 to 2025, with the focus on how AI supports and co-creates with human authors throughout the storytelling process. This research also discovered and identified several benefits, which include increased creativity, idea generation, and efficiency, and also discussed challenges such as authority for storytelling, author originality, and ethical considerations in the ownership of a story. This research also discusses implications for future development and proposes a collaboration model that involves two types of human actors, which are writers and editors, and then collaborating with an AI system by a human-centered business design approach. Those results offer a framework business model for implementing practical storytelling systems by results of literature review and suggest that fictional storytelling may be an ideal and potential field for learning about AI's creative potential. The contribution of this research is the aspect of human-centered AI and provides guidelines for designing collaborative storytelling platforms that include both human and AI roles
Perancangan Sistem Pemesanan pada Usaha Mikro, Kecil, dan Menengah (UMKM) LA Group Kabupaten Jombang Berbasis Website Arif, Muhammad Arif Zikir Risky
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 2 No. 3 (2025): July
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15752546

Abstract

UMKM LA Group, usaha mikro di Jombang yang menyediakan jasa sewa makeup, hairdo, dekorasi lamaran, serta baju pengantin dan adat, menghadapi kendala serius dengan proses pemesanan manual. Metode ini, yang mengandalkan media sosial dan aplikasi pesan instan, menyebabkan pencatatan tidak akurat, konfirmasi lambat, dan manajemen data transaksi yang tidak efisien. Untuk mengatasi masalah ini, sebuah sistem pemesanan berbasis web telah dirancang dan diimplementasikan menggunakan PHP dan MySQL. Tujuannya adalah mempermudah pelanggan dalam melakukan pemesanan sekaligus membantu UMKM mengelola data pesanan secara lebih sistematis, terintegrasi, dan efisien. Pengembangan sistem ini mengikuti model Waterfall, meliputi analisis kebutuhan, perancangan sistem, implementasi, pengujian, dan pemeliharaan. Pendekatan ini dipilih karena strukturnya yang sistematis, menjamin pengembangan yang terorganisir dan terdokumentasi dengan baik. Hasil pengujian black box menunjukkan bahwa semua fungsi sistem berjalan sesuai spesifikasi, tanpa ditemukan kesalahan pada proses input, pengolahan, maupun output data. Sistem ini terbukti meningkatkan efisiensi pemrosesan pesanan, mengurangi kesalahan pencatatan, dan mempercepat pelayanan pelanggan. Dengan adanya sistem ini, UMKM LA Group kini dapat mengelola pesanan secara lebih profesional, terstruktur, dan terdokumentasi.

Page 3 of 5 | Total Record : 44

 1   2   3   4   5 

Filter by Year

2024 2025


Reset
Filter By Issues
All Issue Vol. 2 No. 4 (2025): October Vol. 2 No. 3 (2025): July Vol. 2 No. 2 (2025): April Vol. 2 No. 1 (2025): January Vol. 1 No. 2 (2024): July Vol. 1 No. 1 (2024): January