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CICES (Cyberpreneurship Innovative and Creative Exact and Social Science)
Published by UNIVERSITAS RAHARJA
ISSN : 23565209     EISSN : 26553058     DOI : 10.33050/cices
Core Subject : Economy, Science, Social,
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice
CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) adalah wadah publikasi jurnal ilmiah untuk multidisiplin ilmu seperti Bidang Ilmu Politik, Ekonomi, Manajemen, Sosial, Ideologi, IT, Budaya dan Pendidikan. CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) is a place for publishing scientific journals for multidisciplinary sciences such as Politics, Economics, Management, Social Sciences, Ideology, IT, Culture and Education.
Arjuna Subject : Umum - Umum
Articles 213 Documents
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Sistem Pakar Diagnosa Penyakit ISPA Melalui Integrasi Metode Naïve Bayes dan K-Nearest Neighbors Putra, Dimas Ariwibowo; Haryanto, Haryanto; Sany, Nasril
CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Vol 10 No 2 (2024): CICES
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cices.v10i2.3412

Abstract

Acute Respiratory Infections (ISPA) is one of the common health problems worldwide, causing serious impacts on individuals and communities. To assist in the early diagnosis of ISPA, an expert system has been developed. This system utilizes the integration of Naive Bayes and K-Nearest Neighbors (K-NN) methods to analyze the symptoms provided by users and provide accurate diagnoses. The Naive Bayes method is used to calculate the probability of each symptom for various ISPA diseases, while K-NN is used to identify patterns and relationships among the given symptoms. The integration of these two methods allows the system to leverage the strengths of each, improving accuracy and reliability of diagnosis. The system has been tested using ISPA symptom datasets, and the results demonstrate the system's ability to provide rapid and accurate diagnoses. Thus, the development of this expert system is expected to assist medical professionals in the early diagnosis of ISPA, enabling more effective treatment and preventive measures.
Pengaruh Manajemen Piutang Terhadap Profitabilitas Studi Industri Di Tangerang Mukhlisiah, Rizka; Haryanto, Haryanto
CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Vol 11 No 1 (2025): CICES
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cices.v11i1.3227

Abstract

Working capital in management is very important for the survival of an organization. It is also important for the growth of an organization. Management of receivables is an important component of working capital management carried out in a company. The current study empirically tests the effect of the efficiency of receivables management as measured by the debtor turnover ratio in the commercial industry in Indonesia on the profitability of the company. Profitability is measured using the returned capital. The study was conducted in the period 2019 to 2021. The findings show a significant positive relationship between the debtor turnover ratio and the company's profitability. This indicates that receivables management must be the main focus in increasing the profitability of industrial companies.
Efektivitas Digital Learning Platform terhadap Motivasi Mahasiswa menggunakan Studi Literatur Sunarjo, Richard Andre; Yusup, Muhammad; Andayani, Dwi; Alwiyah, Alwiyah; Khairunnisa, Novita; Khanza, Aulia
CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Vol 11 No 1 (2025): CICES
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cices.v11i1.3234

Abstract

Penelitian ini bertujuan untuk mengeksplorasi dan mengevaluasi penerapan digital learning platform untuk meningkatkan motivasi mahasiswa di era digital. Di tengah perubahan lanskap pendidikan yang dipengaruhi oleh teknologi, motivasi mahasiswa menjadi faktor kunci keberhasilan belajar. Penelitian ini mengintegrasikan konsep-konsep dari teori motivasi, teknologi pendidikan, dan metode digital learning platform untuk merancang strategi pembelajaran yang berfokus pada partisipasi aktif mahasiswa. Pendekatan penelitian memadukan untuk memahami dampak penerapan metode digital learning platform terhadap motivasi mahasiswa. Temuan menunjukkan bahwa penggunaan metode digital learning platform, seperti pembelajaran berbasis realita virtual, pembelajaran berbasis gamifikasi, dan metode pembelajaran simulasi komputer dapat meningkatkan keterlibatan dan motivasi mahasiswa dalam belajar secara signifikan. Implikasi dari penelitian ini menunjukkan bahwa penerapan digital learning platform dapat memberikan manfaat yang signifikan bagi mahasiswa, termasuk peningkatan motivasi, keterlibatan, dan keterampilan belajar. Dengan memanfaatkan teknologi digital secara efektif, mahasiswa dapat mencapai hasil belajar yang lebih baik dan siap menghadapi tantangan di era digital.
Klasifikasi Nilai Ujian Menggunakan Algoritma C5.0 di SMA Hangtuah 2 Sidoarjo Pratiwi, Nisa; Anggraeny, Fetty Tri; Swari, Made Hanindia Prami
CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Vol 11 No 1 (2025): CICES
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cices.v11i1.3490

Abstract

Hangtuah 2 Sidoarjo High School is one of the educational institutions that implements intensive data management practices in all its operational activities. These activities start from processing student personal data, teacher lesson schedules, teaching management, attendance management, library management, financial management as well as evaluating and reporting student grades. In the evaluation process, teachers at Hangtuah 2 Sidoarjo High School often make mistakes in filling in the value data because there is too much data, so that the management of student grades becomes slow and calculation errors occur, resulting in ineffective classification of student grades. For this reason, this research aims to design an academic management system and test score classification using the C5.0 algorithm. With this system, it will be easier for administrators, teachers, librarians and finance departments to store student data and see their grades directly through the system. The results of the average percentage of all the questions that have been distributed have concluded that the UAT test results from the academic management system have very good criteria. The system that has been built can help teachers at Hangtuah 2 Sidoarjo High School to classify exam results based on the parameters of tuition arrears, number of books borrowed. , absenteeism, average UTS and UAS scores, accuracy results obtained from data from 37 students, test data, namely 70%..
Implementasi ANFIS Untuk Forecasting Penjualan Sembako Pada CV XYZ Fitriansyah, Muhammad Daffa; Anggraeny, Fetty Tri; Wahanani, Henni Endah
CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Vol 11 No 1 (2025): CICES
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cices.v11i1.3492

Abstract

This study compares the performance of three fuzzy membership functions—Gaussmf, Gbellmf, and Trimf—in forecasting basic goods sales. The evaluation was conducted by measuring the Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE) on both training and testing data across various window sizes. The evaluation results indicate that the Trimf membership function achieved the best performance. For a window size of 4, Trimf yielded a testing RMSE of 1.77 and a testing MAPE of 8.23%, outperforming Gaussmf (RMSE 2.82, MAPE 12.57%) and Gbellmf (RMSE 4.64, MAPE 17.54%). Meanwhile, Gaussmf and Gbellmf exhibited weaker performance on testing data, particularly at larger window sizes. These findings suggest that the appropriate selection of fuzzy membership functions can significantly enhance prediction accuracy. Future research could explore combinations of membership functions or other parameters that may further improve forecasting performance.
Implementasi Arsitektur Mikroservis dan Orkestrasi Kubernetes dengan Paradigma DDD pada Website Freelancing Farhana, Hafi Ihza; Mumpuni, Retno; Ali Akbar, Fawwaz
CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Vol 11 No 1 (2025): CICES
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cices.v11i1.3496

Abstract

The rapid development of the digital era triggered by COVID-19 has changed the way people earn income, with more and more people turning to freelance work. M-Knows Consulting responded to this change by creating a website-based freelance platform, designed to be a place for Indonesian freelancers to develop their careers. Given the complexity of the system and the high interaction of various users, a more modular development is needed to increase efficiency, especially in handling diverse project challenges. Therefore, a microservice architecture was chosen as a more appropriate solution than a monolithic architecture. The design of this microservice architecture involves several important steps, including the application of the Domain-Driven Design (DDD) paradigm with the principle of bounded context to clearly separate business domains and implement a multi-database approach that suits the specific needs of each service. The deployment process will be carried out using Kubernetes to manage the workload of each microservice and ensure system scalability and reliability. With this approach, it is hoped that the development of a website-based freelance platform can run more efficiently and quickly, so that it can immediately provide optimal services for freelancers in Indonesia.
Penerapan Prediksi Penjualan pada Optimasi Stok dan Manajemen Persediaan Menggunakan Holt-Winters Maharani, Ardiana Deka; Sari, Anggraini Puspita; Putra, Chrystia Aji
CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Vol 11 No 1 (2025): CICES
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cices.v11i1.3499

Abstract

Penjualan memegang peranan penting sebagai penggerak utama perekonomian dan menjadi salah satu indikator keberhasilan suatu bisnis karena mencerminkan kemampuan perusahaan dalam memenuhi kebutuhan dan keinginan konsumen. Seiring dengan perkembangan teknologi dan perubahan tren bisnis, strategi penjualan pun mengalami evolusi menyesuaikan dengan kebutuhan pasar yang semakin kompleks. Dalam menghadapi dinamika pasar yang berubah, perusahaan perlu mengembangkan strategi penjualan yang efektif dan adaptif. Salah satu cara untuk mengatasi tantangan ini adalah dengan melakukan prediksi penjualan yang akurat. Penelitian ini bertujuan untuk mengembangkan sistem prediksi penjualan menggunakan metode Holt-Winters dalam mengoptimalkan manajemen persediaan. Metode ini diterapkan untuk mengantisipasi permintaan pasar dan mengurangi resiko terkait dengan ketidakpastian penjualan. Metode Holt-Winters mengintegrasikan tiga komponen utama: level (α), tren (β), dan musiman (γ), memungkinkan prediksi yang lebih presisi, baik untuk jangka pendek maupun jangka panjang. Penelitian ini memanfaatkan 768 data yang dibagi menjadi 2 yakni data uji dan data latih. Hasil Penelitian menunjukkan bahwa metode Holt-Winters mampu menghasilkan prediksi penjualan dengan tingkat akurasi yang tinggi, ditunjukkan oleh nilai Root Mean Square Error (RMSE) yang terendah sebesar 0.45. Nilai RMSE yang lebih rendah mengindikasikan performa model yang lebih baik dalam memprediksi penjualan. Dengan demikian, penerapan metode Holt-Winters dalam memprediksi penjualan terbukti efektif dalam mengoptimalkan manajemen persediaan.
Implementasi Logika Fuzzy Untuk Pemeriksaan Gizi Berdasarkan IMT Pada Aplikasi Fitpriority Mardhavi, Arif; Sihananto, Andreas Nugroho; Nurlaili, Afina Lina
CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Vol 11 No 1 (2025): CICES
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cices.v11i1.3502

Abstract

Public awareness of the importance of leading a healthy lifestyle and exercising hassignificantly increased in recent years. However, various issues such as a lack of understandingof proper exercise techniques and nutrition that do not align with fitness goals remain prevalent.To address these challenges, this study designs a web-based application called Fitpriority toconnect users with professional trainers. One of the main features of this application is anutritional status check based on Body Mass Index (BMI). This algorithm was chosen for itsability to tolerate small changes in nutritional values, unlike the rigid traditional logic methods.The study employs the Mamdani method to determine nutritional status through the processes offuzzification, implication function application, rule aggregation, and defuzzification using thecentroid method. Additionally, the System Usability Scale (SUS) method is used to assess theusability and user experience of the developed application. The results of this study are expectedto provide an effective solution for individuals aiming to achieve their fitness goals moreefficiently and comfortably, and to serve as a valuable tool for a wide range of users inmaintaining optimal physical health and fitness.
Sistem Rekomendasi Makanan Sesuai Budget Bagi Wisatawan Menggunakan Algoritma Genetika Berbasis Website Nurhaliza, Risma; Sihananto, Andreas Nugroho; Maulana, Hendra
CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Vol 11 No 1 (2025): CICES
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cices.v11i1.3504

Abstract

The development of a web-based food recommendation system using Laravel aims to help tourists in Surabaya find places to eat that suit their preferences, overcoming the constraints of limited information and the many choices that are often confusing. This system utilizes a genetic algorithm, which was chosen for its ability to optimize recommendations based on various criteria such as budget and location. Restaurant data in Genteng and Bubutan Districts is collected and analyzed for use in the recommendation process. Functional testing shows that this system functions well, with a genetic algorithm that is able to produce optimal recommendations based on adequate fitness values ​​and fast execution times. To improve this system, it is recommended to improve the user interface design, optimize algorithm parameters, and perform additional testing to ensure system performance and security.
Recognition of Handwritten Hangeul Characters Using Convolutional Neural Network Kezia, Kezia; Sari, Anggraini Puspita; Maulana, Hendra
CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Vol 11 No 1 (2025): CICES
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cices.v11i1.3505

Abstract

The rapid increase in Indonesian tourists visiting South Korea has highlighted a growing interest in Korean culture, largely fueled by the Korean Wave. However, the inability to read the Korean alphabet (Hangeul) leaves many tourists vulnerable to scams. This paper proposes a novel solution to address this issue by developing a system for recognizing handwritten Hangeul characters, aimed at assisting Indonesian tourists in navigating South Korea safely. The research introduces a hybrid algorithm that integrates Vision Transformers (ViTs) with Convolutional Neural Network (CNN), aiming to overcome the limitations of CNN in capturing global features. The dataset utilized comprises 2,400 images of handwritten Hangeul characters, categorized into consonants and vowels. The study involved pre-processing, training, validation, and testing with three data split ratios (60:20:20, 70:15:15, 80:10:10) and two learning rates (0.001 and 0.0001) over 10 epochs. This hybrid model approach is designed to enhance recognition accuracy and improve the system's adaptability to diverse inputs.

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