CCIT (Creative Communication and Innovative Technology) Journal
CCIT (Creative Communication and Innovative Technology) Journal is a scientific journal published by University of Raharja. CCIT is published twice a year, February and August each. CCIT (Creative Communication and Innovative Technology) Journal receives unprecedented scientific articles from academics, researchers and practitioners. The writing we receive will be processed to choose a good writing. To improve the quality and quantity of publications, University of Raharja became a member of Cooperation Computer Research Inter University (CORIS) to jointly exchange papers for publication. CORIS is an association of several private universities that agree or commit to cooperate in publishing journals, seminars and also research activities. CORIS was established at the end of 2013 by Mr. Dr. Ir. Djoko Soetarno. The journals incorporated in CORIS are: IndoCEISS (Indonesian Computer, Electronics and Instrumentation Support Society) is a forum for scientists, practitioners and educators and enthusiasts in the field of computers, electronics, instrumentation who are interested in advancing the field in Indonesia. CORIS has been doing agreements and working with IndoCEISS since 2013 to improve the quality and quantity of journal publications in cooperation with CORIS. CCIT (Creative Communication and Innovative Technology) Journal is published in ISSN online media: 2655-4275, starting from Vol. 12, No. 1, February 2019. CCIT Journal indexed at: CERTIFICATE OF APPRECIATION : CCIT (Creative Communication and Innovative Technology) Journal Accredited Rank Three Jurnal CCIT (Creative Communication and Innovative Technology) Journal This work is licensed under a Lisensi Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
Conceptual Design of an Integrated Smart Home System with PV Solar Power for Traditional Minahasa Wooden House
The traditional Minahasa wooden house is an integral part of Indonesia's cultural heritage. However, in this modern era, the challenge of preserving cultural authenticity while introducing it to the technological era is becoming increasingly urgent. This research aims to design a Smart Home System concept integrated with Photovoltaic (PV) Solar Power Plant for traditional Minahasa wooden houses. The objective of this study is to identify the potential for integrating smart home technology and PV Solar Power Plant in Minahasa wooden houses and to develop a concept that combines traditional elements with modern technology. The research methodology will involve a literature review to understand the concepts of smart homes, PV Solar Power Plant, and the characteristics of traditional Minahasa wooden houses. Additionally, descriptive research through interviews will be conducted in collaboration with industry partners to obtain data and examples of traditional Minahasa wooden houses to be used as benchmarks in the concept design. This research can contribute to integrating modern technology into Indonesia's cultural traditions while enhancing the competitiveness of Minahasa wooden house products in the market. The result of this research is a conceptual design for the implementation of a Smart Home System integrated with a PV rooftop solar power plant system in Minahasa wooden houses. The utilization of solar energy as electrical energy is predicted to achieve an annual energy yield of 16,775 kWh.
Copyright (c) 2025 CCIT (Creative Communication and Innovative Technology) Journal
TEKNIK MEMBONGKAR PERTAHANAN VIRUS LOKAL MENGGUNAKAN VISUAL BASIC SCRIPT DAN TEXT EDITOR UNTUK PENCEGAHAN
Pesatnya perkembangan virus lokal belakangan ini yang terkadang menginfeksi komputer, menuntut harus mulai berfikir mengambil bagian tentang bagaimana cara pembuatan pencegahnya. Hal ini diperlukan, karena virus lokal terkadang sulit dideteksi oleh beberapa antivirus terkemuka, kecuali oleh beberapa antivirus buatan lokal yang kemudian dipublikasikan sebagai antivirus yang mampu menangani satu atau beberapa jenis virus lokal. Hal ini bisa terjadi mungkin saja disebabkan karena virus lokal bekerja tidak sebagaimana virus non lokal pada umumnya, sehingga keluar dari standar pencarian virus, contohnya saja jarang sekali virus lokal yang menginfeksi file exe atau file com atau yang lainnya, sehingga sangat sulit dideteksi sebagai virus atau bukan, kecuali ketika virus tersebut telah dilaporkan dan terdeteksi oleh pembuat antivirus, baru virus tersebut dapat diatasi, lagi-lagi tercipta asumsi bahwa virus selangkah lebih maju dari antivirus. Salah satu penyebab dari sulitnya mendeteksi virus lokal ini, karena hampir tidak ada bedanya dengan file biasa, apalagi virus ini juga menggunakan bahasa lokal. Satu sisi mungkin bisa berbangga, karena beberapa nama virus lokal merupakan bahasa Indonesia, dan telah menjadi nama yang berada di database daftar virus internasional. Kini saatnya mencoba membongkar pertahanan virus lokal secara manual, yang mungkin suatu saat teknik ini akan mampu menciptakan antivirus secara sederhana. Teknik membongkar pertahanan virus lokal menggunakan bahsa visual basic script dan teks edior mengacu pada target pengamanan beberapa bagian vital yang diinfeksi oleh virus, seperti registry, msconfig, sysedit, cmd, folder windows, system32 dan masih banyak lagi. Hal ini dimaksudkan bahwa dengan memahami teknik membongkar pertahahanan virus tentunya diharapkan mampu mencegah virus menginfeksi komputer lebih dini, hal ini sejalan dengan asumsi bahwa mencegah lebih baik dari mengobati.
PERIODIC HISTORICAL SYSTEM SEBAGAI EVALUASI STRATEGIS DALAM MENDUKUNG PENGAMBILAN KEPUTUSAN MANAJEMEN
Pada era globalisasi seperti sekarang ini, perkembangan sistem informasi memiliki laju pertumbuhan yang sangat pesat, terutama sebagai media untuk memberikan informasi yang cepat dan akurat. Banyak perusahaan maupun organisasi menggunakan sistem informasi sebagai bahan evaluasi kinerja. Sebuah sistem informasi harus memiliki kemampuan yang baik, yaitu mampu memberikan informasi secara cepat dan akurat. Seiring berjalannya waktu maka informasi yang didapat akan semakin meningkat, tetapi informasi tersebut belum dapat terekam dan tersimpan dengan baik kedalam sebuah history sistem, dimana dapat merekam dan menyimpan seluruh informasi yang lama ataupun yang baru serta mampu memberikan informasi dari waktu ke waktu, walaupun informasi tersebut telah lampau, manajemen dapat menggunakan sistem tersebut guna membantu proses evaluasi strategis manajemen. Untuk mengatasi permasalahan ini, dibutuhkan suatu metodologi yang disebut Periodic Historical System (PHS). PHS didefinisikan sebagai teknik pengumpulan, pengintegrasian dan penyimpanan data yang bertujuan untuk memberikan informasi manajemen yang akurat dari waktu ke waktu serta bermanfaat untuk evaluasi manajemen dalam pengambilan keputusan. Diidentifikasikan 5 (lima) masalah yang timbul pada sistem informasi, mendefinisikan metode baru yang disebut PHS, menentukan 4 (empat) ciri khas dari PHS, merancang algoritma PHS, serta menguraikan 5 (lima) manfaat dari penerapan PHS. Aplikasi juga diurai dengan rincian database yang diperlukan serta flowchart diagram. Dengan metodologi PHS ini dapat menjadi sebuah evaluasi terkini dalam mendukung kepentingan manajemen dalam pengambilan keputusan yang akurat.
E LEADERSHIP : KONSEP DAN PENGARUHNYA TERHADAP EFEKTIVITAS KEPEMIMPINAN
Berbagai vendor software dan hardware telah mengeluarkan beberapa produk yang mendukung penerapan teknologi informasi untuk kepentingan para manajer organisasi. Namun pemanfaatan produk tersebut oleh para manajer belum optimal. Hal ini disebabkan para manajer belum memahami konsep penerapan dan cara kerja teknologi informasi untuk mendukung pelaksanaan fungsi-fungsi kepemimpinan yang disebut e-leadership. Sementara itu pemanfaatan teknologi informasi diberbagai organisasi dan perusahaan, dan penerapan konsep dan cara kerja e-leadership oleh para manajernya merupakan suatu keharusan. Organisasi yang dipimpin oleh manajer yang tidak berminat dan tidak menguasai penerapkan konsep dan cara kerja e-leadership senantiasa akan sulit bertahan diera persaingan yang semakin kompetitif. Untuk itu diperlukan penjabaran tentang konsep dan penerapan cara kerja e-leadership dan pengaruhnya terhadap efektivitas pelaksanaan fungsi manajer sebagai pemimpin, diantaranya dalam melakukan fungsi: perencanaan, pengelolaan, pendelegasian, motivasi, pengontrolan, dan evaluasi.
REKAYASA TEKNIK PEMROGRAMAN PENCEGAHAN DAN PERLINDUNGAN DARI VIRUS LOKAL MENGGUNAKAN API VISUAL BASIC
Belakangan ini perkembangan virus yang begitu cepat membuat pengguna komputer merasa kesal, apabila komputernya berjalan sangat lambat tidak seperti biasanya, hal ini mungkin telah terinfeksi virus. Dari sekian banyaknya virus, beberapa diantaranya merupakan virus lokal yang beberapa bulan terakhir sedang gencar-gencarnya menyerang. Virus lokal yang dibuat dengan bahasa pemrograman visual basic, mempunyai beragam nama dan varian, juga memiliki keragaman teknik penyerangan dan pertahanan, biasanya aktivitas penyerangan sulit untuk diketahui. Namun demikian, jika kita mencoba memahami teknik penyerangan, penyebaran dan pertahanannya, virus lokal yang dibuat dengan bahasa pemrograman visual basic, hampir memiliki kemiripan teknik penyerangan, penyebaran dan pertahanan, sehingga mudah bagi yang mengerti untuk mengetahui penyerangan dan pertahanan virus lokal. Rekayasa virus lokal dengan visual basic meliputi teknik menginfeksi flashdisk dari sebuah komputer, menginfeksi komputer target dimana flashdisk terpasang, menggandakan diri ke folder tertentu (umumnya beberapa folder inti seperti windows, system32 dan lain sebagainya). Kemudian virus lokal ini akan menginfeksi registry, pemblokiran registry, cmd, msconfig, sysedit, pengatur folder option dan masih banyak lagi yang akan dibahas satu persatu dalam memahami teknik penyerangan dan pertahanan virus lokal serta pembuatannya melalui bahasa pemrograman visual basic. Dilihat dari teknik infeksi sistem, penggandaan ke sistem dan infeksi registry, virus lokal yang dibuat dengan bahasa pemrograman visual basic mudah untuk diciptakan bagi yang sedikit mengerti dan mudah untuk dimusnahkan bagi yang sedikit mengerti, hal ini sangat tergantung dari tingkat pemahaman. Atas dasar itulah penelitian ini dilakukan untuk memberikan gambaran tentang teknik pembuatan virus lokal dalam hal penyerangan dan pertahanannya.
PENGONTROLAN DAN OTOMATISASI WORKFLOW MENGGUNAKAN COMPANY WIDE WEB CWW
Selama beberapa waktu dunia bisnis telah berhasil mengatasi persoalan aliran data yang besar dengan mengalihkan pemrosesan rutin dan transaksi bisnis mereka pada sistem informasi berbasis komputer. Namun, adanya perbedaan sistem informasi pada masing-masing bagian seringkali mensyaratkan penterjemahan dari satu sistem ke sistem lain secara manual, yang dapat mengurangi kecepatan dan keandalan proses pertukaran informasi antar bagian dalam perusahaan, serta sulitnya pengontrolan pekerjaan di seluruh bagian perusahaan. Company Wide Web (CWW) muncul sebagai usaha untuk mengatasi masalah ini. CWW didefinisikan sebagai sistem web yang digunakan untuk mengontrol, mengintegrasikan, dan mengotomasikan proses bisnis yang meliputi perpindahan dokumen melalui suatu prosedur kerja secara elektronis ke seluruh bagian perusahaan secara mudah, akurat, efisien, dan konsisten. Dalam artikel ini akan dikemukakan beberapa langkah pemecahan masalah, antara lain: mengidentifikasikan 3 (tiga) masalah yang sering dihadapi perusahaan dalam hal pengontrolan aliran kerja, mendefinisikan konsep baru dan 6 (enam) ciri khas dari CWW, serta menguraikan 7 (tujuh) manfaat dari penerapan CWW, yang pada akhirnya akan dibuktikan melalui implementasi dengan mengambil studi kasus pada Perguruan Tinggi Raharja. Dengan adanya CWW, diharapkan dapat meningkatkan kualitas kecepata proses dan pertukaran informasi, meningkatkan self monitoring, constant reminding dan early warning bagi karyawan guna meningkatkan kinerja perusahaan, juga lebih efisien dalam melakukan manajemen informasi.
Optimization of Student Grade Data Management Using RESTful API and Microservices Architecture : Case Study at Universitas Mitra Indonesia
The management of student grade data is a critical component of academic information systems that require high efficiency and reliability. At Universitas Mitra Indonesia, the old monolithic system faced challenges in scalability, security, and accessibility. This study proposes the implementation of RESTful API and microservices architecture to optimize the management of student grade data. RESTful API serves as the primary interface for inter-service communication, while microservices allow for independent management of modules such as user authentication, grade data processing, and academic service provision. Implementation results demonstrate a 35% increase in data access speed, a 25% reduction in server load, and enhanced security through token-based authentication. This study significantly contributes to modernizing academic information systems, especially in improving the performance and scalability of digital academic services.
Application of Data Mining on Player Statistics for Scouting in Football
The sophistication of today's technology makes the use of data increasingly massive. All digital aspects must have data that is ready to be processed, including in the football industry. The use of data in the football industry is one of them used to record all activities carried out by players to see their performance in the match. Dewa United has a scouting division that is tasked with finding talented players according to the wishes of the head coach. In its search, the scouting division observes the players on the field and also uses raw statistical data to see the player's performance. However, the implementation of these activities still has obstacles as evidenced by the difference between the results of observations and the performance of players when joining the team. To solve this problem, the use of data mining can provide scouting recommendations according to player statistics, making the scouting process effective and efficient. The purpose of this study is to make it easier for the team to search for players according to what is desired, which is obtained is a web-based application that has a scouting recommendation feature based on attributes or players according to choice and detailed descriptions of the selected players..
WebBased Library Service Information System Design Using Electronic Customer Relationship Management ECRM At SMK YUPPENTEK 1 Tangerang
The utilization of information and communication technology in education is a means of informing quality education. One area that feels the impact of technology in the library. SMK Yuppentek 1 Tangerang currently has a library, but it is not computerized with an information system. In other words, all data is still written in a ledger to recapitulate the transactions that occur so that the data is less accurate in the reporting process. The collection of books that is continually increasing in the library is not followed by the readiness of the officers to update the data so that it becomes difficult for visitors to get the latest information. This study aims to create a website-based library information system at SMK Yuppentek 1 Tangerang city by using Electronic Customer Relationship Management (E-CRM) as a service improvement strategy that is oriented to the needs of members so that it becomes a solution for processing library information data to be practical, accurate and effective. Easy and excellent service can be obtained by visitors well. The methodology of this research analysis is the method of data collection and analysis of Performance, Information, Economic, Control, Efficiency, Service (PIECES), which will present a discussion of the theoretical basis, stages of analyzing and modeling processing systems using Unified Modeling Language (UML), black-box testing that will be used as a testing method.
Electronic Customer Relationship Management (E-CRM),
Implementation of the KNearest Neighbor Algorithm for Classifying Immigration Residence Permit Applicants at the Class I Special Immigration Office TPI SoekarnoHatta
This study aims to apply the K-Nearest Neighbor (KNN) algorithm in classifying immigration residence permit applicants at the Class I Special Immigration Office TPI Soekarno-Hatta, focusing on the algorithm's effectiveness and accuracy in categorizing residence permit applicants based on the types of residence permits: Visit Stay Permit (ITK), Limited Stay Permit (ITAS), and Permanent Stay Permit (ITAP). This study employs a quantitative, experiment-based approach utilizing a dataset of 17,212 residence permit applicant records consisting of 11 key attributes, such as nationality, visa type, residence permit type, gender, and age group.The research process began with data preprocessing stages, including data cleaning, normalization, and dataset splitting into training and testing sets with 80:20 and 70:30 partitioning scenarios. The KNN algorithm was implemented using a parameter of k=5k = 5k=5, chosen based on experimentation to achieve optimal performance. The model's performance evaluation was conducted using accuracy, precision, and recall metrics derived from a confusion matrix. The findings reveal that the KNN algorithm successfully classifies data with the highest accuracy of 96.95% in the 80:20 dataset partition scenario and 96.84% in the 70:30 scenario. The Visit Stay Permit (ITK) class demonstrated the best performance with a precision of 97.46% and a recall of 99.97%, whereas the Permanent Stay Permit (ITAP) class showed the lowest performance with a recall of 59.79%, indicating challenges in recognizing patterns for this class. This study also identifies the advantages of the KNN algorithm, including its simplicity of implementation, flexibility in handling multiclass data, and effectiveness for low-dimensional datasets. However, the algorithm has limitations, such as sensitivity to imbalanced data distributions and high computational time for large datasets.
Neural Network Approach Using PyTorch to Predict the Growth of Various Types of Plants
In the era of rapid technological advancement, agriculture faces increasing challenges in optimizing production efficiency and managing resources sustainably. In Indonesia, various plant types are essential agricultural commodities, yet their productivity is often disrupted by erratic weather, poor land management, pest infestations, and land-use change. This study proposes a predictive model for plant growth using a neural network implemented in the PyTorch framework, integrating multiple environmental features such as temperature, humidity, soil moisture, nutrients, pH, and NPK levels. Unlike previous works that typically focus on specific crops or limited variables, this research introduces a multivariate approach combining diverse agro-environmental data to classify plant types accurately. The model architecture was tuned using GridSearchCV, resulting in optimal hyperparameters (e.g., batch size 32, learning rate 0.001, activation: tanh), achieving high performance with Area Under the Curve (AUC) values nearing 1.0 across most classes. Visualization of network weights reveals how input features are transformed through hidden layers, providing interpretability and transparency in decision-making. The proposed system demonstrates strong generalization capability, as validated on unseen data, and offers real-time prediction feasibility for deployment on edge devices such as NVIDIA Jetson Nano. This work contributes a novel, data-driven approach to smart agriculture by enabling precise growth prediction across multiple plant types, enhancing strategic planning for resource allocation and crop management. Future work includes model adaptation for time-series forecasting and validation with live sensor inputs in real-world agricultural environments.
Business Process Analysis in the Financial System of PT Oti Eya Abadi With Business Process Modelling and Notation BPMN Method
Every company certainly needs an information system for ease of work management in a company organization. As in the problems faced by the company PT. Oti Eya Abadi who needs an information system that can create and print company cash as efficiently as possible so that leaders and employees who manage the company's financial cash do not make manual formats in excel anymore and obtain cash data formats automatically from the information system. In order to achieve a sequential but still efficient system flow in the use of information systems, an analysis is made related to the business process flow of the information system with a description in the form of Business Process Modelling and Notation (BPMN). By describing BPMN, the creation of an information system can be made more directed in each access feature so that when the information system is completed it can be used with access that is easier for users to understand and more efficient in using an information system, including the financial information system of PT. Oti Eya Abadi.
Implementation of Lean UX to Improve the Quality of User Experience Case Study: PT XYZ
The importance of websites in the modern digital world encourages various companies to develop effective user interfaces (UI) and user experiences (UX). This study aims to design the UI/UX design of PT. XYZ's website using the Lean UX method, which focuses on active collaboration with users in developing a Minimum Viable Product (MVP). The Lean UX method involves four main stages: Declare Assumptions, Create MVP, Run Experiments, and Feedback and Research. Testing was carried out using the System Usability Scale (SUS) to measure the level of usability. The results of the study showed that the new UI/UX design significantly improved efficiency and user satisfaction, with a SUS value of 80, which is included in the "Excellent" category. This study makes a significant contribution to website development in the digital sector, especially in designing user-friendly interfaces that are centered on user needs.
Comparison of Naive Bayes Decision Trees and SVM Algorithms for Sentiment Classification of JMO Applications
In this study, the researchers found that SVM achieved a precision of 0.75 for negative sentiment and 0.93 for positive sentiment, with recalls of 0.86 and 0.94, and f1-scores of 0.80 and 0.94, and an overall accuracy of 0.88. Naive Bayes showed similar results with a precision of 0.74 for negative and 0.93 for positive, recalls of 0.87 and 0.94, f1-scores of 0.80 and 0.94, and an accuracy of 0.88. Meanwhile, Decision Tree had the lowest precision for negative (0.71) and positive (0.91) sentiment, with recalls of 0.73 and 0.93, f1-scores of 0.72 and 0.92, and an accuracy of 0.85. These findings suggest that SVM and Naive Bayes offer excellent performance in sentiment classification, while Decision Tree, while still effective, performed slightly lower. These results provide valuable guidance in selecting the right algorithm for sentiment analysis on app data. This study compares the effectiveness of three machine learning algorithms—Naive Bayes, Decision Trees, and Support Vector Machine (SVM)—in sentiment classification of JMO apps using review data taken from Google Play Store via web scraping and processed with a Python application. The evaluation is done based on precision, recall, f1-score, and accuracy metrics.
CNN Algorithm for Herbal Leaf Classification Using MobileNetV2 and ResNet50V2
Indonesia is home to over 30,000 types of herbal plants, with approximately 1,200 species utilized as raw materials for alternative and traditional medicine. Leaves play a crucial role in herbal medicine preparation. However, many people struggle to identify different herbal leaves due to their similar appearances, making classification difficult. Each leaf possesses unique characteristics such as shape, size, midrib, stalk, blade, and type, which can be used for differentiation. To assist in identifying herbal leaves, a classification system based on image recognition is essential. Convolutional Neural Networks (CNN) are deep learning algorithms designed for processing two-dimensional image data. Model performance can be enhanced through transfer learning, with MobileNetV2 and ResNet50V2 being widely used architectures. These pretrained models have been trained to recognize images with high accuracy. This study focuses on classifying herbal plants based on leaf shape using CNN architectures from MobileNetV2 and ResNet50V2. The evaluation results show that the MobileNetV2 architecture, with a 90%:10% data split, achieved an accuracy of 98.51%, precision of 98.92%, recall of 98.51%, and an F1-score of 98.56%. These findings indicate that CNN with transfer learning can effectively classify herbal leaves with high accuracy.