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Pengembangan Sistem Pembayaran pada Website Bimbingan Belajar Non-Formal Berbasis PHP MySQL di LOOP Coding BSD, Tangerang, Banten Arika Karpina; Yuma Akbar; Widya Ayu Lestari; Fitriani Noer Jamilah
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 4 (2025): OCTOBER-DECEMBER 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i4.3846

Abstract

This study develops a web-based payment system using PHP and MySQL to overcome the problem of manual recording in course institutions. Many course places still use manual recording that is prone to errors, administrative delays, and difficulties in making financial reports. This system aims to improve efficiency and accuracy by providing a more structured administration solution. Features such as dashboards, monthly and annual payment monitoring, and financial data recaps allow for transparency and more effective data management. The implementation of the system at Loop Coding BSD, Tangerang, has been proven to speed up the recording process, reduce manual errors, and improve financial reports. This system improves operational efficiency, data security, and facilitates evaluation or auditing. Overall, the implementation of this web-based system makes it easier to manage payment data and supports smooth administration and financial management in educational institutions.
Optimasi Keamanan Jaringan dengan Metode Sentralisasi Koneksi VPN Berbasis Zerotier pada Industri Soho Nasrullah Syamil Salahudin; Yuma Akbar
Jurnal Komputer, Informasi dan Teknologi Vol. 5 No. 2 (2025): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v5i2.3037

Abstract

Network security plays a crucial role in supporting productivity and ensuring operational continuity within Small Office/Home Office (SOHO) environments. However, limitations in infrastructure and technical resources often hinder the implementation of reliable and efficient security solutions. This study aims to optimize network security through a centralized VPN connection approach using ZeroTier technology. ZeroTier is a peer-to-peer-based virtual network solution that supports end-to-end encryption using the AES-256-GCM protocol and public key authentication based on Curve25519. It enables secure connections between computers within a virtual local network, even if they are physically located in different places. This research employs an experimental methodology by comparing two scenarios: a SOHO network without VPN and a SOHO network with centralized VPN connectivity using ZeroTier. The evaluation focuses on security parameters (encryption, authentication, and secure routing), network performance (latency and throughput), and ease of implementation. The results show that implementing ZeroTier significantly enhances data communication security without requiring additional physical infrastructure. Furthermore, the centralized connection scheme offers centralized traffic control, simplifies access management, and reduces potential vulnerabilities from uncontrolled peer-to-peer connections. In conclusion, the application of centralized VPN connections using ZeroTier proves effective in optimizing network security for SOHO environments through a lightweight, efficient, and easy-to-implement approach.
Social Media Sentiment Analysis of Instagram Use by Early Childhood Education Information System Development Based on Naïve Bayes Yuma Akbar; Sugiyono Sugiyono; Dedi Gunawan; Salsabila Putri Wibowo
International Journal of Information Engineering and Science Vol. 3 No. 1 (2026): February : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v2i1.341

Abstract

This study employs the Naïve Bayes method to analyze social media sentiment regarding the use of Instagram by early childhood users. The primary objective of this research is to understand public perceptions of the positive and negative impacts of Instagram usage among young children, particularly in relation to their social, psychological, and digital behavioral development. Sentiment analysis is carried out using data from various social media platforms, which are then classified into positive, negative, and neutral opinions. The classification results form the basis for developing an integrated educational information system designed to provide guidance for parents, educators, and children in using Instagram safely, healthily, and responsibly. The system also emphasizes the importance of age-appropriate content education, privacy settings, and strategies to minimize the risks of exposure to inappropriate content and the negative effects of excessive usage. This research is expected to support the creation of a more positive, safe, and beneficial digital environment for early childhood users while also serving as a reference in formulating effective policies in the social media era.
Classification of Sales of Best-Selling Products in Ira Store Using Naive Bayes Algorithm and K-Nearest Neighbor Algorithm Yuma Akbar; Kiki Setiawan; Muhammad Joko Umbaran Kharis Bahrudin; Intan Purwasih
International Journal of Electrical Engineering, Mathematics and Computer Science Vol. 1 No. 4 (2024): December : International Journal of Electrical Engineering, Mathematics and Com
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijeemcs.v1i4.13

Abstract

In today's world of retail and technology, competition is fiercely competitive. With the development of retail businesses increasing in number and mushrooming in a region, consumer needs are increasing, and retail business players are competing to develop their businesses by utilizing existing technology. Daily sales transaction data continues to increase, causing a lot of storage. Toko Ira has more than 228 sales transaction data records from 2023 to 2024 that have not been used. Data requires a lot of storage space. Additionally, the data has not been used in an effective way. Based on this problem, this research aims to use data mining to classify sales transaction data to determine which items are selling best. This research is a case study with a qualitative approach. This research was conducted with the Naive Bayes method and Rapidminer was used. The results of the sales transaction data classification research are the division of products into best-selling and non-selling categories. The results of this research show that the K-Nearest Neighbors (KNN) algorithm with a 50:50 data division is more effective in predicting and classifying sales of best-selling and non-selling products in IRA stores. The results show that the Naive Bayes algorithm has an accuracy of 89.91%, while the K-Nearest Neighbors (KNN) algorithm has an accuracy of 60.09%.
Public Sentiment Analysis on the Issue of Stopping Tax Payments on Twitter Using the Naive Bayes Method and Support Vector Machine Mesra Betty Yel; Yuma Akbar; Sugiyono Sugiyono; Nova Mahendra
Journal of Engineering, Electrical and Informatics Vol. 2 No. 1 (2022): Februari : Journal of Engineering, Electrical and Informatics
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v2i1.203

Abstract

This research was conducted to find out public opinion on the Stop Paying Tax Issue on Twitter social media. In this study the author aims to use the Naïve Bayes Algorithm and Support Vector Machine in analyzing positive and negative sentiment labels and knowing the results of the accuracy of the Naïve Bayes algorithm and Support Vector Machine in posts by Twitter social media users related to Stop Paying Taxes. The data collection process in this study will using public data sets. The public data set is obtained from 2000 tweets. The final result of this comparison with the two test methods uses the naïve byes algorithm and Support Vector and Machine, namely the prediction results of Public Sentiment on Stop Paying Tax Issues based on data obtained from Twitter and implemented with the SVM (Support Vector Machine) method showing an accuracy value of 84.77 % Of the test data, it is predicted that 1,192 data are Negative Sentiment and 174 data are Positive Sentiment. Of the 1367 test data, 883 data were predicted as Negative Sentiment and 483 data as Positive Sentiment For the prediction results from Negative Sentiment, there were 1367 data predicted Negative and 1 data predicted Positive.
Design of an IoT-Based Server Room Temperature Security Monitoring System Using a Microcontroller and Fuzzy Logic Method Yuma Akbar; Tri Wahyudi; Sugiyono Sugiyono; Ghofurur Nawangsah
Journal of Engineering, Electrical and Informatics Vol. 2 No. 2 (2022): Juni: Journal of Engineering, Electrical and Informatics:
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v2i2.204

Abstract

PT. Sridatta Prastama Telecommunications (PRASTATEL) as a company in the field of telecommunications service providers must provide non-stop cell phone / VoIP servi-ces. Devices that work 24 hours non-stop by minimizing the damage that occurs, must be supported by monitoring to ensure the system is running properly. If there is a sig-nificant increase in temperature, it can affect system performance or cause damage to the hardware side. The cooler in the server room is felt to be not optimal because the cooler is often constrained by frequent power outages or the cooler turns off and avoids suspicious activities / activities that occur in the server room because the server room administrator is not always on site. From the problems described above, a solution is needed to monitor the system remotely. So that the system is able to know changes in room temperature (Monitoring) in real time and monitor whether there is activity oc-curring in the server room. By using Internet of Things (IoT) technology, the NO-DEMCU ESP-8266 device and the fuzzy logic method which basically maps an input space into an output space that is applied to the server room temperature sensor. This monitoring system uses the Telegram application to receive notifications in the form of text or images. So that it can monitor temperature changes and activities that occur in the server room in real time and accurately. Therefore the server room administrator does not have to be on the site.
Classification of Favorite Book Borrowing Data at the STIKOM CKI Library Using the Decision Tree Algorithm Yuma Akbar; Untung Surapati; Sutisna Sutisna; Yansen Yansen
Journal of Engineering, Electrical and Informatics Vol. 2 No. 1 (2022): Februari : Journal of Engineering, Electrical and Informatics
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v2i1.3663

Abstract

The library on the STIKOM CKI campus as a means of providing information and has a complete collection of learning media books, but the data processing system for borrowing and returning favorite books in the library is currently still manual, that is, all data collection processes are written on book cards, although it is quite good but the process is rather slow and requires quite a long time because in the process of searching the data must be checked per page one by one so that the data processing is less effective and efficient. To overcome this, it is necessary to develop an application using the decision tree algorithm method which can make it easier to collect borrowing data and return favorite books that are more effective and efficient and display integrated output of student reports that have not returned so that data processing is more accurate and can speed up officer performance. library. Submitting a favorite book lending classification application can make it easier to access loans and returns anywhere and anytime. So that data processing is more accurate and can speed up librarian performance.
Implementation of Mikrotik Network Management Using Quality of Service Features with the Hierarchical Token Bucket Algorithm Yuma Akbar; Rizki Ananda Pratama; Sugiyono Sugiyono; Faris Jawad
International Journal of Mechanical, Electrical and Civil Engineering Vol. 1 No. 4 (2024): October : International Journal of Mechanical, Electrical and Civil Engineering
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/ijmecie.v1i4.271

Abstract

This research aims to address the issue of uneven bandwidth distribution in large organizational networks by implementing Quality of Service (QoS) using FIFO and the Hierarchical Token Bucket (HTB) algorithm on Mikrotik routers. Uneven bandwidth distribution can disrupt productivity and operational efficiency. This study creates a fair and efficient traffic management system, allowing bandwidth allocation according to user needs. The methodology involves detailed configuration of Mikrotik RouterOS to optimize QoS with adjusted HTB settings. Testing was conducted using IPerf3 to measure bandwidth variations received by clients in different conditions, including scenarios with two and three active clients. The results indicate that the HTB method provides more stable and consistent bandwidth distribution compared to FIFO. In the two-active client scenario, the unused bandwidth by the third client is allocated to higher priority clients, demonstrating HTB's effectiveness in managing traffic priorities. This research is expected to enhance user satisfaction by providing a network that is both stable and responsive to the needs of various operational applications, and contribute significantly to the development of best practices for bandwidth management in complex organizational environments.
Data Driven Evaluation of the New Learning Paradigm Using Machine Learning for Optimizing Graduate Outcomes Mesra Betty Yel; Relita Buaton; Yuma Akbar; Novriyenni Novriyenni
Journal of Applied Data Sciences Vol 7, No 3: September 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i3.1152

Abstract

In preparing students to face digital literacy and critical thinking transformations rapid, universities are therefore required to design and implement learning processes that are innovative, adaptive, and differentiated, in accordance with the new learning paradigm. However, the unemployment rate in Indonesia remains high approximately 5.98% vocational high school graduates and 4.8% diploma and university graduates. To develop highly skilled human resources, higher education must strengthen the competencies of students as future agents of change entering the workforce. The persistent unemployment rate among diploma and university graduates presents a national challenge that may hinder the progress of human capital development. Therefore, this study aims to develop a classification and association model linking new learning paradigm programs to student learning outcomes, in order to generate new knowledge and identify correlations among grade point average, employment waiting period, occupational field, and graduate income. The research employs a machine learning approach using association rule mining and the K-Nearest Neighbors algorithm to analyze correlations and predict graduate outcomes. Based on data processing of 450 graduate data who participated in the new paradigm learning program, the findings indicate that graduates under the new learning paradigm with grade point average ≥ 3.50 are significantly more likely to secure employment within ≤ 2 months, support = 20%, confidence = 100% based on processing a data set of 450 data. Participants in the teaching assistance program tend to experience longer waiting periods ≥ 6 months and lower initial earnings compared to those from other new learning paradigm pathways. Conversely, graduates involved in certified internships or independent study programs demonstrate higher earnings potential and stronger academic performance. The results confirm that the new learning paradigm exerts a positive influence on graduate employability, income level, and academic achievement, especially through experiential and industry-oriented learning mechanisms.
Traffic Condition Classification Using IoT on Raden Inten II Road Untung Surapati; Yuma Akbar; Dwi Swasono Rachmad; Hadi Gunawan
International Journal of Applied Mathematics and Computing Vol. 2 No. 4 (2025): October : International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v2i4.121

Abstract

Unmonitored traffic conditions often hinder decision-making processes in traffic management, particularly on secondary roads. Jalan Raden Inten II in East Jakarta is one of the connecting routes with heavy traffic activity at certain times, yet no integrated data-based monitoring system is currently available. This study proposes an Internet of Things (IoT)-based traffic condition classification system to identify Clear, Normal, or Congested states based on vehicle counts and speed categorization. The system is designed using an ESP32 microcontroller, an HB100 sensor to detect vehicle speed, and two AJ-SR04M ultrasonic sensors to detect vehicle presence. Data on vehicle counts and the percentage of slow-moving vehicles are periodically transmitted to the ThingSpeak platform and processed using the Threshold-Based Classification method. The classification results are visualized on a dashboard-based website equipped with charts, traffic condition status, and notifications when consecutive congestion is detected. Testing was conducted using simulation data over a specific period. Qualitative validation was carried out by comparing the classification results with traffic indicators from Google Maps. The results show that the system can classify traffic conditions with a good degree of agreement with external references, although discrepancies occurred at certain times due to the limitations of simulated data. This research demonstrates that a simple IoT approach can provide an affordable and effective solution for monitoring and classifying traffic conditions, with potential for real-world implementation in future studies.
Co-Authors ., Novriyenni AA Sudharmawan, AA Abdul Shomad Abdulloh Abdurrahman Asyam Albahy Abror, Ikhsan Adhipramana, Fernanda Aditya Bagas Pramudhi Aditya Zakaria Hidayat Aditya Zakaria Hidayat Adzani, Adinda Mutiara Agung Pratama Agung Wianata Sugeng Kusuma Agung Wiranata Sugeng Kusuma Ahluna, Faza Ahmad Suprianto Ahmad Zulfikar Aidil Rizki Hidayat Aimar, Muqorrobin Akhsani, Ziyat Akmaludin Akmaludin Al Ammaar, Mohammad Farroos Albahy, Abdurrahman Asyam Aldi Sitohang Aldino Nur Ihsan Amrullah, Aziz Septian Angga Tristhanaya Anita Rosiana Anwar, Imam Dzikrilloh Apriyanus Laia Arfadhillah, Zahra Ari Ramadhan Arib Nawwar Tahir Arief, Yoga Sofyan Arif, Sulthan Cendikia Arika Karpina Arinal, Veri Aula, Raisah Fajri Aulia, Mutia Dwi Awang Hariman, Aloisius Az-zahra, Haura Salsabila Azis, Iim Muhaemin Abdul Aziz Septian Amrullah Azzahra, Yasmin Aulia Bachtiar, Yuliana Bebriani, Serli Benny Sulaiman K Betty Yel, Mesra Bintoro, Bayu Bryan Pratama Buaton, Relita Cahyono, Bayu Adi Candra Milad Ridha Eislam Dadang Iskandar Mulyana` Damayanti, Yulia Dava Septya Arroufu Dedi Dwi Saputra Dedi Gunawan Dewa Gde Adi Murthi Udayana Doddy Mulyadi Saputra Dwi Swasono Rachmad Edhy Poerwandono Edhy Poerwandono Edhy Poerwandono Eka Satria Maheswara Fadhil Khanifan Achmad Fadillah, Fauzan Fahmi Chairulloh Faisal Akbar Faisal Akbar Nasution Farhani, Aulia Faris Jawad Farisi, Muhamad Fatkul Toriq Febrianti, Syafira Feni Putriani Fentri Boy Pasaribu Fernanda Adhipramana Fitriani Noer Jamilah Franido, Richard Frencis Matheos Sarimolle Gabriel Alezhandro Pakpahan Ghofurur Nawangsah Gipari Pradina Abdillah Gusniar Alfian Noor Hadi Gunawan Hafiz, Tegar Muhamad Hartinah, Suci Sugih Hazrul Aswad Hengky, Mario Hidayat, Aditya Zakaria Ibnazia Darnov Ikhsan Abror Ikhwanul Kurnia Rahman Intan Purwasih Jodi Juliansah Joey Abdiner Parlindungan Hutabarat Juliansah, Jodi Julianto, Muhammad Rizky Julvan Marzuki Putra Sibarani K, Benny Sulaiman Kiki Setiawan Kiki Setiawan Kusuma, Agung Wiranata Sugeng Lestari, Dinny Amalia M Ilham Setya Aji M Jundi Hakim Mafazi, Luthfillah Marjuki Masaranto Laia Maulana Putra Hertaryawan, Ryfan Mayangsari, Descania Meilisa Miftahul Huda Mizsuari Muamar Rizky Mohammad Farroos Al Ammaar Muhamad Farisi Muhamad Fawaz Kamali Muhamad Fikri Nugraha Muhamad Umar Hasan Asrori Muhamad Zaeni Nadip Muhammad Arham Muhammad Arya Ramadhan Muhammad Derry Oktaviandi Muhammad Derry Oktaviandi Muhammad Fadlan Muhammad Faizal Lazuardi Muhammad Joko Umbaran Kharis Bahrudin Mulya, Citra Pricylia Ananda Nadya Khairunnisa Nasrullah Syamil Salahudin Nirat Nirat Nirat, Nirat Noor, Gusniar Alfian Nova Mahendra Novianto, Firza NST, Silvan Nufus, Reda Hayati Nugraha, Muhamad Fikri Nur Arif Khairudin Nur Oktavian Nurfaishal, Muhammad Dzaky Nurmaylina, Vivi Oka Prasetiyo Oktavian, Nur Oky Tria Saputra Oky Tria Saputra7 Permatasari, Veren Nita Piqih Akmal Poerwandono, Edhy Praja Raymond , Samuel Pramudhi, Aditya Bagas Pramudita, Diky Prasetiyo, Oka Putri S, Dhiyah Labibah Nauli Putri Wibowo, Salsabila Qibthiyah, Mariyatul Qolbi, Rofika Ramadhan, Muhammad Arya Rasiban Rasiban Regita, Anggit Nur Hannaa Rekardius Tafonao Rezha Mulia Revandy Richard Franido Richard Franido Rizki Ananda Pratama Rizki Maulana, Rizki Rizky Adawiyah Ropindo Pelix Pane Rosiana, Grace Lolita Ryan Rivaldo S, Fahmi Chairulloh Widia Safhani, Rizca Sahrul Hidayat Sahrul Hidayat Salsabila Putri Wibowo Salsabila Salsabila Saputra, Mochammed Erryandra Sarimole, Frencis Matheos Septiansyah, Ade Setiawan, Kiki Shafwan Abiyu Wirawan Sibarani, Julvan Marzuki Putra Sinaga, Putri Cahyani SOPAN ADRIANTO SRI LESTARI Sri Lestari Sugiharto, Tri Sugiyono Sugiyono Sugiyono Sugiyono Sugiyono Sumpena Sumpena Sumpena, Sumpena Surapati, Untung Sutisna Sutisna Sutisna Sutisna Sutisna Sutisna Sutisna Suwandi Suwandi Tegar Muhamad Hafiz Tegar Muhamad Hafiz Tegar Rizky Ardana Toriq, Fatkul Tri Wahyudi Tri Wahyudi Tristhanaya, Angga Tundo, Tundo Untung Surapati Untung Surapati Untung Surapati Untung Surapati Untung Wahyudi Untung Wahyudi Vivi Nurmaylina Wahyu Saputro Wewisman Tafonao Widya Ayu Lestari Wijaya, Rohmat Willy Wijayanto WINDU GATA Yansen Yansen Yusril Nurhadi AS