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Classification of Customer Satisfaction with the K-Nearest Neighbor Algorithm in Relation to Employee Performance at PT. Airkon Pratama Ahmad Suprianto; Untung Surapati; Yuma Akbar; Aditya Zakaria Hidayat
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 3 (2024): DECEMBER 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i3.2948

Abstract

PT. Airkon Pratama is the technical consultancy company in the field of maintenance, repair, and operate system. Among its projects are a four-building, multi-story tax office complex. PT. Airkon Pratama experience obstacles to know how its customer satisfaction with their services that is was measured by a questionnaireobtained from work order form. The purpose of this study is to determine how well K-Nearest Neighbor data classification accurately classifies customer satisfaction based on employee performance by PT. Airkon Pratama. The data used in this study is from PT. Airkon Pratama with the data processing using RapidMiner with the K-Nearest Neighbor method which produces an accuracy of 96.53%. Among them four performance indicators were rated as "good", and two as "adequate". Of the 196 that were correctly predicted to be "good," three were "adequate." Most of the 04 respondents gave a positive response indicating their satisfaction with the management of tax office facilities provided by PT. Airkon Pratama in January 2024.
2D Platformer Game Prototype on Indonesian History Using Scratch Yuma Akbar; Mohammad Farroos Al Ammaar
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 3 (2024): DECEMBER 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i3.3070

Abstract

In this study, we would like to share a prototype of a 2D platformer game in Scratch centered on the development of Indonesian history that can increase students' interest and motivation in learning history. In search of a more entertaining and successful alternative to the bad lecture situation, the demand for interactive learning media. Visual programming is chosen with Scratch because it is easier to create educational games in this language. Its creation involves the implementation of visual components such as characters, background environments, UI, etc. Data Evaluation provides a positive level of acceptance to students with an average student evaluation score of 4.1/5 Positive responses were obtained for game elements, story content, and ease of operation First, the results of the evaluation of the Validation of 2D Platformer Games in Indonesian History as a Learning Tool. Through student activeness, a more active way of responding to historical material is being implemented by use. Game development has the ability to become a new educational media if it is well structured and organized.
Implementation of RFM Analysis to Enhance Sales Patterns of Food and Beverages at Bonjour Café and Resto Using the Apriori Algorithm Julvan Marzuki Putra Sibarani; Yuma Akbar; Sutisna; Kiki Setiawan
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 3 (2024): DECEMBER 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i3.3073

Abstract

The rapid growth of the culinary business has made business competition in this field increasingly tight, so a strategy is needed to increase food and beverage sales patterns. Bonjur Cafe Resto serves many food and beverage menus, but business actors need to try to produce product innovations in order to provide satisfactory service to customers. In this condition, a data processing technique is needed to determine customer segmentation and menu recommendations at Bonjur Cafe Resto. The analysis method used is RFM Analysis by analyzing customer behavior, analyzing purchase transaction data consisting of Recency Frequency Monetary (RFM) attributes and data mining techniques with the Apriori algorithm, where this algorithm is used to determine the most frequently appearing data set (frequent itemset). The results of this study are grouped into five categories of customers based on their purchasing behavior and association rules are formed with predetermined parameters, support 28% and confidence 70%. This can later be a recommendation for a menu combination from the data that has been collected and applied using the apriori algorithm so that it is expected to be used for service evaluation and be able to increase customer satisfaction so that Bonjur Cafe Resto can develop better
Sentiment Analysis of Social Media X Users Towards Legislators Engaged in Online Gambling Using Naïve Bayes Algorithm Vivi Nurmaylina; Yuma Akbar
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 3 (2024): DECEMBER 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i3.3079

Abstract

This research analyzes public feelings toward legislative members participating in online gambling applying the Naïve bayes classification technique. The collected data were processed, labeled, cleaned, preprocessed, and classified using RapidMiner Studio software, while conducting the sentiment analysis according to a systematic approach from each of those steps described above, namely, data crawling, cleaning, preprocessing, and classification of the Twitter data. Sentiment distribution yielded 286 negative and 90 positive sentiments with a prediction accuracy of 73.10%. These findings illustrate an overwhelmingly negative public response to this behavior and the expectation society has for legislators as public figures.
Automatic Purchase Order Classification Using SVM in POS System at Skus Mart Sri Lestari; Muhamad Zaeni Nadip; Yuma Akbar; Aditya Zakaria Hidayat; Raisah Fajri Aula
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4564

Abstract

In retail business processes, decision-making regarding Purchase Order PO submissions often remains manual and subjective, creating risks that impede procurement efficiency. The study develops an automatic classification model to predict PO approval status using Support Vector Machine SVM algorithm integrated within Point of Sale POS systems. Historical purchase transaction data was obtained from SKUS Mart POS database containing 133 entries, including attributes such as item quantity, purchase price, previous stock levels, and total purchase amounts. The research applies CRISP-DM methodology, encompassing business understanding, data exploration, preprocessing normalization using StandardScaler, model training, evaluation, and deployment phases. The model was trained using linear kernel and validated through holdout technique with 80:20 ratio for training and testing. Test results demonstrate that the SVM model achieves 76.69% accuracy, 82.21% precision, 76.69% recall, and 78.51% F1-score. The model was implemented in a web-based POS system CodeIgniter 3 combined with Python scripts to generate automatic classifications displayed directly in the user interface. Although the model demonstrates adequate performance, the study has not compared its effectiveness against other machine learning algorithms such as Random Forest or K-Nearest Neighbor. These findings establish initial groundwork for machine learning integration to support decision automation in procurement systems.
Optimization of Bandwidth Management and Network Security Using PPPoE Method and Intrusion Detection Prevention System Muhammad Arham; Yuma Akbar
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.5021

Abstract

Rural internet networks frequently struggle with unstable connections, bandwidth waste, and cyber vulnerabilities. We optimized bandwidth management and network security by implementing Point to Point Protocol over Ethernet (PPPoE) alongside Intrusion Detection and Prevention System (IDPS). PPPoE manages user authentication and dynamic bandwidth allocation, while IDPS identifies and blocks network threats. Our experimental research took place in Sukanegara Village network environment. Testing involved network load simulations and cyber-attack scenarios to evaluate system performance. We compared network metrics before and after implementation, focusing on bandwidth consumption, threat detection rates, and connection stability. PPPoE implementation reduced bandwidth consumption by 35% through controlled user access and fair distribution mechanisms. The IDPS successfully detected 92% of simulated attack attempts, including port scanning, flooding attacks, and unauthorized access attempts. Network latency dropped significantly during peak usage hours, while connection stability improved across all user categories. The combined PPPoE-IDPS solution effectively addresses rural network challenges. The system delivers cost-efficient bandwidth management while maintaining robust security protection. Implementation requires minimal additional hardware and allows management by local technical staff. Our findings support widespread adoption in community and village-scale networks seeking reliable internet infrastructure with adequate security measures.
Optimization of Data Security Protection with Full SSL Inspection on AWS Using FortiGate Virtual Appliance Yuma Akbar; Gipari Pradina Abdillah; Dadang Iskandar Mulyana; Sutisna Sutisna
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.5153

Abstract

The expanding adoption of cloud services, particularly Amazon Web Services (AWS), has intensified challenges in protecting encrypted data traffic within network security frameworks. SSL/TLS protocols, widely utilized for data encryption, have become exploitation vectors for cyber adversaries as conventional security solutions lack the capability to scrutinize encrypted traffic effectively. The research addresses such security gaps by implementing Full SSL Inspection through Fortigate Virtual Appliance deployment within AWS cloud environments. The study examines cloud-based network architecture integrated with Fortigate systems, employing methodologies that encompass virtual appliance installation, SSL/TLS inspection feature configuration, and assessment of system effectiveness alongside performance impact evaluation. Research instruments include simulated cyber-attack scenarios targeting encrypted traffic patterns. Findings demonstrate that Full SSL Inspection significantly enhances threat detection capabilities within network traffic, albeit with measurable increases in system latency and computational overhead. The implementation of Fortigate Virtual Appliance proves effective in strengthening AWS data security postures. Research outcomes emphasize the necessity for configuration optimization to maintain security-performance equilibrium, positioning the solution as viable for organizations prioritizing data protection strategies
Analisis Clustering Penyakit Menular pada Manusia di Jakarta Timur Menggunakan Algoritma K-Means Muhammad Arya Ramadhan; Edhy Poerwandono; Yuma Akbar; Aditya Zakaria Hidayat
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 1 (2025): JANUARI-MARET 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.v9i1.3007

Abstract

Humans are highly susceptible to various diseases without realizing their causes. The high incidence of infectious diseases in East Jakarta requires an analysis of distribution patterns to determine intervention priorities. This study aims to identify clusters of infectious diseases in East Jakarta, helping authorities plan effective prevention and treatment strategies. Data on infectious disease cases were obtained from the Central Statistics Agency of DKI Jakarta. The K-Means algorithm was used to cluster data based on variables such as period, region, type of disease, and number of cases. The results indicate several main clusters with distinct characteristics that can serve as a foundation for targeted strategies. From 2018 to 2021, diarrhea was predominant, making up 84.14% of cases in 2018 and 81.97% in 2019, pneumonia accounted for 32.92% in 2020, and TB Paru 33.63% in 2021. In conclusion, the K-Means algorithm effectively clusters infectious disease data and provides useful insights into disease distribution in East Jakarta, improving the impact of data-driven health programs.
Implementasi Game 2D Edukasi Pengetahuan Islam untuk Remaja Menggunakan Unity Yuma Akbar; Abdurrahman Asyam Albahy
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 1 (2025): JANUARI-MARET 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.v9i1.3019

Abstract

This research aims to address the lack of interest among children in learning basic Islamic knowledge through conventional learning methods, which are often perceived as boring. The proposed solution is the development of Unity-based educational 2D games that present basic Islamic knowledge in an engaging and interactive way. The target audience for this research is children aged 12–15 years, who are expected to show greater interest and motivation to learn Islam through more enjoyable media. The methodology employed in this research is the Waterfall method, consisting of the stages of needs analysis, system design, implementation, verification, and maintenance. The tools used include Unity software for game development and Visual Studio for C# coding. The study also utilized surveys and observations to measure the game's effectiveness in enhancing children's knowledge and engagement. Through efficient project management, it is anticipated that this educational game will become an effective and engaging learning tool for children, while contributing significantly to the field of Islamic religious education.
Optimasi Gigabit Passive Optical Network dan Algoritma Naïve Bayes dalam Analisis Jaringan FTTH Suwandi; Yuma Akbar; Dadang Iskandar Mulyana
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 1 (2025): JANUARI-MARET 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.v9i1.3058

Abstract

Internet service users expect reliable bandwidth quality to support the communication access process. From year to year, human needs for communication services continue to increase. Humans still want convenience in daily activities such as sending messages, video and voice, and want the quality of sending and receiving messages to be fast. This encourages telecommunications service providers to focus on innovative telecommunications networks to meet the needs of all customers. Research began by taking data at Tablue and AVS regarding the distance of the fiber cable used as far as 10Km from the OLT. Manual calculations using OTDR. The results of previous measurements and data processing regarding the attenuation obtained in fiber cables are followed by calculating the total attenuation using the existing formula. The next stage is data processing using RapidMiner software with the Naive Bayes algorithm. The final results of the comparison with this test method, namely the prediction results) show an accuracy value of 99.91%. Of the 1124 test data, 1080 data were predicted as OK sentiment and 43 data as Not OK. For prediction results from Not ok. and the Naive Bayes method shows an accuracy value of 0.962% OK. Not ok 0.038% of 1124, test data.
Co-Authors AA Sudharmawan, AA Abdul Shomad Abdulloh Abdurrahman Asyam Albahy Abror, Ikhsan Adhipramana, Fernanda 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 Ardana, Tegar Rizky Arfadhillah, Zahra Ari Ramadhan 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 Betty Yel, Mesra Betty Yel, Mesra Bintoro, Bayu Bryan Pratama Cahyono, Bayu Adi Candra Milad Ridha Eislam Dadang Iskandar Mulyana` Dadang Iskandar, Dadang Damayanti, Yulia Dava Septya Arroufu Dedi Dwi Saputra Dewa Gde Adi Murthi Udayana Doddy Mulyadi Saputra Edhy Poerwandono Edhy Poerwandono Edhy Poerwandono Eka Satria Maheswara Fadhil Khanifan Achmad Fadillah, Fauzan Fahmi Chairulloh Faisal Akbar Faisal Akbar Nasution Farhani, Aulia Farisi, Muhamad Fatkul Toriq Febrianti, Syafira Feni Putriani Fentri Boy Pasaribu Fernanda Adhipramana Fitriani Noer Jamilah Franido, Richard Gipari Pradina Abdillah Gusniar Alfian Noor Hafiz, Tegar Muhamad Hartinah, Suci Sugih Hazrul Aswad Hengky, Mario Hidayat, Aditya Zakaria Hutabarat, Joey Abdiner Parlindungan Ikhsan Abror Ikhwanul Kurnia Rahman Jodi Juliansah Juliansah, Jodi Julianto, Muhammad Rizky Julvan Marzuki Putra Sibarani K, Benny Sulaiman Kamali, Muhamad Fawaz Kiki Setiawan Kusuma, Agung Wiranata Sugeng Laia, Apriyanus Laia, Masaranto Lestari, Dinny Amalia M Ilham Setya Aji M Jundi Hakim Mafazi, Luthfillah Marjuki Maulana Putra Hertaryawan, Ryfan Mayangsari, Descania Meilisa Miftahul Huda Mizsuari Muamar Rizky Mohammad Farroos Al Ammaar Muhamad Fikri Nugraha Muhamad Umar Hasan Asrori Muhamad Zaeni Nadip Muhammad Arham Muhammad Arya Ramadhan Muhammad Faizal Lazuardi Mulya, Citra Pricylia Ananda Nirat Nirat Nirat, Nirat Noor, Gusniar Alfian Novianto, Firza NST, Silvan Nufus, Reda Hayati Nugraha, Muhamad Fikri Nur Arif Khairudin Nurfaishal, Muhammad Dzaky Nurmaylina, Vivi Oka Prasetiyo Oktavian, Nur Oky Tria Saputra Oky Tria Saputra7 Pakpahan, Gabriel Alezhandro Pane, Ropindo Pelix 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 Raisah Fajri Aula Ramadhan, Muhammad Arya Regita, Anggit Nur Hannaa Rezha Mulia Revandy Richard Franido Richard Franido Rizki Maulana, Rizki Rizky Adawiyah Rosiana, Grace Lolita S, Fahmi Chairulloh Widia Safhani, Rizca Sahrul Hidayat Sahrul Hidayat Saputra, Mochammed Erryandra Sarimole, Frencis Matheos Septiansyah, Ade Setiawan, Kiki Sibarani, Julvan Marzuki Putra Sinaga, Putri Cahyani Sri Lestari Sri Lestari SRI LESTARI Sugiharto, Tri Sugiyono Sugiyono Sugiyono Sumpena Sumpena Sumpena, Sumpena Surapati, Untung Sutisna Sutisna Sutisna Sutisna Sutisna Suwandi Suwandi Tafonao, Rekardius Tafonao, Wewisman Tegar Muhamad Hafiz Tegar Muhamad Hafiz Toriq, Fatkul Tri Wahyudi Tristhanaya, Angga Tundo, Tundo Untung Surapati Untung Surapati Untung Surapati Untung Wahyudi Untung Wahyudi Vivi Nurmaylina Wahyu Saputro Widya Ayu Lestari Wijaya, Rohmat WINDU GATA Yusril Nurhadi AS