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All Journal Teknika CESS (Journal of Computer Engineering, System and Science) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan INTECOMS: Journal of Information Technology and Computer Science JURNAL PENDIDIKAN TAMBUSAI Jurnal Sains dan Teknologi Journal of Applied Engineering and Technological Science (JAETS) Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Pengabdian Nasional (JPN) Indonesia J-SAKTI (Jurnal Sains Komputer dan Informatika) AJAD : Jurnal Pengabdian kepada Masyarakat Jurnal Pendidikan Sains dan Komputer International Journal Software Engineering and Computer Science (IJSECS) International Journal Education and Computer Studies Aptekmas : Jurnal Pengabdian Kepada Masyarakat Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Nasional Teknologi Komputer Malcom: Indonesian Journal of Machine Learning and Computer Science Journal of Artificial Intelligence and Digital Business CKI On Spot Sistem Komputer & Teknologi Intelegensi Artifisial (SIKOMTIA) Jurnal Indonesia : Manajemen Informatika dan Komunikasi Jurnal Pengabdian Nasional (JPN) Indonesia Journal Innovations Computer Science International Journal of Applied Mathematics and Computing. International Journal of Computer Technology and Science International Journal of Information Engineering and Science International Journal of Mechanical, Electrical and Civil Engineering Journal of Engineering, Electrical and Informatics
Sarimole, Frencis Matheos
Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika
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Journal : international journal software engineering and computer science ijsecs

 1 
Implementation of IoT-Based Facial Recognition for Home Security System Using Raspberry Pi and Mobile Application Sarimole, Frencis Matheos; Septianto, Ahas Eko
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 2 (2024): AUGUST 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i2.2554

Abstract

The rapid advancement of technologies such as Artificial Intelligence (AI), computer vision, and the Internet of Things (IoT) has significantly impacted various fields, particularly in security systems. Traditional security measures, such as door locks, are increasingly inadequate in ensuring the safety of homes. To address this issue, we have developed a prototype of a home security system based on Raspberry Pi, integrated with a real-time mobile application. This intelligent system is designed to monitor residential areas, detect unfamiliar individuals, and send immediate notifications to the homeowner's mobile device. Utilizing Raspberry Pi in conjunction with OpenCV for motion and facial recognition, as well as a web server, the system demonstrates high accuracy in detecting motion and faces. It promptly notifies the homeowner in the event of suspicious activity. This prototype represents an efficient and effective solution to enhancing home security by leveraging modern technology.
Data Mining Modeling Using the K-Means Algorithm to Analyze the Impact of New Media on Early Childhood Psychology at Bimba Rainbow Kids Sukmajaya Sugiyono; Haryati; Sarimole, Frencis Matheos; Tundo
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 2 (2024): AUGUST 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i2.2874

Abstract

New media, particularly the internet, has become an integral aspect of contemporary life, fundamentally altering the ways in which individuals interact, learn, play, and access information. The continuous evolution of new media, driven by technological advancements, exerts a profound influence on its users, with implications that span various dimensions of human experience. This study aims to analyze and classify the psychological impact of new media on early childhood, specifically within the context of Bimba Rainbow Kids Sukmajaya, utilizing the K-Means data mining method. This research employs a qualitative approach to uncover the underlying factors that shape the psychological effects observed in young children. The anticipated outcomes of this study are expected to contribute significantly to the academic discourse on the influence of new media on early childhood psychology. Moreover, the findings hold potential relevance for educators, parents, teachers, policymakers, and the general public who are invested in comprehending the broader implications of new media on the psychological development of early childhood
Application of Decision Tree Method for Sales Prediction at PT. Cipta Naga Semesta (Mayora Group) North Jakarta for 2023 Beay, Richardviki; Sarimole, Frencis Matheos
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.v4i3.2999

Abstract

The purpose of this study is to forecast sales of PT. Cipta Naga Semesta, one of the companies owned by Mayora Group headquartered in North Jakarta using the Decision Tree method during 2023. Decision Tree was chosen because this model identifies key attributes that greatly affect sales in the data and has the ability to predict outcomes by recognizing patterns in historical data. The database used in this analysis includes monthly records of sales, promotions, prices, and other economic characteristics. The findings of the study indicate that the Decision Tree method is very effective in providing accurate sales predictions with a low margin of error. The forecast provides valuable perspectives for company management, which can help them design tighter sales strategies and make better inventory decisions, thereby maximizing operational efficiency and profitability. In addition, the exploration of sales prediction models is one of the future works proposed in this study, which recommends practitioners to explore alternative methods to improve forecast accuracy and robustness.
Analysis of Scooter Spare Parts Sales at Harapan Indah Scooter Using the K-Means Algorithm Sarimole, Frencis Matheos; Lingga, Tracy Olivera
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.v4i3.3026

Abstract

: K-means clustering algorithm has been used in this study to analyze the sales performance of scooter spare parts at Harapan Indah Scooter. By using the K-means method, researchers can classify products into 3 categories according to their sales volume. The purpose of this analysis is to identify patterns in sales data and compare the characteristics of each product group. Researchers can see the output from the previous step shows three clusters: Low, Medium, and High Sales. Associating products with these categories Empowers improved tracking of sales movements and fluctuation trends in product options. The findings of this study can be useful in the field of inventory management and to develop marketing strategies to increase product sales. Companies can find out which products fall into which categories and therefore can make better decisions on how to manage stock and promotional efforts. These findings are the first step to maintain and improve sales performance and optimize Harapan Indah Scooter business
Vehicle License Plate Object Detection for Vehicle Registration Using Fuzzy Logic Alannuari, Fiky; Sarimole, Frencis Matheos; Mulyana, Dadang Iskandar
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.v4i3.3055

Abstract

Object detection of vehicle license plates plays a role in the efficiency of vehicle data collection systems. There are many factors that make the accuracy and speed of detection on vehicle license plates less than optimal, causing errors in the detection process. The factors that affect the accuracy of object detection of vehicle license plates include clarity, lighting, shadows, color, font type, weather, and others. Based on the advantages of the Fuzzy Logic approach in handling various vague factors and uncertain data, it is hoped that this method can help the detection process to be more accurate and faster. This research aims to develop a method for detecting vehicle license plate objects using the Fuzzy Logic approach so that it can be applied in diverse environments to produce data with consistent accuracy. This research involves the development of software integrated with computers and cameras for vehicle license plate recognition, and also takes some data sources and code from libraries already available in the programming language used. The results of the tests conducted, detection using this Fuzzy Logic approach has an accuracy rate of up to 93.33% and the accuracy of reading the text stored in the database reaches 63.66%.
Application of Decision Tree Method for Sales Prediction at PT. Cipta Naga Semesta (Mayora Group) North Jakarta for 2023 Richardviki Beay; Frencis Matheos Sarimole
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.v4i3.2999

Abstract

The purpose of this study is to forecast sales of PT. Cipta Naga Semesta, one of the companies owned by Mayora Group headquartered in North Jakarta using the Decision Tree method during 2023. Decision Tree was chosen because this model identifies key attributes that greatly affect sales in the data and has the ability to predict outcomes by recognizing patterns in historical data. The database used in this analysis includes monthly records of sales, promotions, prices, and other economic characteristics. The findings of the study indicate that the Decision Tree method is very effective in providing accurate sales predictions with a low margin of error. The forecast provides valuable perspectives for company management, which can help them design tighter sales strategies and make better inventory decisions, thereby maximizing operational efficiency and profitability. In addition, the exploration of sales prediction models is one of the future works proposed in this study, which recommends practitioners to explore alternative methods to improve forecast accuracy and robustness.
Analysis of Scooter Spare Parts Sales at Harapan Indah Scooter Using the K-Means Algorithm Frencis Matheos Sarimole; Tracy Olivera Lingga
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.v4i3.3026

Abstract

: K-means clustering algorithm has been used in this study to analyze the sales performance of scooter spare parts at Harapan Indah Scooter. By using the K-means method, researchers can classify products into 3 categories according to their sales volume. The purpose of this analysis is to identify patterns in sales data and compare the characteristics of each product group. Researchers can see the output from the previous step shows three clusters: Low, Medium, and High Sales. Associating products with these categories Empowers improved tracking of sales movements and fluctuation trends in product options. The findings of this study can be useful in the field of inventory management and to develop marketing strategies to increase product sales. Companies can find out which products fall into which categories and therefore can make better decisions on how to manage stock and promotional efforts. These findings are the first step to maintain and improve sales performance and optimize Harapan Indah Scooter business
Vehicle License Plate Object Detection for Vehicle Registration Using Fuzzy Logic Fiky Alannuari; Frencis Matheos Sarimole; Dadang Iskandar Mulyana
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.v4i3.3055

Abstract

Object detection of vehicle license plates plays a role in the efficiency of vehicle data collection systems. There are many factors that make the accuracy and speed of detection on vehicle license plates less than optimal, causing errors in the detection process. The factors that affect the accuracy of object detection of vehicle license plates include clarity, lighting, shadows, color, font type, weather, and others. Based on the advantages of the Fuzzy Logic approach in handling various vague factors and uncertain data, it is hoped that this method can help the detection process to be more accurate and faster. This research aims to develop a method for detecting vehicle license plate objects using the Fuzzy Logic approach so that it can be applied in diverse environments to produce data with consistent accuracy. This research involves the development of software integrated with computers and cameras for vehicle license plate recognition, and also takes some data sources and code from libraries already available in the programming language used. The results of the tests conducted, detection using this Fuzzy Logic approach has an accuracy rate of up to 93.33% and the accuracy of reading the text stored in the database reaches 63.66%.
Development of an E-Commerce Website Integrated with a Payment Gateway for Basreng RZQ Small and Medium Enterprise in Bandung Nur Aswan Multazam; Frencis Matheos Sarimole
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 2 (2026): AUGUST 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i2.7588

Abstract

This study aims to develop an e-commerce website integrated with the Midtrans payment gateway for Basreng RZQ, a micro, small, and medium-sized enterprise (MSME) in Bandung. The study is motivated by operational challenges in reconciling daily transaction data due to the absence of an internal admin panel on the existing website. This condition has the potential to cause errors in manual bookkeeping and increase the workload of business operators. To address these problems, an e-commerce platform was developed to enable customers to order products and make digital payments without requiring account registration. The study employed a descriptive-evaluative qualitative case study with a lean architecture approach. Data were collected through observation, interviews, and documentation and were analyzed based on the transaction processes and operational needs of the MSME. Functional system testing was conducted using the black-box testing method based on ordering and payment verification scenarios. The results indicate that the integration of the Midtrans payment gateway supports automated payment verification and helps simplify transaction management. The developed system also provides a more structured alternative for recording transactions compared with manual bookkeeping. This study provides a practical solution for supporting the digitalization of sales and payment processes in MSMEs and may serve as a reference for developing e-commerce systems integrated with digital payment services.
Implementation of a Web-Based Inventory Monitoring System at Optik Sanjaya Depok Axel Rajaliu Chaniago; Frencis Matheos Sarimole
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 3 (2026): DECEMBER 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i3.8249

Abstract

Optik Sanjaya Depok, a micro, small, and medium enterprise (MSME) engaged in eyewear retail, still recorded its eyeglasses stock manually in handwritten ledgers, which frequently resulted in recording errors, delayed stock updates, difficulty in determining available items, and time-consuming report preparation. This study aimed to design and implement a web-based stock monitoring system to establish more structured, efficient, and traceable inventory management for the store. The system was developed using the Waterfall software development life cycle, covering requirement analysis, Unified Modeling Language (UML) and Entity-Relationship Diagram (ERD) design, implementation using PHP Native, MySQL, and Bootstrap, and testing. The system provides role-separated access for the Administrator and the Warehouse Admin, a summary dashboard, user management, item and item-category data management, incoming-stock and outgoing-stock recording that automatically updates item quantities, real-time stock monitoring, stock reporting with Excel export, and DataTables-based search, filter, sort, and pagination. Black box testing was applied to ten core features, and every test scenario produced the expected result. User Acceptance Testing using a five-point Likert-scale questionnaire completed by two respondents consisting of the owner and warehouse staff of Optik Sanjaya Depok yielded average scores between 4.7 and 4.9 (overall average 4.82). The system replaced the manual recording process and supported centralized, consistent stock recording; the reduction of stock-data errors was not measured quantitatively in this study and is therefore not claimed as a research finding. These findings indicate that a role-based, web-based stock monitoring system is a feasible initial step in the digital transformation of small-scale optical retail businesses.
Co-Authors Abdillah, Junindo Abdulloh Achmad Syaeful Aditya Zakaria Hidayat Ahas Eko Septianto Ahmad Baidowi Ahmad Ramdani Akbar, Firman Aulia Akbar, Yuma Alannuari, Fiky Alwi Renaldhy Amelia, Ika Andrian Nur Ihsan Anita Rosiana Apriyanto, Kevin Jonathan Ari Ramadhan Arinal, Veri Aryanti, Putri Gea Awang Hariman, Aloisius Axel Rajaliu Chaniago Azis, Abd Barronzoeputra, Gaoeng Qalbun Beay, Richardviki Bere Tae, Chelvyn Erikson Betty Yel, Mesra Betty Yel, Mesra Bili, Yudisman Ferdian Bimantoro, Dava Sevtiandra Brian - Pangestu Candra Milad Ridha Eislam Dadang Iskandar Mulyana` Dava Septya Arroufu Dedi Gunawan Diadi, Randitia Ridad Fadhil Khanifan Achmad Fahmi Chairulloh Fahmi, Hakon Feni Putriani Fentri Boy Pasaribu Fiktor Kurnia Tafonao Fiky Alannuari Ginting, Yafet Nikolas Guntara, Arya Hakim, Lukamanul Haryati Heri Rizky Firdaus Ikhwanul Kurnia Rahman Iqhlima, Salabila Listania Karim, Lutfi Kiki Setiawan Kudrat, Kudrat Kurnia, Mega Tri Lingga, Tracy Olivera Lutfi Karim Marjuki Marliani, Tiara Meilisa Miftahul Huda Muhammad Ilham Fadillah Novianto, Firza Nufaisa Almazar Nugraha, Pramudya Nur Arif Khairudin Nur Aswan Multazam Nurmayanti, Laily Nurmaylina, Vivi Oky Tria Saputra7 Praja Raymond , Samuel Pramudya Nugraha Purwandono, Eddy Purwanto, Helmi Purwasih, Intan Rahmah, Shafira Azzahra Nurul Raihan, Farid Raihanah, Syifa Randitia Ridad Diadi Rasiban Richardviki Beay Rindy Julianda Rizky Adawiyah Roid Adip Akmal Romadan, Diva Putra Saepudin Satria Wira Yudha Septian, Wahyu Septiansyah, Muhamad Aqil Septianto, Ahas Eko Setiawan, Kiki Siahaan, Bangun Sidiq, Bagas Maulana Siti Nur Hidayati SOPAN ADRIANTO Sugeng Sugeng Sugiono Sugiono Sugiyono Sugiyono Sugiyono Surapati, Untung Sutisna Sutisna Sutisna Syaeful, Achmad Tanjung, Cici Yolanda Tasya Aisyah Amini Tracy Olivera Lingga Tundo, Tundo Untung Wahyudi Wibawa, Andri Putra Wida Lestari Widianto Putro, Faris Wijayanto, Willy Yakob, Galih Satria Yuliantoro, Dita Tri