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Journal : International Journal Software Engineering and Computer Science (IJSECS)

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%.
Co-Authors Abdillah, Junindo Abdulloh Achmad Syaeful Aditya Zakaria Hidayat Ahmad Baidowi 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 Azis, Abd Barronzoeputra, Gaoeng Qalbun Beay, Richardviki Betty Yel, Mesra Bili, Yudisman Ferdian Bimantoro, Dava Sevtiandra Brian - Pangestu Candra Milad Ridha Eislam Dadang Iskandar Mulyana` Dava Septya Arroufu Diadi, Randitia Ridad Fadhil Khanifan Achmad Fahmi Chairulloh Fahmi, Hakon Feni Putriani Fentri Boy Pasaribu Ginting, Yafet Nikolas Guntara, Arya Hakim, Lukamanul Haryati Heri Rizky Firdaus Ikhwanul Kurnia Rahman Karim, Lutfi 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 Nurmayanti, Laily Nurmaylina, Vivi Oky Tria Saputra7 Praja Raymond , Samuel Purwandono, Eddy Purwanto, Helmi Purwasih, Intan Rahmah, Shafira Azzahra Nurul Raihan, Farid Raihanah, Syifa Randitia Ridad Diadi Rasiban Rizky Adawiyah Romadan, Diva Putra Saepudin Septian, Wahyu Septiansyah, Muhamad Aqil Septianto, Ahas Eko Setiawan, Kiki Siahaan, Bangun Sugiono Sugiono Sugiyono Surapati, Untung Sutisna Syaeful, Achmad Tanjung, Cici Yolanda Tasya Aisyah Amini Tundo, Tundo Untung Wahyudi Wibawa, Andri Putra Widianto Putro, Faris Yakob, Galih Satria Yuliantoro, Dita Tri