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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Martabe : Jurnal Pengabdian Kepada Masyarakat The IJICS (International Journal of Informatics and Computer Science) Informatika Journal of Applied Engineering and Technological Science (JAETS) Jatilima : Jurnal Multimedia Dan Teknologi Informasi Indonesian Journal of Electrical Engineering and Computer Science INFOKUM Computer Science and Information Technologies Ihsan: Jurnal Pengabdian Masyarakat Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) International Journal Of Science, Technology & Management (IJSTM) Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) Jurnal Sains Teknologi dan Sistem Informasi Proceeding International Seminar of Islamic Studies Jurnal Minfo Polgan (JMP) Prosiding Snastikom sudo Jurnal Teknik Informatika Edu Society: Jurnal Pendidikan, Ilmu Sosial dan Pengabdian Kepada Masyarakat Internasional Journal of Data Science, Computer Science and Informatics Technology (InJODACSIT) Blend Sains Jurnal Teknik Wahana TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi International Journal of Economic, Technology and Social Sciences (Injects) Jurnal Pengabdian Barelang Jurnal Ilmu Komputer dan Sistem Informasi Hanif Journal of Information Systems Electronic Integrated Computer Algorithm Journal Jurnal Sains, Teknologi dan Komputer Economic: Journal Economic and Business Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Pengabdiaan Masyarakat Larisma Al'Adzkiya International of Computer Science and Information Technology Journal AQILA : Acceleration, Quantum, Information Technology and Algorithm Journal Tsabit
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Journal : Electronic Integrated Computer Algorithm Journal

Application of Multiple Linear Regression Models in Forming Priority patterns of Village Fund Budget Use Nasution, Tia Alfi Sahara; Al-Khowarizmi
Electronic Integrated Computer Algorithm Journal Vol. 2 No. 1 (2024): VOLUME 2, NO 1: OCTOBER 2024
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/enigma.v2i1.37

Abstract

This study aims to analyze the factors that influence the level of utilization of the village fund budget in Dolok Maraja Village, Simalungun Regency. Descriptive quantitative method with Multiple Linear Regression analysis was used to achieve the objective. The results showed that there was a significant relationship between the independent variable (village fund budget) and the dependent variable (the utilization rate of the village fund budget). The factors that most influence the utilization rate of the village fund budget are population, area, and poverty level. Implication of The implication of this study is that the government should consider these factors in the process of allocating village fund budgets. Villages with larger populations, larger areas, and higher poverty rates require larger budget allocations to ensure effective and efficient village development. In addition, the importance of good governance of village fund budgets and active community participation in the process of planning and implementing village development is also highlighted in this study. Specifically, this study shows that every year, the utilization rate of the village fund budget increases by an average of 6.5632. Meanwhile, each increase in the number of poor people and the Village Fund Ceiling decreases and increases the utilization rate of the village fund budget by an average of 2.6104 and 3.7433, respectively. Village area did not have a significant effect. Although this regression model has low explanatory power, it is statistically valid and fits the observed data. This research highlights the importance for the government to consider the factors of population, area, and Village Fund Ceiling in allocating the village fund budget, as well as improving governance and community participation in village development.
Modification of K-Nearest Neighbor Method with Normalized Euclidean Distance for Classification of Local Berastagi Orange Quality Siregar, Ananda Afifah; Al-Khowarizmi
Electronic Integrated Computer Algorithm Journal Vol. 2 No. 2 (2025): VOLUME 2, NO 2: APRIL 2025
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/enigma.v2i2.60

Abstract

Local Indonesian fruit is one example of Indonesia's natural wealth, one of which is the local Berastagi orange. Oranges are rich in vitamin C which is good for body health. Oranges tend to have a sour, fresh, and sweet taste. The vitamin C contained in oranges is 97.3 milligrams or equivalent to 163% of the nutritional adequacy rate. Not only Vitamin C, oranges also contain vitamin B6, antioxidants and fiber. Therefore, it is highly recommended to consume oranges every day because oranges can facilitate digestion, reduce the risk of diabetes, maintain healthy skin, and also maintain endurance. This study aims to apply the Classification and assessment of the quality of local oranges using the K-Nearest Neighbor (KNN) method modified with Normalized Euclidean distance to classify the quality of local Berastagi oranges based on the color of the fruit image. The research dataset was taken from 100 images of local Berastagi oranges, where the 100 images were divided into 2, namely, good oranges and bad oranges. The classification process for local Berastagi oranges uses the matlab application.
Quality Classification of Air Quality in Medan Industrial Area Using Naïve Bayes Method Zhafirah, Zhahrah; Al-Khowarizmi
Electronic Integrated Computer Algorithm Journal Vol. 2 No. 2 (2025): VOLUME 2, NO 2: APRIL 2025
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/enigma.v2i2.61

Abstract

Advances in information technology have affected various aspects of life, including efforts to monitor air quality. Clean air is a basic human need, but technological developments and increased industry and the number of motorized vehicles have caused a decline in air quality. Air pollution has various negative impacts, including health problems and global warming. To help the community and government in monitoring air quality, this study implements a data mining method with a classification technique using the Naïve Bayes Algorithm. This method was chosen because of its effective ability to predict air quality based on historical data. This study uses data from the Air Pollution Standard Index (ISPU) parameters to build a classification model that can separate air quality categories, such as Good, Moderate, Unhealthy, Very Unhealthy, and Hazardous. The results of the study are expected to provide accurate information to the public about air quality in KIM, as well as assist the government in efforts to control air pollution.
Application of Region of Interest (ROI) in Student Attendance Detection System in Classroom Faizi, Setyo Fahmi Noor; Al-Khowarizmi
Electronic Integrated Computer Algorithm Journal Vol. 3 No. 1 (2025): VOLUME 3, NO 1: OCTOBER 2025
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/enigma.v3i1.107

Abstract

Efficient classroom management is a crucial requirement in academic environments such as the Faculty of Computer Science and Information Technology to increase productivity. This study aims to design and evaluate a real-time presence detection and counting system by implementing the Region of Interest (ROI) method to improve computational efficiency and accuracy. This methodology involves the use of a Logitech C270 HD webcam, with a static ROI set at 90% of the central video frame to focus the analysis. Person detection and counting are performed using a combination of Histogram of Oriented Gradients (HOG) for the body and Haar Cascade for the face. Time series reasoning with a minimum duration of 60 seconds and a grace period of 5 seconds is implemented to validate presence and stabilize the room status, with system performance evaluated using Precision and Recall metrics. The results show that the system successfully displays the status and number of people in the room very well, but the evaluation shows a Recall value of 1.00, which means the system detects every actual human presence. However, this system has significant accuracy issues, indicated by a low Precision of 0.04 and a high number of False Positives of 710. In conclusion, although the ROI application successfully improves the computational load and the temporal logic stabilizes the output, the HOG and Haar Cascade models are inadequate to handle visual noise in the ROI, resulting in low Precision and indicating the need for more sophisticated detection models.
Implementation of Machine Learning For Indonesian Sign Language Recognition Using Convolutional Neural Network Model Salamah, Umi; Al-Khowarizmi
Electronic Integrated Computer Algorithm Journal Vol. 3 No. 1 (2025): VOLUME 3, NO 1: OCTOBER 2025
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/enigma.v3i1.108

Abstract

Sign language is the primary means of communication for people with hearing impairments. However, the public's limited understanding of Indonesian Sign Language (BISINDO) remains a communication barrier. This study implemented machine learning with a Convolutional Neural Network (CNN) model to automatically recognize BISINDO gestures. The dataset consists of 2,600 manually captured hand images representing the letters A–Z. The training process was carried out through data pre-processing, image augmentation, and CNN parameter optimization. Test results showed that the system was able to recognize BISINDO letters with high accuracy and could combine letters into simple words such as "HAI", "SAYA", and "UMI" in real-time. This study demonstrates that CNN is effective in supporting a computer-based sign language translation system, thus becoming an inclusive communication solution for people with hearing impairments.
Implementation of a Drowsiness Detection System in Four-Wheel Vehicle Drivers Using OpenCv Ma’ajid, Farhan Riqi; Al-Khowarizmi
Electronic Integrated Computer Algorithm Journal Vol. 3 No. 1 (2025): VOLUME 3, NO 1: OCTOBER 2025
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/enigma.v3i1.109

Abstract

Drowsiness while driving is one of the triggers of traffic accidents. This study proposes a non-invasive and economical computer vision-based real-time drowsiness detection system. The system combines Eye Aspect Ratio (EAR) to assess eye openness, Convolutional Neural Network (CNN) for open/closed eye classification, and MediaPipe FaceMesh for stable facial landmark extraction. The dataset is taken from Kaggle (Open and Closed classes, totaling 1,452 images) and processed through grayscale conversion, normalization, 64×64 pixel resizing, and augmentation. Drowsiness detection is triggered when EAR <0.25 and CNN classifies both eyes as closed for ±2 consecutive seconds; visual/audio alarms are automatically activated. Test results on 218 images show excellent performance with only 1 misclassification (≈99.5% accuracy), with no false alarms for the open eye class. The system is implemented as a Flask-based web application for easy cross-device access. These findings demonstrate an efficient visual approach that is feasible to be integrated as a driving safety feature.
Co-Authors Abdulbasah Kamil, Anton Ade Haikal Adidtya Perdana, Adidtya Adila Mawaddah Meuraxa Ajulio Padly Sembiring Akbar Idaman Al Hamidy Albara Amrullah Amrullah Amrullah Andy Satria Angkat, Fhatiya Alzahra Aulia Jannah Bela, Bela Budi Kurniawan Hutasuhut Chindy Yovita Sukma Dalimunthe, Yulia Agustina Diana, Has Dicky Apdilah Edy Rahman Syahputra Efendi, Syahril Elveny, Marischa Fadhilah, Ulfa Faizi, Setyo Fahmi Noor Faradillah, Yanty Farid Akbar Siregar Fatma Sari Hutagalung FAUZI . Fauzi Fauzi Faza, Sharfina Ferry Fachrizal - Firahmi Rizky Frainskoy Rio Naibaho Gabriel Ardi Hutagalung Ginting, Nurman Habibi Ramdani Safitri Halim Maulana Hapzi Ali Harefa, Hafid Rahman Hariani, Pipit Putri Hasanuddin Hasanuddin Hasdiana Herman Mawengkang Hutagalung , Fatma Sari Hutagalung, Fatma Sari Ichsan, Aulia Idham Kamil Ilham Ramadhan Nasution Indah Purnama Sari Indah Purnama Sari Indah Purnama Sari Indah Purnama Sari Irvan, Irvan Ismail Hanif Batubara Julham Julham Julham Julham Lubis, Arif Ridho Lubis, Mhd Muchlisin M. Iqbal Tanjung M.Pd, Akrim Mahyuddin K. M Nasution Mandra Saragih Manurung, Asrar Aspia Marah Doly Nasution Ma’ajid, Farhan Riqi MD, Pipit Putri Hariani Mhd Faris Pratama Mhd. Basri Mhd. Basri Michael J Watts Miftah Fariz Prima Putra Muhammad Basri Muhammad Luthfi Hamzah Muhammad Said Harahap Muharman Lubis Muhathir, Muhathir Muhathir, Muhathir Mulkan Azhari Mulkan Azhari Mulkan Azhari Mutiara Akbar Nasution Nadeak, Nurhalimah Nasution, Tia Alfi Sahara Niken Aprilina Oris Krianto Sulaiman Permatasari, Dhyta Pipit Putri Hariani MD Pradesyah, Riyan Pradesyah, Riyan Prayudani, Santi Putri, Berlianda Oktariani Jelita Putri, Wan Hafizah Ainun Syah Qadri, Habib Al Rahmad B.Y Syah Rahmad Syah Rahmad Syah, Rahmad Rahmat Mushlihuddin Ramadhani, Fanny Romi Fadillah Rahmat Salma, Riza Sarah Purnamawati Sari Hutagalung, Fatma Septiana Dewi Andriana, Septiana Dewi Sibarani, Theofil Tri Saputra Simanungkalit, Ahmad Hazazi Siregar, Ananda Afifah Siregar, Muhammad Rizky Pratama Suherman Suherman Tessya Fakhta Tri Nasution Triantono, Gatot Umi Salamah Vicky Rolanda Wasesa, Istikha Ruchitra Hayudirga Watts, Michael J. Yoshida Sary Yuyun Yusnida Lase Zhafirah, Zhahrah