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All Journal ComEngApp : Computer Engineering and Applications Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) TEKNIK INFORMATIKA Teknika Jurnal Teliska Proceedings of KNASTIK Elkom: Jurnal Elektronika dan Komputer PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Prosiding SNATIF Teknika: Jurnal Sains dan Teknologi Annual Research Seminar SMATIKA Jurnal Ampere Proceeding of the Electrical Engineering Computer Science and Informatics PROtek : Jurnal Ilmiah Teknik Elektro Jurnal Informatika Upgris Tech-E International Journal of Artificial Intelligence Research JURNAL MEDIA INFORMATIKA BUDIDARMA VOLT : Jurnal Ilmiah Pendidikan Teknik Elektro Indonesian Journal of Artificial Intelligence and Data Mining JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal TIPS : Jurnal Teknologi Informasi dan Komputer Politeknik Sekayu Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal RESISTOR (Rekayasa Sistem Komputer) Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Qua Teknika Jurnal Fokus Elektroda : Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali Jurnal Teknologi Informasi dan Pendidikan Building of Informatics, Technology and Science Jurnal Informatika dan Rekayasa Elektronik bit-Tech Indonesian Journal of Electrical Engineering and Computer Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) International Journal of Advances in Data and Information Systems Jurnal Teknik Informatika (JUTIF) Fokus Elektroda: Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali) Advance Sustainable Science, Engineering and Technology (ASSET) Aptekmas : Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat Bangsa Enrichment: Journal of Multidisciplinary Research and Development Prosiding Seminar Hasil Penelitian dan Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat Sultan Indonesia Journal of Environment and Sustainability Education JEPEmas: Jurnal Pengabdian Masyarakat (Bidang Ekonomi) Jurnal Pengabdian Masyarakat Mentari
Ade Silvia Handayani
Politeknik Negeri Sriwijaya
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Journal : ComEngApp : Computer Engineering and Applications Journal

 1 
Environmental Application with Multi Sensor Network Ade Silvia Handayani; Nyayu Latifah Husni; Rosmalinda Permatasari
Computer Engineering and Applications Journal Vol 9 No 1 (2020)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (459.163 KB) | DOI: 10.18495/comengapp.v9i1.322

Abstract

This paper aimed to monitor temperature, humidity, and CO gas level using environmental application with multi sensor network (MSN). This system was applied in real life and real time, to be able to obtain data and information through mobile devices and other on internet network. In this research, environmental application is monitored remotely using displays on the web and sensors as device. This research obtained data in outdoor and indoor parking area also with obstacles and without obstacles, so it obtained the results from each of the different environmental conditions.
Real Time Garbage Bin Capacity Monitoring Nyayu Husni Latifah; Sitangsu Sitangsu; Sabilal Rasyad; Ade Silvia Handayani
Computer Engineering and Applications Journal Vol 9 No 2 (2020)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (246.845 KB) | DOI: 10.18495/comengapp.v9i2.340

Abstract

This paper discusses about a garbage bin that can be monitored in real time. The information of the garbage capacity can be obtained in the application that is integrated in the mobile phone. The communication between the garbage bin and the mobile phone is intended to help the garbage collector and the user to monitor the capacity of the garbage in a garbage bin. When it has been overloaded, the collector can manage the garbage by moving the garbage to the other bigger garbage bin. (landfill). This garbage bin has been tested and it could run well. It could open and close its cover as soon as it detected or did not detect the objects. It could also send the information of the garbage capacity to the mobile phone immediately with delay only 0.45-0.47 s.
Air Quality Classification Using Support Vector Machine Ade Silvia Handayani; Sopian Soim; Theresia Enim Agusdi; Nyayu Latifah Husni
Computer Engineering and Applications Journal Vol 10 No 1 (2021)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (381.677 KB) | DOI: 10.18495/comengapp.v10i1.350

Abstract

Air pollution in Indonesia, especially in urban areas, becomes a serious problem that needs attention. The air pollution will impact on the environment and health. In this research, the air quality will be classified using Support Vector Machine method that obtained from the sensor readings. The sensors used in the detection of CO, CO2, HC, dust/PM10 and temperature, namely TGS-2442, TGS-2611, MG-811, GP2Y1010AU0F and DHT-11. After testing, the results obtained with classification accuracy of 95.02%. The conclusion of this research indicates that the classification using the Support Vector Machine has the ability to classify air quality data.
Wireless Controlling for Garbage Robot (G-Bot) Nyayu Latifah Husni; Robi Robi; Ekawati Prihatini; Ade Silvia Handayani; Sabilal Rasyad; Firdaus Firdaus
Computer Engineering and Applications Journal Vol 10 No 2 (2021)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (719.313 KB) | DOI: 10.18495/comengapp.v10i2.376

Abstract

This paper presents one of the solutions in overcoming the garbage problems. The people sometimes feel too lazy to throw the garbage into proper place due to their habit that has been grown since little kids. In this research, A G-Bot, a robot that has function as the garbage container is offered. By using an Internet of Things (IoT) application, the users can control the motion of the G-Bot wirelessly, so that it can move to the users’ desired location. In addition, the covers of the G-Bot can also be opened using smart phones that connected to the G-Bot. A Blynk that acts as the IoT Application is used in order to set up the G-Bot communication. From the experimental result, it can be concluded that the proposed research has been successful to be implemented. The users can move the G-Bot to the targeted location wirelessly, and they can also open and close the G-Bot’s lids wirelessly trough the mobile phones.
Performance Evaluation on Applied Low-Cost Multi-Sensor Technology in Air Pollution Monitoring Ade Silvia Handayani; Nyayu Latifah Husni
Computer Engineering and Applications Journal Vol 11 No 3 (2022)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (449.773 KB) | DOI: 10.18495/comengapp.v11i3.401

Abstract

This research aims to discuss the application of multi-sensor network technology for the monitoring of indoor air pollution. Indoor air pollution has become a severe problem that affects public health, especially indoor parking. The indoor air pollution monitoring system will provide information about vehicle exhaust emission levels. We have improved the system to identify six parameters of the vehicles' gas emissions within a different location at once. This research aimed to measure the parameter of Carbon Monoxide (CO), Carbon Dioxide (CO2), Hydro Carbon (HC), temperature and humidity, and levels of particulates in the air (PM10). The performance of this system shows good ability to compare the results of measurements of air quality measuring professionals. In this study, we investigated the performance of a custom-built prototype developed under the android-based application to detect air pollution levels in the parking area. Our objective was to evaluate the suitability of a low-cost multi-sensor network for monitoring air pollution in parking and the other area. The benefit of our approach is that its time and space complexity make it valuable and efficient for real-time monitoring of air pollution.
Littering Activities Monitoring using Image Processing Nyayu Latifah Husni; Ade Silvia Handayani
Computer Engineering and Applications Journal Vol 12 No 3 (2023)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/comengapp.v12i3.427

Abstract

Littering is a human behavior that become a habit since childhood. Even though there are rules that prohibit this behavior, the community still continues to do so. In order to limit this bad behavior, a device that can monitor and provide notifications is needed. In this research, a device is offered that can identify human activities in real time using webcam-based image processing. Then, it is processed by machine learning using the Recurrent Neural Network (RNN). The monitoring device produced in this research works by comparing the captured image data with a dataset. The captured image data will then be extracted features and form several coordinate points on the human body, then the system will classify these human activities into the category of normal activities or littering activities. This device will provide an output in the form of a warning every time the activity of littering is detected.
Development of a Littering Behavior Detection Using 3D Convolutional Neural Networks (3D CNN) Husni, Nyayu Latifah; Prihatini, Ekawati; Ulandari, Monica; Handayani, Ade Silvia
Computer Engineering and Applications Journal Vol 14 No 1 (2025)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/comengapp.v14i1.1246

Abstract

Littering has become a significant problem that negatively impacts public health and environmental cleanliness. This research introduces an innovative solution using 3D Convolutional Neural Networks (3D CNN) technology to automatically detect littering behavior through real-time CCTV recordings. Two models were developed and tested. Model 1, which employs Conv3D, Batch Normalization, and Dropout, showed high training accuracy but exhibited fluctuations in validation accuracy, indicating potential overfitting. In contrast, Model 2, designed with a simpler structure without Batch Normalization and Dropout, achieved higher classification accuracy and efficiency. Both models significantly contribute to addressing littering in public areas, increasing awareness, and supporting environmental law enforcement. The integration of 3D CNN technology in detecting littering behavior demonstrates its potential to reduce pollution and promote environmentally responsible behavior.
Performance Evaluation on Applied Low-Cost Multi-Sensor Technology in Air Pollution Monitoring Handayani, Ade Silvia; Husni, Nyayu Latifah; Permatasari, Rosmalinda
Computer Engineering and Applications Journal (ComEngApp) Vol. 11 No. 3 (2022)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research aims to discuss the application of multi-sensor network technology for the monitoring of indoor air pollution. Indoor air pollution has become a severe problem that affects public health, especially indoor parking. The indoor air pollution monitoring system will provide information about vehicle exhaust emission levels. We have improved the system to identify six parameters of the vehicles' gas emissions within a different location at once. This research aimed to measure the parameter of Carbon Monoxide (CO), Carbon Dioxide (CO2), Hydro Carbon (HC), temperature and humidity, and levels of particulates in the air (PM10). The performance of this system shows good ability to compare the results of measurements of air quality measuring professionals. In this study, we investigated the performance of a custombuilt prototype developed under the android-based application to detect air pollution levels in the parking area. Our objective was to evaluate the suitability of a low-cost multi-sensor network for monitoring air pollution in parking and the other area. The benefit of our approach is that its time and space complexity make it valuable and efficient for real-time monitoring of air pollution.
Littering Activities Monitoring using Image Processing Husni, Nyayu Latifah; Handayani, Ade Silvia; Passarella, Rossi; Abdurrahman; Rahman, A.; Felia, Okta
Computer Engineering and Applications Journal (ComEngApp) Vol. 12 No. 3 (2023)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Littering is a human behavior that become a habit since childhood. Even though there are rules that prohibit this behavior, the community still continues to do so. In order to limit this bad behavior, a device that can monitor and provide notifications is needed. In this research, proposed device can identify human activities by utilizing webcam-based image processing. It is processed by machine learning using the Recurrent Neural Network (RNN). The monitoring device produced in this research works by comparing the captured image data with dataset. The captured image data are extracted into figures and form several coordinate points on the human body. Then, the system classifies the human activities into two categories, i.e., normal or littering. This device will provide an output in the form of a ewarning every time the activity of littering is detected.
Development of a Littering Behavior Detection Using 3D Convolutional Neural Networks (3D CNN) Husni, Nyayu Latifah; Prihatini, Ekawati; Ulandari, Monica; Handayani, Ade Silvia
Computer Engineering and Applications Journal (ComEngApp) Vol. 14 No. 1 (2025)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Littering has become a significant problem that negatively impacts public health and environmental cleanliness. This research introduces an innovative solution using 3D Convolutional Neural Networks (3D CNN) technology to automatically detect littering behavior through real-time CCTV recordings. Two models were developed and tested. Model 1, which employs Conv3D, Batch Normalization, and Dropout, showed high training accuracy but exhibited fluctuations in validation accuracy, indicating potential overfitting. In contrast, Model 2, designed with a simpler structure without Batch Normalization and Dropout, achieved higher classification accuracy and efficiency. Both models significantly contribute to addressing littering in public areas, increasing awareness, and supporting environmental law enforcement. The integration of 3D CNN technology in detecting littering behavior demonstrates its potential to reduce pollution and promote environmentally responsible behavior.
Co-Authors A. Rahman AA Sudharmawan, AA Aan Sugiyanto Abdul Rakhman Abdurahman Abdurrahman Abu Hasan Aditya, M Rizky Vira Afifah, Luthfia Afiifa Aaliyah Maharani Agung, Muhammad Zakuan Ahmad Taqwa Ahmad Taqwa Al Fatur Sayid Al-Kausar, Jefri Albertia Youlanda Alfarizal, Niksen Ali Nurdin Ali Nurdin Ali Nurdin Alquratu SeptriaPS, Annies Amperawan Amperawan Andry Meylani Angguna, Welan Mauli Anisah Fadhilah Arinaullah, Nabiel Aryanti Aryanti Asriyadi Asriyadi Aswarisman, Novie Rahmadani Auditra Faza Amira Az-zahra, Maudhy Banu Putri Pratiwi Br Ginting, Nurul Devani Btari Puspa Yahya C. Ciksadan Carlos R Sitompul Ciksadan Ciksadan Ciksadan, Ciksadan Destra Andika Destra Andika Pratama Devi Indah Pujiana Dewi, Tresna Dody Novriansyah DWI RAMADHANI Dzikrillah, Muhammad Ekawati Prihatini Ekawati Prihatini Elisa Islami Putri Emilia Hesti Endri, Jon Endri, Jon Enri, Jon Evelina Evelina Evelina Evelina Evelina, Evelina Faisal Damsi Farid Jatri Abiyyu Faris, Fakhri Al Farozi, Ahmad Felia, Okta Felisia Talitha Aprilia Firdaus Firdaus Hani Marta Putri Harlasyanti, Dewi Ekha Hertani Indah Lestari Hetty Meileni Hj. Lindawati Husni, Nyayu Latifah Ibnu Ziad, Ibnu Ihsan Mustaqiim Inayah, Cantika Tri Irawan Hadi Irawan Hadi Irdayanti, Yeni Irma Salamah Irsyadi Yani Iryadi Yani Iryadi Yani, Iryadi Iskandar Lutfi Jon Endri Kaila, Afifah Syifah Kinasih, Ayu Antika Sekar Kurniawan, M Lutfi Leni Novianti Linda Wati Lindawati Lindawati M Arief Rahman M. Ardiansyah M. Ilham Akbar M. Sobri Maharani, Ullya Dwi Mardiani, Mega Marieska Lupikawaty Martinus Mujur Rose Masayu Anisah Maysya Ayu, Ghina Medina Nadila Prima Putri Mega Hasanul Huda Meranda, Arganda Meutia Deli Rachmawati Mieska Despitasari Moh. Heri Kurniawan Mohammad Fadhli Msy Aulia Hasanah Muhamad Rizki Harahap Nabila, Puspita Aliya Nasron Nasron Nasron Nasron Nofriyanti, Duwi Novriansyah, Dody Nur Agustini Nur Hopipah Nurhajar Anugraha Nyanyu Latifah Husni Nyayu Latifah Nyayu Latifah Husni Nyayu Latifah Husni Nyayu Latifah Husni Nyayu Latifah Husni Nyayu Latifah Husni, Nyayu Latifah Oktariani, Clara Permata Sari, Mira Permatasari, Rosmalinda Plowerita, Sanyyah Pratama, Destra Andika Prihatini, Ekawati Putra, Muhammad Rizki Ganda Putra, Yogie Dwi Putri, Amanda Kanaya Rahman, M Arief Rahman, M. Arief Rakhman, M Arief Rakhman, M.Arief Rasyad, Sabilal Riska Handayani Riswal Hanafi Siregar Rivaldo Arviando Rizkiyanti, Shally Rizky Vira Robi Robi Rosita, Ella Rossi Passarella Rumiasih Rumiasih Rumiasih Rumiasih Rumiasih Rumiasih Sabilal Rasyad Sabilal Rasyad Safitri, Rahmi Dian Salsabillah, Farhah Sanyyah Plowerita Sarjana Sarjana Sarjana, Sarjana Sehatiningsih, Ambar Selamat Muslimin Sinaga, Putri Sitangsu Sitangsu Siti Chodijah Siti Nurmaini Sitompul, Carlos R Sobri, M. Sopian Soim Sopian Soim Sopian Soim, Sopian Sri Chodidjah Sugiyanto, Aan Suroso Suroso Suroso Suroso suzan zefi Syauqiyah, Khansa Ghazalah Taqwa, Ing Ahmad Tarmidi Tarmidi Theresia Enim Agusdi Tresna Dewi Tresna Dewi Ulandari, Monica Wahyu Caesarendra Wahyuni, Devi Widya, Afni Rara Wildan Putra Pratama Wirayudha, Ikhwan Adhi Yani, Iryadi Yeni Irdayanti Yudi Wijanarko