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SOSIALISASI DAN PELATIHAN PENGGUNAAN MESIN PEMBERI PAKAN IKAN TAWAR OTOMATIS BERBASIS IoT DI KOLONG BEKAS PENAMBANGAN TIMAH DI KABUPATEN BANGKA Sulistyo, Eko; Dwisaputra, Indra; Ocsirendi, Ocsirendi; Tumatul Ainin, Dewi; Buulolo, Martinus; Juanda, Juanda; Ramli, Ramli
Jurnal Pengabdian Masyarakat Polmanbabel Vol. 5 No. 02 (2025): DULANG : Jurnal Pengabdian Kepada Masyarakat
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33504/dulang.v5i02.697

Abstract

This community service activity aims to improve the efficiency and productivity of freshwater fish farming in former tin mining pits through the socialization and training on the use of Internet of Things (IoT)-based automatic feeding machines. The activity was carried out in Bangka Regency and involved 20 local fish farmers who had previously relied on manual feeding methods. The program began with an introduction to the concept and benefits of IoT technology in the fisheries sector, followed by theoretical training and hands-on practice using the automatic feeding machine, as well as an evaluation of the training outcomes through pre-tests and post-tests. The evaluation results showed a significant increase in participants' understanding of IoT technology, with an average improvement of 87%, rising from 13% prior to the training. Participants also demonstrated better comprehension of how the automatic machine works and enhanced their ability to operate it independently. The IoT-based automatic feeding machine has proven effective in increasing time efficiency, reducing feed waste, and enabling remote monitoring via mobile devices. This community service initiative is expected to be a starting point for technological transformation in aquaculture practices in post-mining areas, moving towards a more modern, productive, and sustainable system.
Maximum Power Point Tracking (MPPT) pada Solar Panel Ardhita, Maya; Liana, Valencia; Setiawan, I Made Andik; Ocsirendi, Ocsirendi
Jurnal Inovasi Teknologi Terapan Vol. 3 No. 2 (2025): Jurnal Inovasi Teknologi Terapan
Publisher : Politeknik Manufaktur Negeri Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33504/jitt.v3i2.281

Abstract

The increasing demand for electricity encourages the utilization of renewable energy such as solar panels. However, solar electricity production faces efficiency challenges as the panel output is highly dependent on light intensity and ambient temperature. This test aims to optimize the output power of solar panels using Maximum Power Point Tracking (MPPT) with Perturb and Observe (PO) method and light sensor-based prediction (LDR). The test was conducted using 100 Wp monocrystal solar panel with MPPT algorithm implemented through buck-boost converter and controlled by Arduino Mega 2560. The results showed that the MPPT system increased the output power efficiency by 16.13% compared to the non-MPPT system. Variation of light intensity from 0 to 10,400 lux resulted in an increase in voltage from 1.15V to 25V, with maximum power increasing from 0.023W to 13W, reaching an average of 800 LUX/W. Characterization of LDR resulted in a conversion factor of 7,761.194 LUX/LDR, enabling accurate prediction of MPPT values based on light intensity. Comparative analysis between the LDR and PO methods showed the LDR method reached a maximum power of 11.62W at 9,293.71 lux, while the PO method reached 12.51W at 8,500 lux, indicating comparable performance in optimizing solar panel output power.
Penerapan Pembangkit Listrik Tenaga Angin Untuk Penerangan Lampu Jalan Dipesisir Pantai Teluk Uber Secara Otomatis Berbasis IoT Azharry, Deni; Maulina, Firly; Sulistyo, Eko; Ocsirendi, Ocsirendi
Jurnal Inovasi Teknologi Terapan Vol. 3 No. 2 (2025): Jurnal Inovasi Teknologi Terapan
Publisher : Politeknik Manufaktur Negeri Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33504/jitt.v3i2.317

Abstract

Renewable energy, particularly wind power, offers a relevant solution to address climate change challenges and the growing electricity demand, especially in coastal areas such as Pantai Teluk Uber, Bangka Belitung. This study develops a Wind Power Generation System (PLTB) based on the Internet of Things (IoT) for real-time monitoring via smartphones. The system utilizes a wind turbine equipped with an anemometer sensor for wind speed, an INA219 sensor for monitoring current and voltage, and a BH1750 sensor for measuring light intensity. The collected data is transmitted to an IoT platform for remote monitoring. Additionally, the system was tested for battery charging and discharging, with charging requiring approximately 8 hours at an average current of 1 A, and discharging lasting around 10 hours with a 12V 10W DC lamp load. The maximum power generated by the system is 6.73 watts at a wind speed of 9 m/s, while the minimum power recorded is 0.35 watts at a wind speed of 2 m/s. The results show that the IoT-based PLTB system can efficiently provide energy for nighttime lighting and other applications.
Sistem Proteksi Dan Kontrol Pada Sensor Motor Menggunakan Face Rcognition Pratama, Bagas; Savitri, Karlin; Sulistyo, Eko; Ocsirendi, Ocsirendi
Jurnal Inovasi Teknologi Terapan Vol. 3 No. 2 (2025): Jurnal Inovasi Teknologi Terapan
Publisher : Politeknik Manufaktur Negeri Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33504/jitt.v3i2.328

Abstract

A motorcycle protection system based on Face Recognition was developed to improve security and prevent theft. This system combines protection key technology with a real-time location tracking feature connected via an Android application. NodeMCU is used as the main controller that integrates the GPS module to obtain motorcycle location data, while Firebase functions as a storage and processor of location data displayed on the application. This system is designed to control motorcycle electricity, including turning the motorcycle on and off via the application, while monitoring the location of the motorcycle with high accuracy. Testing was carried out to assess the function of key protection and motorcycle location tracking. The system has proven to have a fast response time and is reliable in controlling motorcycle electricity, both for one unit and several motorcycle units at once. Location tracking testing showed a success rate of 99% with a very low error of 0.0003%, while the data displayed on the application and Firebase has an accuracy of 100%. The results of the study show that this system can replace manual ignition with a better level of security. In addition, the location tracking feature provides additional benefits for users to monitor the position of the motorcycle in real time with accurate and reliable data.
Rancang Bangun Sistem Pemberi Pakan Ikan di Kolong Bekas Tambang Timah Secara Otomatis Berbasis IoT Ocsirendi, Ocsirendi; Sulistyo, Eko; Dwisaputra, Indra; Ainin, Dewi Tumatul; Susanto, Dedi; Ramli, Ramli
Manutech : Jurnal Teknologi Manufaktur Vol. 17 No. 02 (2025): Manutech: Jurnal Teknologi Manufaktur
Publisher : Politeknik Manufaktur Negeri Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33504/manutech.v17i02.671

Abstract

This study aims to design and develop an automatic fish feeding system based on the Internet of Things (IoT) that can be applied in former tin mining pits in Bangka Belitung. The system is expected to improve feeding efficiency and reduce dependence on manual labor. The research method includes hardware design using a NodeMCU ESP32 microcontroller, a servo motor as the feed dispensing actuator, and an RTC module as the time controller. The system is equipped with a web-based IoT application for remote control and monitoring. Testing was carried out at a fish farming site located in a former mining pond, with observations on feeding schedule accuracy, feed throwing distance, and feed usage efficiency. The results showed that the system achieved 100% accuracy in feed timing based on RTC sensor readings. Feed output during multiple feeder motor rotations was stable, with an error rate of less than 1%. The pellet throwing distance at 90% motor speed reached a maximum of 6.6 meters and a minimum of 2.4 meters.The system can also be controlled remotely via the web, allowing users to schedule feeding times and monitor device status in real time from a smartphone or computer. This system has proven to be effective and feasible for freshwater fish farming in post-mining areas, supporting sustainable aquaculture development.
SISTEM CERDAS DIAGNOSA DINI TUBERKULOSIS MENGGUNAKAN NAIVE BAYES DAN CHATBOT AI Afriansyah, Riki; Saputra, Andika; Ocsirendi, Ocsirendi; Sari, Lana; Lanaya, Dela
Technologia : Jurnal Ilmiah Vol 17, No 1 (2026): Technologia (Januari)
Publisher : Universitas Islam Kalimantan Muhammad Arsyad Al Banjari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/tji.v17i1.21223

Abstract

Tuberkulosis (TBC) merupakan salah satu penyakit yang masih menjadi masalah kesehatan utama yang ada di Indonesia, termasuk di Kabupaten Bangka. Keterlambatan diagnosis dan keterbatasan dalam akses konsultasi, turut menjadi hambatan dalam menangani kasus ini. Penelitian ini dilakukan guna mengembangkan sebuah inovasi sistem cerdas diagnosis dini TBC berbasis web yang mengintegrasikan metode Bernoulli Naive Bayes sebagai algoritma, lengkap dengan fitur Chatbot AI sebagai sarana konsultasi. Sistem ini dirancang agar masyarakat dapat melakukan pemeriksaan mandiri secara cepat dan memperoleh informasi awal melalui Chatbot AI yang interaktif. Uji coba model memperlihatkan bahwa sistem berhasil mencapai akurasi 95,24%, dengan tingkat presisi 100%, dan recall 93,33%. Selanjutnya evaluasi kinerja sistem dilakukan melalui metode Blackbox Testing untuk memastikan seluruh fitur berfungsi sesuai dengan rancangan. Dengan hasil tersebut, sistem ini dinilai mampu mendukung proses deteksi dini TBC secara lebih efektif, sekaligus menyediakan layanan konsultasi awal yang mudah diakses oleh masyarakat, khususnya masyarakat yang ada di Kabupaten Bangka.
Co-Authors ., Yudhi Aan Febriansyah Aditya, Decxa Amanda Tia, Tariska Anada, Dea Andhika Dwi Putra ANDIKA SAPUTRA Andini, Dilah Ardhita, Maya Ariansyah Sapta Arrois Syaifullah Athalah Pasha Hafidly Audrey Nugraha, Frizscha Azharry, Deni Bambang Supriyadi catur arief wijaksono Dandi Efendi Dedi Susanto Dewi Tumatul Ainin Dharta, Yuli Dori Oktariandi Dwi Nugroho, Bimo Eko Sulistyo Eko Sulistyo Fadillah, Ilham Fauzan Andika Putra Fauzan, M Nur Fikri Mardianto Fildzah Raazzaq Fitri Annisha, Angelin Gema Azfajri Haikel, M. Zuhriyandi Hera, Hera Indra Dwisaputra Irfan Rahmi Irwan Irwan Islamaya, Adinda Juanda Kartika Magdalena Kunanti, Ananda Kusuma Pradana, Teguh Hari Lanaya, Dela Liana, Valencia Lutfi Toya, Leando M Yunuf Made Andik Setiawan Mahardika Apriliandi, Aldy Martinus Buulolo Maryani Supatria Maulina, Firly Mayati, Iis Meisya Suandari Muhamat Sarwanto Muhammad Erfani Ramadhani Muhammad Fajri Rinaldy Muhammad ifdansyah Muhammad Naufal Almahmudy Ninda Puspita Nofriyani Nofriyani Nova Anggriani Saputri Nur Khasanah Nursabila, Dhava Okta Rina, Tiara Parulian Silalahi Pratama, Bagas Pratama, M. Setya Puput Dwi Wahyuni Rahmadhani, Kiki Patrisia Rama Ramli Ramli Rifqy Adrian Riki Afriansyah Riki Afriansyah Riki Afriansyah Afriansyah Rindy Clarita Rizastiani, Rizastiani Rosidah Safitri, Juliarti Sahrul Ramadhan Salsabilla, Safira Sandika Romadhon Romadhon Santrila, Hafizra Saputra, Gilang Saputra, Gillang Saputro, Ego Wisnu Sari, Lana Savitri, Karlin Selah Sella Amril Sepina, Sepina Setiawan, I Made Andik Silvia Syavira Sindi Anggira Siti Barokah Sopian Arif Sulistiarawati Sunita Handayani Surojo Susianti, Helda Tesah Aldi Parani Tia Fatiha Trihendi Pamungkas Pamungkas Tumatul Ainin, Dewi Vadila, Vadila Wandari, Fitri Wijaya, Sastra Wiwin Sundari Wulandari, Niki Yandi, Misri Yudhi Yuni Setialoka Zanu Saputra