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Impact of Coal Washing Activities on Water Quality and The Community of Aquatic Life In The Barito River, South Barito Regency Gianina, Lovina; Fitri Purwanti, Ipung
International Journal of Science and Environment (IJSE) Vol. 5 No. 4 (2025): November 2025
Publisher : CV. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51601/ijse.v5i4.257

Abstract

The Barito River is a recipient of pollution from various human activities such as agriculture, settlements, and especially the mining industry. Coal washing activities along the Barito River Basin (DAS) are one of the activities that have the most significant impact on water quality degradation. This research aims to analyze the impact of coal washing activities on water quality and aquatic biota communities in the Barito River, South Barito Regency. The research location is the Barito River, South Barito Regency. Sampling points were taken at three points: upstream, outfall, and downstream of the Barito River. Water quality parameters in the Barito River include physical aspects (temperature and TSS), chemical (DO, pH, Fe, and Mn), and biological (nekton, plankton, and benthos) measured using the SNI method and specific fishing gear. Water quality assessment was carried out using the Storet method and the Pollution Index (IP) to determine water quality status based on parameters that do not meet quality standards. The water quality of the Barito River is classified as lightly to moderately polluted. Most physicochemical parameters are still within quality standards, except for low DO and Mn at several points exceeding the threshold. Storet results showed a score of -10 (class B, light pollution), while the Pollution Index (IP) was 1.98 (light pollution). Coal washing activities affected the distribution of aquatic biota. The diversity index (H’) of nekton was moderate-high (2.64–3.17), plankton was moderate (1.70–2.06), and benthos was low (0.64–0.69). High evenness and low dominance values ​​indicated a relatively stable community, despite anthropogenic pressures. The presence of bioindicators such as Rasbora caudimaculata, Macrobrachium rosenbergii, and Bithynia sp. confirmed the influence of human activities on the ecosystem.
Integration of A Web Mdvr Howen Vehicle Surveillance System (Vss) and An Artificial Intelligence Based in Car Camera (Icc) For Fleet Safety PT. Putra Perkasa Abadi Jobsite Adaro Indonesia Gianina, Lovina; Khadafi, Muammer; Farzan, Arizal; Abidin, Zainal
International Journal of Science and Environment (IJSE) Vol. 6 No. 1 (2026): February 2026
Publisher : CV. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51601/ijse.v6i1.288

Abstract

The main technology widely applied is the Vehicle Surveillance System (VSS) Web MDVR Howen, a digital surveillance platform that utilizes Mobile Digital Video Recorder, multi angle cameras, GPS, and AI alarms to monitor vehicle activity in real time. The combination of visual data, AI alarms, and behavioral analytics, this system supports the process of recording, validating, and analyzing events. This AI based integration is in line with the needs of modern industry to improve fleet safety, operational efficiency, and compliance with evidence based safety standards. The research aims to analyze the integration of the VSS Web MDVR Howen system and Artificial Intelligence based In Car Camera (ICC) for fleet safety. This research uses a qualitative descriptive method. VSS Web MDVR Howen and AI based In Car Camera (ICC) are two complementary fleet surveillance technologies to form a comprehensive driving safety system. The integration of the VSS Web MDVR Howen system and Artificial Intelligence based In Car Camera (ICC) has been proven to be able to improve the safety of the PT Putra Perkasa Abadi Jobsite Adaro Indonesia fleet through real time monitoring of vehicle conditions and driver behavior. Data analysis from October–November 2025 showed that this technology effectively detected critical deviations such as fatigue and drowsiness, which are key risks, while maintaining compliance with other aspects such as phone bans and camera closures. AI based monitoring enables rapid intervention, automated alerts, and the provision of accurate data for safety evaluation, helping companies strengthen a safe work culture, improve compliance with SOPs, and significantly reduce the potential for accidents.