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All Journal Jurnal ULTIMA Computing Jurnal Pensil : Pendidikan Teknik Sipil Vocatech : Vocational Education and Technology Journal J-Sil (Jurnal Teknik Sipil dan Lingkungan)
Rahmawati, Hanifah Indah
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science Mechanical Engineering Transportation Other

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Air Filtration System Utilizing Biomimetic Technology and IoT for Air Quality Improvement Fauzan, Mochamad Rizal; Al Azhima, Silmi Ath Thahirah; Pramudita, Resa; Hakim, Dadang Lukman; Rahmawati, Hanifah Indah; Azmi, Mutiara Nabila; Fauzi, Rafi Rahman; Somantri, Maman; Rahayu, Sri
Ultima Computing : Jurnal Sistem Komputer Vol 16 No 2 (2024): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v16i2.3871

Abstract

The "Hepix" smart air filtration system, developed with biomimetic and Internet of Things (IoT) technology, aims to address the urgent issue of poor indoor air quality, particularly in high-mobility urban areas. This system integrates advanced sensors (MQ135 and BME680) and biomimetic filtration inspired by leaf stomata to monitor and filter air pollutants. Tested across three locations—Cilame, Jatinangor, and Cibiru—the system achieved an approximate 24.4% reduction in pollutant levels, as well as stable control of humidity and air pressure. Real-time data is continuously monitored through a mobile and web interface, supported by Google Assistant integration for voice commands. The results demonstrate that "Hepix" effectively improves air quality, offering a practical solution for healthier indoor environments in urban areas.
MENJELAJAHI BIBLIOSHINY UNTUK MEMETAKAN PENELITIAN ARTIFICIAL INTELLIGENCE DALAM DUNIA PENDIDIKAN Rahmawati, Hanifah Indah; Sabitri, Zenita; Azmi, Mutiara Nabila; Meirawan, Danny
Jurnal Pensil : Pendidikan Teknik Sipil Vol. 14 No. 2 (2025): Jurnal Pensil : Pendidikan Teknik Sipil
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/jpensil.v14i2.54083

Abstract

This study critically analyzes the development of artificial intelligence (AI) research in education using a bibliometric approach, leveraging data from 191 Scopus-indexed documents during the 2015-2024 period. Employing Biblioshiny software, the study identifies an annual publication growth rate of 44.22% and an average of 11.88 citations per document. The analysis maps five key clusters: AI-based adaptive learning, automated assessment systems, predictive learning analytics, intelligent pedagogical agents, and personalized learning content. Dominant contributions are observed from countries such as the United States, China, and India, supported by substantial international collaboration. The findings also highlight dominant keywords like "Artificial Intelligence" and "Education Technology," reflecting a global research focus. While emphasizing AI's strategic potential in transforming education systems, this study critically underscores ethical and data privacy challenges that require further attention in advancing educational technology.
Utilization of Biomimetic Design on the Design of an Internet of Things-Based Smart Air Purifier in Urban Residences Rahmawati, Hanifah Indah; Meirawan, Danny; Rahayu, Sri; Fauzan, Mochammad Rizal; Azmi, Mutiara Nabila; Fauzi, Rafi Zahran
Jurnal Teknik Sipil dan Lingkungan Vol. 10 No. 2: October 2025
Publisher : Departemen Teknik Sipil dan Lingkungan IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jsil.10.2.239-248

Abstract

Poor air quality in urban areas significantly impacts public health, productivity, and quality of life. Various efforts have been made to address this issue, but many solutions still have limitations, such as low effectiveness, designs that lack portability, and the inability for real time monitoring. This research aims to develop a smart air purifier based on biomimetics and the Internet of Things (IoT) as an innovative solution to improve air quality in urban residences. The device prototype mimics the mechanism of leaf stomata, which naturally regulate the flow of air and gases, thus enabling more optimal clean air circulation. The system can monitor environmental parameters, namely temperature, humidity, air pressure, and Indoor Air Quality (IAQ) Index, in real time using BME680 and MQ-135 sensors, and can be controlled via Google Assistant. Testing was conducted in three locations in West Java Province, Indonesia: Cilame, Cibiru, and Jatinangor. Linear regression analysis was used to evaluate the relationship between environmental variables and air quality. The results showed that the device was able to significantly improve air quality in all locations, especially in Cilame, with air pressure being the dominant factor affecting IAQ (coefficient of determination 0.88). Different from previous research, this device offers advantages in the form of high portability, real time monitoring, and IoT integration, making it a potential sustainable solution for improving the air quality of urban residences.
Air Filtration System Utilizing Biomimetic Technology and IoT for Air Quality Improvement Fauzan, Mochamad Rizal; Al Azhima, Silmi Ath Thahirah; Pramudita, Resa; Hakim, Dadang Lukman; Rahmawati, Hanifah Indah; Azmi, Mutiara Nabila; Fauzi, Rafi Rahman; Somantri, Maman; Rahayu, Sri
ULTIMA Computing Vol 16 No 2 (2024): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v16i2.3871

Abstract

The "Hepix" smart air filtration system, developed with biomimetic and Internet of Things (IoT) technology, aims to address the urgent issue of poor indoor air quality, particularly in high-mobility urban areas. This system integrates advanced sensors (MQ135 and BME680) and biomimetic filtration inspired by leaf stomata to monitor and filter air pollutants. Tested across three locations”Cilame, Jatinangor, and Cibiru”the system achieved an approximate 24.4% reduction in pollutant levels, as well as stable control of humidity and air pressure. Real-time data is continuously monitored through a mobile and web interface, supported by Google Assistant integration for voice commands. The results demonstrate that "Hepix" effectively improves air quality, offering a practical solution for healthier indoor environments in urban areas.
Pemetaan Kemampuan Mahasiswa Dalam Penulisan Akademik Sebagai Dasar Sistem Pembelajaran Pendidikan Tinggi Berbasis AI Rahayu, Sri; Rahmawati, Hanifah Indah; Ghinaya, Zahra; Meirawan, Danny; Sukadi, Sukadi; Purwanto, Dedi; Iswardhany, Rieske; Sofia, Dewi Ayu; Amin, Rais
VOCATECH: Vocational Education and Technology Journal Vol 7, No 2 (2025): December
Publisher : Akademi Komunitas Negeri Aceh Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38038/vocatech.v7i2.248

Abstract

AbstractRecent advancements in Artificial Intelligence (AI) technology have yet to fully address fundamental challenges in academic writing within the context of higher education. Most existing systems remain focused on surface-level corrections, offering limited support for students struggling to construct logical arguments, organize ideas coherently, and adhere to the structural conventions of academic discourse. This study aims to analyze and map students’ academic writing proficiency as a foundation for developing AI-based learning systems that are responsive to actual needs in higher education. Employing a descriptive quantitative approach, data were collected through a closed-ended online questionnaire distributed via Google Forms. The instrument was designed based on five key dimensions: writing structure, language proficiency, argumentation and logic, referencing, and technical skills, using a 5-point Likert scale. A total of 132 final-year students from various Indonesian universities—particularly those in construction-related disciplines—participated in the study. Contextual analysis was conducted based on study programs, and data validity was enhanced through triangulation. The findings reveal that while most students fall within the “competent” category, notable deficiencies remain in language mastery and logical argumentation, preventing many from reaching a “highly competent” level. These results highlight persistent gaps in academic literacy that necessitate innovative learning interventions. The development of AI-assisted systems capable of delivering both technical and conceptual feedback is therefore essential to improving the quality of student academic writing. Further research is recommended to design an integrated AI-based academic writing platform and to expand the study population across institutions to strengthen the generalizability of the findings. AbstrakSaat ini, kemajuan teknologi Artificial Intelligence (AI) dalam pendidikan tinggi belum sepenuhnya mampu menjawab tantangan mendasar dalam hal penulisan akademik mahasiswa. Banyak sistem yang tersedia masih berfokus pada perbaikan teknis, sementara mahasiswa kerap mengalami kesulitan dalam menyusun argumen logis, mengorganisasi ide secara koheren, dan memahami struktur wacana akademik secara utuh. Penelitian ini bertujuan untuk menganalisis dan memetakan kemampuan menulis akademik mahasiswa sebagai dasar dalam merancang sistem pembelajaran berbasis AI yang relevan dengan kebutuhan aktual di pendidikan tinggi. Metode yang digunakan adalah pendekatan kuantitatif deskriptif melalui penyebaran angket tertutup menggunakan kuesioner daring berbasis Google Form. Instrumen dirancang berdasarkan lima aspek utama: struktur penulisan, penguasaan bahasa, argumentasi dan logika, penggunaan referensi, serta keterampilan teknik, dengan skala Likert 1–5. Responden terdiri atas 132 mahasiswa tingkat akhir dari berbagai perguruan tinggi di Indonesia, khususnya dari rumpun keilmuan teknik konstruksi. Data dianalisis secara kontekstual berdasarkan program studi serta diverifikasi melalui triangulasi untuk meningkatkan validitas hasil. Temuan menunjukkan bahwa sebagian besar mahasiswa berada pada kategori “mampu” dalam menulis akademik, namun belum mencapai kategori “sangat mampu”, terutama pada aspek penguasaan bahasa dan argumentasi logis. Hasil ini mengindikasikan adanya kesenjangan dalam keterampilan literasi akademik yang memerlukan intervensi pembelajaran inovatif. Oleh karena itu, pengembangan sistem pembelajaran berbasis AI yang mampu memberikan umpan balik teknis dan konseptual secara adaptif menjadi penting untuk mendorong peningkatan kualitas penulisan ilmiah mahasiswa. Rekomendasi penelitian lanjutan mencakup pengembangan sistem AI terintegrasi dan perluasan populasi lintas institusi guna memperluas generalisasi hasil.
Co-Authors Al Azhima, Silmi Ath Thahirah Amin Rais Azmi, Mutiara Nabila Dadang Lukman Hakim Danny Meirawan Dedi Purwanto, Dedi Dewi Ayu Sofia Fauzan, Mochamad Rizal Fauzan, Mochammad Rizal Fauzi, Rafi Rahman Fauzi, Rafi Zahran Ghinaya, Zahra Iswardhany, Rieske Maman Somantri Pramudita, Resa Sabitri, Zenita SRI RAHAYU Sukadi Sukadi