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Muhammad Syahriandi Adhantoro
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Jurnal Penelitian Sains Teknologi
Published by Universitas Muhammadiyah Surakarta
ISSN : 14115174     EISSN : 2830067X     DOI : 10.23917/saintek
Core Subject : Science, Engineering,
Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Physics Transportation
Jurnal Penelitian Sains Teknologi is a peer-reviewed scientific journal dedicated to publishing high-quality, original, and methodologically rigorous research in the fields of science and technology. The journal aims to serve as a scholarly forum for the dissemination of theoretical and applied research that advances scientific knowledge, technological innovation, and evidence-based solutions to contemporary challenges. Its scope covers applied science and computational studies, information technology and intelligent systems, engineering and applied technology, as well as the development, evaluation, and implementation of technological models, methods, and systems across various sectors, including education, industry, healthcare, government, energy, and the environment. By emphasizing originality, academic integrity, interdisciplinary perspectives, and ethical research practices, Jurnal Penelitian Sains Teknologi seeks to foster scholarly dialogue, support innovation-driven research, and enhance the impact and visibility of scientific and technological contributions at both national and global levels.
Arjuna Subject : Umum - Umum
Articles 28 Documents
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Black Soldier Fly Bioconversion for Sustainable Organic Waste Management: A Systematic Review and Circular Economy Framework Hakim Garda Patria; Lista Ferlindia Putri Vanisa; Arundia Putri Wimala; Chintiya Fauziah Sulistiyawan; Rahima Laili Agustine; Faridhatun Nikmah; Yasir Sidiq; Siti Hadiyati Nur Hafida; Nour El Houda Alaoui; Dimitra Alexandra Nikolaou
Jurnal Penelitian Sains Teknologi Vol. 3, No 1, January 2027
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/saintek.v3i1.18035

Abstract

Organic waste is a major environmental challenge due to increasing generation and limitations in conventional waste management systems. This study systematically reviews the potential of Black Soldier Fly (BSF) (Hermetia illucens) bioconversion as an integrated approach to sustainable organic waste management. A qualitative systematic literature review was conducted through structured literature searching, screening, data extraction, and thematic synthesis using the PRISMA 2020 framework. The findings indicate that BSF larvae can rapidly reduce organic waste while producing protein-rich larval biomass and nutrient-rich frass. Bioconversion performance is influenced by substrate characteristics, temperature, moisture, aeration, larval density, and operational management. Beyond waste reduction, BSF technology supports resource recovery, alternative feed production, organic fertilizer generation, landfill diversion, and circular economy development. The main contribution of this review is an integrated conceptual framework linking BSF bioconversion with environmental benefits, economic value creation, and sustainable resource management. The findings demonstrate that BSF technology should be considered not merely as a waste treatment method but as an integrated strategy for sustainable organic waste management and circular economy implementation.
Artificial Intelligence as a Virtual Assistant Teacher for Personalized Inclusive Learning: A Systematic Literature Review and Human AI Collaboration Framework for Indonesia Rahayu Febri Riyanti; Alya Al Izzati Rofidah; Nabila Nurfianda; Azizah Nur Fadilah; Altra Slashearly Ryanlista Firstly; Siti Fatimah Nur Lidini Salamah; Valeria Isabel Navarro; Charlotte Marie Janssens
Jurnal Penelitian Sains Teknologi Vol. 3, No 1, January 2027
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/saintek.v3i1.18366

Abstract

The advancements in Artificial Intelligence (AI) have significantly influenced various sectors, including education. In recent years, the implementation of AI has demonstrated a remarkably substantial increase. Conversely, only approximately 30% of inclusive schools in Indonesia utilize adaptive technology. This condition necessitates serious consideration regarding the role of AI as a virtual assistant teacher in personalizing inclusive learning. This study aims to analyze the role of AI as a virtual assistant teacher in personalizing inclusive learning, assess its impact on student engagement, and identify the challenges and integration of AI in education. Employing a qualitative approach, this study conducts a literature review of 35 scientific articles published between 2021 and 2026. The findings indicate that AI can function as a virtual assistant to support inclusive learning that is more interactive, adaptive, and effective in enhancing the engagement of students with special needs. With appropriate policy support, the integration of AI and human educators can serve as a progressive step toward improving the quality of inclusive education in the future.
Atmospheric Microplastic Pollution in Jakarta: Environmental Impacts, Human Health Implications, and Integrated Management Strategies Zidane Surya Pratama; Fahri Rozani Ardiansyah; Farhana Cahya Apriliya; Denissa Anindya Wardani Prasetyo; Kesya Agung Ariellintang; Dzaky Alhafizh Arseno; Faridhatun Nikmah; Sofyan Anif; Savenaca Jone Viliame; Noah Malek Vira; Phan Anh Dũng
Jurnal Penelitian Sains Teknologi Vol. 3, No 1, January 2027
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/saintek.v3i1.18474

Abstract

Pollution microplastics has develop become threat global environment that is not only pollute ecosystem sea and land, but also the atmosphere. In matter This show that Jakarta recorded level contamination microplastics highest in rainwater compared to a number of other regions in Indonesia, indicating existence cycle pollution increasingly plastic​ complex through track air and precipitation. This study aimfor analyze source pollution, level contamination, as well as impact ecological and health from deposited microplastics​ through rainwater in urban areas dense high. Research This arranged use approach qualitative descriptive research​ this is studies literature with study various secondary data sources that originate from from journal scientific, articles scientific, institutions research, books, and publication relevant official​ with topic pollution microplastics atmospheric. Findings from various source show that rainwater​ no Again can categorized as a completely media clean, but potential become vector distribution pollutant dangerous to land, water bodies, and bodies human impact​ term identified length​ covers disturbance health system breathing, risk toxicity, as well as degradation ecosystem urban. Conditions This confirm urgency implementation policy restrictions plastic very use, repair governance system​ more waste​ effective, and improvement literacy public to threat microplastics atmospheric. With Thus, the phenomenon Rain microplastics in Jakarta are warning Serious that crisis pollution plastic has enter phase new ones that require response multidisciplinary and sustainable.
Artificial Intelligence in Smart Waste Management: International Applications, Challenges, and Opportunities for Indonesia Abdullah Muhammad Rotibbul Haddad; Yaoxiang Mei Olivia; Liao Hong-Yuan Mark; Huang An-Ning
Jurnal Penelitian Sains Teknologi Vol. 3, No 1, January 2027
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/saintek.v3i1.18999

Abstract

Indonesia faces significant waste management challenges due to the high volume of unmanaged waste, inefficient sorting, and continued reliance on conventional disposal practices. This study aims to examine the role and implementation of Artificial Intelligence (AI) in waste sorting and management and its potential application in Indonesia. A Narrative Literature Review (NLR) was conducted by analyzing relevant studies obtained through Google Scholar using keywords related to AI, waste management, computer vision, and waste classification. The findings indicate that AI has been applied to automated waste identification, classification, real-time detection, monitoring, and robotic sorting. Applications of computer vision, deep learning, object detection, and robotic systems demonstrate potential to improve sorting accuracy, processing speed, operational efficiency, and recycling. Comparative evidence from Bangladesh, Vietnam, India, Russia, and the United Kingdom shows diverse approaches to AI-based waste management. For Indonesia, AI adoption should be adapted to local waste characteristics, infrastructure, datasets, and human resource capacity. A gradual integration of AI with digital infrastructure and automated systems can support more efficient and sustainable waste management.
Valorization of Crab Shell Waste into Onion Sticks: Physicochemical Characteristics and Sensory Acceptance of Soft-Shell Crab and Blue Swimming Crab Shell Flours Santosa Pradana Putra Setya Negara; Dicky Pratama; Putri Balqis Al Kubro
Jurnal Penelitian Sains Teknologi Vol. 1 No. 2 (2025)
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/saintek.v1i2.19790

Abstract

Crab shell waste is an abundant fisheries by-product that remains underutilized despite its potential as a source of minerals and other valuable components. This study aimed to evaluate the physicochemical characteristics and sensory acceptance of onion sticks formulated with different types of crab shell flour. A Completely Randomized Design was applied using four treatments: control, soft-shell crab (Scylla serrata) shell flour, blue swimming crab (Portunus pelagicus) shell flour, and a mixture of both shell flours, with three replications. Analyses included moisture content, ash content, instrumental color (L*, a*, and b*), descriptive sensory evaluation by eight trained panelists, and hedonic testing by 50 untrained panelists. Data were analyzed using ANOVA followed by Duncan’s Multiple Range Test at a 5% significance level. Crab shell flour increased the ash content and modified the color characteristics of the onion sticks while enhancing crab-related aroma and flavor. Although shell flour increased the perception of sandy texture, crispness remained relatively stable across treatments. The hedonic evaluation showed that the soft-shell crab treatment achieved overall acceptance comparable to the control and exhibited a more favorable sensory profile than the blue swimming crab treatment. These findings indicate that soft-shell crab shell flour has potential as a value-added ingredient for onion stick production and as an alternative approach for utilizing crab shell waste.
Determinan Sosial Perilaku Pencegahan Demam Berdarah Dengue: Peran Pendidikan, Pengetahuan, dan Modal Sosial di Kabupaten Pati Rhavida Anniza Andyani; Galih Wiratmoko; Muhammad Hasan Al Banna
Jurnal Penelitian Sains Teknologi Vol. 1 No. 2 (2025)
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/saintek.v1i2.19795

Abstract

Dengue Hemorrhagic Fever (DHF) remains a public health problem in Indonesia, including Pati Regency. This study aimed to analyze factors associated with preventive and control behaviors against DHF. An observational analytic study with a case-control design was conducted among 225 participants selected using simple random sampling. Data were collected using questionnaires and analyzed using logistic regression with STATA 13. The results showed that 52.0% of participants had poor DHF prevention behavior. Higher education was significantly associated with better prevention behavior (p = 0.040; OR = 2.36), as were good knowledge (p = 0.036; OR = 2.36) and strong social capital (p = 0.019; OR = 2.92). Social capital demonstrated the strongest association with DHF prevention behavior. Therefore, DHF control strategies should integrate improvements in education and health knowledge with strengthened social capital and community participation in implementing the 3M Plus approach.
Rainfall Variability and Rice Production under Climate Change: Empirical Evidence and Climate-Smart Adaptation in Bogor Regency, Indonesia Santosa Pradana Putra Setya Negara; Rhavida Anniza Andyani; Ni Putu Vida Indriani; Akmil Asril; Lucas Nathaniel Tan; Lucas Adrian Lee; Somsak Phommasone
Jurnal Penelitian Sains Teknologi Vol. 3, No 1, January 2027
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/saintek.v3i1.19831

Abstract

Climate variability poses a growing challenge to rice production in Indonesia due to changes in rainfall patterns, water availability, and the increasing occurrence of extreme climatic events. This study aims to examine the relationship between rainfall variability and rice production and to identify climate-adaptation strategies for strengthening agricultural resilience. A qualitative approach combining a Systematic Literature Review (SLR), comparative analysis, and secondary-data analysis was employed. The literature review followed the PRISMA 2020 framework and synthesized 30 selected scientific studies, including three key studies used as principal synthesis sources. Secondary data on annual rainfall, ENSO conditions, harvested area, and rice production in Bogor Regency were analyzed for the 2018–2024 period.
Edge-Assisted Multi-Agent Reinforcement Learning for Decentralized Autonomous Swarm Drone Navigation under Bandwidth Constraints Lina Amira Becker; Aisha Lena Müller; Freya Amina Hansen; Aisha Laila Jørgensen; Oscar Yusuf Pedersen; Jakub Ali Wisniewski; Maja Hana Kaczmarek
Jurnal Penelitian Sains Teknologi Vol. 3, No 1, January 2027
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/saintek.v3i1.20053

Abstract

Decentralized navigation and inter-agent communication are key requirements for the safety of UAV swarms. However, restricted communication bandwidth will limit the exchange of information, thus lowering the level of coordination, the collision probability, and even affect navigation. In this study, we have designed an Edge-Assisted Multi-Agent Reinforcement Learning (EA-MARL) framework for decentralized autonomous swarm drone navigation under bandwidth constraints. The design consists of decentralized policy implementation, edge-assisted learning, and bandwidth aware communication where the communication bandwidth is explicitly considered during the process of navigation learning. The effectiveness of the designed framework has been tested under various bandwidths and has been compared with existing reinforcement learning frameworks. According to the expected results, our framework performs with a success rate of 96.1%, a collision rate of 2.8%, an average path length of 107.6 units and an average reward of 93.5. When the bandwidth drops from 100 Mbps to 25 Mbps, the communication overhead will reduce from 18.5 MB to 10.7 MB per episode with a drop of 42.2%, while the navigation success still maintains 89.6%. Through ablation analysis, it could be found that edge assistance, bandwidth aware communication, and selective information exchange all contribute to the better performance of navigation and training convergence.

Page 3 of 3 | Total Record : 28

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