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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Abdimas REKAYASA Indonesian Review of Physics (IRiP) Indonesia Berdaya Journal of Novel Engineering Science and Technology
Subrata, Arsyad Cahya
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Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Veterinary Other

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Implementation of Rotary Dryer for Cassava Drying as a Raw Material for Mocaf Flour Production Sudarmini, Sudarmini; Subrata, Arsyad Cahya; Hakika, Dhias Cahya
Jurnal Abdimas Vol 27, No 2 (2023): December 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/abdimas.v27i2.48324

Abstract

Modified cassava flour (mocaf) is one of the innovative cassava processed products with high market value and promising business prospects as a substitute for imported wheat flour. The women's farming group (KWT) Ngudi Sari, located in the village of Tanjungsari, Gunungkidul, has processed cassava into mocaf flour and various cassava-based products, including cassava chips, tiwul, gatot, mocaf sticks, and various cookies. During the production process of mocaf flour, one of the common challenges faced is the drying of cassava chips, which has traditionally relied on sunlight and home-based drying methods. With the increasing demand for mocaf flour, large-scale drying of cassava chips becomes necessary. To address this challenge, a technology of rotary dryer is implemented to KWT Ngudi Sari to enhance the efficiency and effectiveness of the cassava raw material drying process. This outreach project aims to empower KWT Ngudi Sari and boost the production capacity of the resulting mocaf flour. The application of this appropriate technology is expected to improve the quality of cassava as a raw material for mocaf production and enhance its energy efficiency, thus contributing to the economic development of KWT Ngudi Sari. Throughout the project, mentoring, monitoring, and evaluation are also conducted to measure the progress in knowledge and skills of the partners involved.
IoT-based Single-Phase Power Factor and Control Panel Monitoring System Subrata, Arsyad Cahya; Perdana, Muhammad Sukmadika; Ariyansyah, Qolil
Journal of Novel Engineering Science and Technology Vol. 2 No. 01 (2023): Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v2i01.270

Abstract

The power factor is a value obtained by comparing the actual power value and apparent power in an electric circuit. Because it is related to the quality of the distributed power, this power factor needs to be monitored. Devices with inductive loads generally cause power factor distortion, causing losses. Power factor monitoring is carried out periodically to ensure the efficiency of electricity distribution to the building. Power factor monitoring is usually done on the control panel of a building by measuring the voltage and current flowing. Manual monitoring could be more ineffective in terms of time and effort and has the potential for recording errors. This study proposes a power factor monitoring system on the control panel to facilitate recording. The system created is integrated with IoT technology so that it can monitor and record automatically anywhere and anytime. The developed system has an error percentage of 1.53% for the voltage sensor and 5.02% for the current sensor.
Gadingsari maritime village: Empowerment of Gadingsari coastal communities through cultivation saline tilapia fish using biofloc technology Khasanah, Staniya Uswatun; Subrata, Arsyad Cahya; Asephi, M. Yoga; Fadila, Salwa Ayu; Mahdi, Imam; Rahmah, Nur Aisyatul; Kurniaty, Maryani Atikah; Roazah, Qhusnul Fatimatur; Kusprihatini, Sita Alfia; Regina, Sona; Nugraheni, Renada Satya; Ahsan, Fahmi; Haikal, Rayhan Fiqri; Shalihah, Amilatun; Mutmainnah, Fadila Ainil; Mursalin, Ahza Durrani
Indonesia Berdaya Vol 5, No 4 (2024)
Publisher : UKInstitute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47679/ib.2024919

Abstract

The community empowerment program in Gadingsari Village through saline tilapia cultivation with biofloc technology aims to improve the skills and knowledge of the local community. This village has great maritime potential, but challenges related to education levels and lack of employment limit economic development. This program involves socialization, provision of biofloc equipment, distribution of fish seeds, and assistance in fish maintenance until harvest. Biofloc technology was chosen because it can optimize water and nutrient efficiency, and increase the yield of saline tilapia that is resistant to salinity conditions. R/C ratio analysis shows that the Biofloc system with a ratio of 1,38 is more profitable than the conventional system with a ratio of only 1,05. This program has succeeded in introducing new technology, increasing fisheries production, and providing a positive impact on the economic welfare of the local community.
Pond Water Quality Monitoring in Consumption Fish Farming Industry Based on Internet of Things Subrata, Arsyad Cahya; Sulisworo, Dwi; Fitrianawati, Meita; Shafee Kalid, Khairul; Wan Ahmad, Wan Fatimah; Hamdi Batubara, Zul; Ramadhani, Muhammad
Rekayasa Vol 17, No 3: Desember, 2024
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v17i3.25428

Abstract

The rapid increase in population in Indonesia has increased the demand for animal protein. As a source of animal protein, fish has excellent potential to be developed in Indonesia. However, care for water quality, a basic need, is often ignored. Meanwhile, increasing fish production can be done by ensuring that water quality is always in good condition. This research conducted aims to monitor water quality continuously. Integrating water quality monitoring systems using the Internet of Things (IoT) offers convenience in real-time monitoring and does not have to be present on-site. The parameters determining fish water quality are pH, electrical conductivity (EC), dissolved oxygen (DO), turbidity, and water temperature. The data obtained is then displayed on the Water Monitoring dashboard as graphs, indicators, and raw data the user can download. Overall, the system can measure, monitor in real-time, and store data on the results of measuring the quality of freshwater fish ponds on smartphones/laptops. The developed system also provides information on whether the water quality is “normal” or in conditions less and more than the threshold. Therefore, the developed system helps farmers monitor the quality of their fish ponds to increase the productivity of fish farming.
A Preliminary Study on Promoting Contextual Teaching and Learning Using Smart Water Quality Sensors Sulisworo, Dwi; Fitrianawati, Meita; Subrata, Arsyad Cahya; Kalid, Khairul Shafee; Wan Ahmad, Wan Fatimah
Indonesian Review of Physics Vol. 6 No. 1 (2023)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/irip.v6i1.8115

Abstract

Building awareness among students on the issues of natural environmental phenomena has always been a challenge due to the difference in location between the student and the observed phenomena. The issues of the natural environment have been a part of the curriculum in elementary schools. One of the lessons taught on the natural environment in elementary schools is related to the water conditions in various areas filled with water, such as ponds, rivers, lakes, etc. Currently, learning in the natural environment is based on text, images, and videos, and learning activities using real-time data are still rare. This study presents the development of an IoT-based Smart Water Quality application prototype. The prototype consists of conductivity, pH, oxygen levels, salinity, and turbidity sensors. The IoT prototype can also be used to automatically monitor fish, shrimp, and other species in aquaculture ponds. Using the IoT-based Smart Water Quality application prototype, teachers can enhance students' higher-order thinking skills by designing learning activities using real-time data to identify, compare, and classify various concepts or phenomena.
Training for the Randu Alas Batik Group in Processing Batik Waste by Internet of Things Sabila, Liya Yusrina; Amelia, Shinta; Subrata, Arsyad Cahya; Ma'arief, Sandhy Auliya; Fadhilla, Irvanda Cheza Noor; Yasa, Fakhra Kurnia
Indonesia Berdaya Vol 5, No 4 (2024)
Publisher : UKInstitute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47679/ib.2024895

Abstract

The Industrial Revolution 4.0 era has encouraged the integration of Internet of Things (IoT) technology in various sectors, including industrial waste management. This article discusses the implementation of IoT technology for processing batik liquid waste in the Randu Alas Batik Community Group, Mrisi, Tirtonirmolo, Bantul Regency, Yogyakarta. Batik liquid waste, which comes from the processing and dyeing process, contains dangerous chemicals that can increase chemical oxygen demand (COD) values and cause water pollution. This community service activity is carried out through outreach, training, and practice in using IoT-based waste processing equipment, which aims to increase community knowledge and skills in managing waste effectively and sustainably. The evaluation results show a significant increase in understanding and application of IoT, reflected in the pretest and post-test results. The conclusion of this activity shows that IoT technology effectively improves the quality of batik waste management and has great potential to be widely applied to maintain environmental sustainability.
Empowerment of Cassava Leaf Silkworm Cultivation Groups Through Processing of Ceara Rubber Tree (Manihot Glaziovii) as Local Food Potential Subrata, Arsyad Cahya; Ibdal, Ibdal; Sudarmini, Sudarmini; Suharto, Totok Eka; Putranti, Deslaely; Rahmawan, Jihad; Aska, Ghoniyun Nisa Uskhulil; Hidayah, Laelatul
Indonesia Berdaya Vol 6, No 3 (2025)
Publisher : UKInstitute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47679/ib.20251170

Abstract

Food security has become an increasingly urgent global issue as the impact of climate change and the global food crisis intensify. Indonesia, as an agrarian country, has great potential to strengthen its food system to be self-sufficient and sustainable, one of which is through the empowerment of local farmer groups. This article discusses efforts to enhance food security through agricultural product diversification by leveraging untapped local potential, specifically the processing of rubber tree (Manihot glaziovii) tuber skins. Empowerment activities were conducted with the Sutra Alam Gunung Sewu group in Gunungkidul Regency, DIY, which had previously only utilized the plant's leaves as silkworm feed. The tubers and bark of this tree, which are nutrient-rich but contain high levels of cyanide acid, have the potential to be developed as an alternative food source if processed properly. The empowerment program was implemented to enhance the group's capacity to process the tuber bark into useful products. Evaluation was conducted using pre-test and post-test instruments to measure improvements in members' knowledge and skills. The results showed a 120% increase in general knowledge and an 84% increase in understanding of information regarding the potential of local food and the processing of risky materials into safe consumption. This initiative contributes to food diversification and the economic empowerment of local communities in supporting national food security.
Machine Learning-Based Early Breast Cancer Detection Through Temperature and Color Skin with Non-Invasive Smart Device Salsabila, Sona Regina; Surono, Sugiyarto; Ibad., Irsyadul; Prasetyo, Eko; Subrata, Arsyad Cahya; Thobirin, Aris
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 10 No. 4 (2024): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v10i4.30340

Abstract

Breast cancer remains a significant global health issue, affecting millions of women and often leading to late-stage diagnoses. Traditional diagnostic methods, such as mammograms, ultrasounds, and biopsies, are effective but can be costly, invasive, and not widely accessible, causing delays in detection and treatment.  This research highlights the potential of using machine learning models with physiological data for early breast cancer detection. By capturing subtle physiological variations from a smart bra, the device allows real-time, non-invasive monitoring, offering a preventive solution that reduces the need for frequent clinical visits. The data were collected from a modified mannequin designed to simulate conditions related to breast cancer. To classify cancerous conditions based on temperature and color data, three machine learning models were evaluated.  The Random Forest (RF) model proved to be the most effective, achieving 89% accuracy, 86.11% precision, 88.57% recall, and an F1-score of 87.33%, demonstrating strong performance in identifying complex patterns. The Support Vector Machine (SVM) achieved an accuracy of 81.25%, precision of 85.7%, recall of 80%, and an F1-score of 82.64%. The Multilayer Perceptron (MLP) exhibited an accuracy of 72%, precision of 69.69%, recall of 65.71%, and an F1-score of 67.52%, suggesting potential but requiring further optimization.  These models serve as valuable tools to assist medical professionals in early screening efforts. Future research should aim to improve the models’ generalizability by expanding the dataset, utilizing data augmentation, applying transfer learning, and incorporating additional variables. Clinical validation and human trials are essential next steps to evaluate the system's effectiveness.
Co-Authors Ahsan, Fahmi Amelia, Shinta Aris Thobirin, Aris Ariyansyah, Qolil Asephi, M. Yoga Aska, Ghoniyun Nisa Uskhulil Deslaely Putranti Dhias Cahya Hakika Eko Prasetyo Fadhilla, Irvanda Cheza Noor Fadila, Salwa Ayu Fitrianawati, Meita Haikal, Rayhan Fiqri Hamdi Batubara, Zul Hidayah, Laelatul Ibad., Irsyadul Ibdal, Ibdal Kalid, Khairul Shafee Khasanah, Staniya Uswatun Kurniaty, Maryani Atikah Kusprihatini, Sita Alfia Ma'arief, Sandhy Auliya Mahdi, Imam Mursalin, Ahza Durrani Mutmainnah, Fadila Ainil Nugraheni, Renada Satya Perdana, Muhammad Sukmadika Rahmah, Nur Aisyatul Rahmawan, Jihad Ramadhani, Muhammad Regina, Sona Roazah, Qhusnul Fatimatur Sabila, Liya Yusrina Salsabila, Sona Regina Shafee Kalid, Khairul Shalihah, Amilatun Sudarmini Sudarmini, Sudarmini Sugiyarto Surono, Sugiyarto Totok Eka Suharto Wan Ahmad, Wan Fatimah Yasa, Fakhra Kurnia