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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Reconfigurable and Embedded Systems (IJRES) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Techno.Com: Jurnal Teknologi Informasi MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Bulletin of Electrical Engineering and Informatics DINAMIKA DOTCOM Jurnal EECCIS Jurnal Teknologi Informasi dan Ilmu Komputer Journal of ICT Research and Applications Jurnal Edukasi dan Penelitian Informatika (JEPIN) Proceeding SENDI_U PROCEEDING IC-ITECHS 2014 JOIV : International Journal on Informatics Visualization Jurnal Aplikasi Teknologi Pangan International Conferences SDGs 2030 Challenges and Solutions JITK (Jurnal Ilmu Pengetahuan dan Komputer) Communications in Science and Technology Dinamisia: Jurnal Pengabdian Kepada Masyarakat JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Sinergitas PkM & CSR JURNAL PENDIDIKAN TAMBUSAI ENGLISH JOURNAL International Journal of Community Service Learning WIDYA LAKSANA RESISTOR (Elektronika Kendali Telekomunikasi Tenaga Listrik Komputer) Journal of Information System, Applied, Management, Accounting and Research Indonesian Journal of Electrical Engineering and Computer Science Community Development Journal: Jurnal Pengabdian Masyarakat English Journal Studies in Learning and Teaching Journal of Innovation in Educational and Cultural Research Jurnal Jaringan Telekomunikasi Jurnal Pengabdian Polinema Kepada Masyarakat Journal of English Language and Education Prosiding Konferensi Nasional PKM-CSR Jurnal Nasional Teknik Elektro dan Teknologi Informasi Indonesian Journal Of Educational Research and Review TRANSFORMATIONAL LANGUAGE, LITERATURE, AND TECHNOLOGY OVERVIEW IN LEARNING (TRANSTOOL) Journal of Scientific Research, Education, and Technology Jurnal ELTEK Prosiding Seminar Nasional Pengabdian Masyarakat JPM Pambudi Jurnal Pengabdian Kepada Masyarakat Jurnal Linguistik Terapan Journal of Informatics and Vocational Education
Moechammad Sarosa
Politeknik Negeri Malang
Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Rancang Bangun Sistem Pemantauan dan Pengaturan Nutrisi pada Hidroponik Berbasis IoT Rafi, Barra; Sarosa, Moechammad; Sumari, Arwin; Evan, Agil
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 13 No 2: April 2026
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.132

Abstract

Hidroponik adalah metode pertanian modern yang efisien dalam penggunaan sumber daya dan lingkungan, namun memerlukan pemantauan dan pengaturan nutrisi yang tepat agar tanaman dapat tumbuh dengan optimal. Penelitian ini mengenalkan sistem pemantauan dan pengaturan nutrisi berbasis Internet of Things (IoT) pada sistem hidroponik, dengan fokus pengujian pada tanaman selada. Sensor Total Dissolved Solids (TDS) dan sensor pH terhubung secara nirkabel untuk mengumpulkan data secara otomatis, sementara kamera ESP32-Cam merekam visual pertumbuhan tanaman. Data yang diperoleh dari sensor-sensor dikirim ke basis data Firebase lalu dilanjutkan ke aplikasi. Sistem ini dilengkapi dengan mekanisme otomatisasi untuk mengatur nutrisi berdasarkan parameter yang telah ditentukan. Pengujian dan evaluasi dilakukan pada sistem yang diimplementasikan dalam lingkungan hidroponik. Aplikasi memberikan pengguna kemampuan untuk memantau dan mengatur tingkat nutrisi tanaman selada secara real-time dari jarak jauh. Dengan menggunakan selada sebagai tanaman uji, penelitian ini menyediakan wawasan khusus tentang pengelolaan nutrisi yang efektif dalam konteks hidroponik. Sistem ini bertujuan meningkatkan efisiensi dan produktivitas pertanian hidroponik, sambil memberikan pengguna kemudahan dan aksesibilitas melalui aplikasi mobile yang terhubung secara digital. Hasil yang didapatkan dengan menggunakan sistem automasi didapatkan sistem pemantauan yang tidak kalah akurat dengan menggunakan pemantauan secara langsung. Secara keseluruhan nilai error menggunakan sensor TDS didapatkan antara 0%-3% dan nilai error pada sensor pH sebesar 1%-4%. Dengan demikian, penelitian ini memberikan kontribusi pada pengembangan pertanian modern. Sistem pemantauan dan pengaturan nutrisi pada hidroponik ini dapat membantu petani meningkatkan produktivitas, mengoptimalkan penggunaan sumber daya, dan mendukung pertanian berkelanjutan di masa depan.   Abstract Hydroponics is a modern agricultural method that is efficient in using resources and the environment, but requires proper monitoring and regulation of nutrition so that plants can grow optimally. This research introduces an Internet of Things (IoT)-based nutrient monitoring and regulation system in hydroponic systems, with a focus on testing on lettuce plants. The Total Dissolved Solids (TDS) sensor and pH sensor connect wirelessly to collect data automatically, while the ESP32-Cam camera records visuals of plant growth. Data obtained from sensors is sent to the Firebase database and then continued to the application. This system is equipped with an automation mechanism to regulate nutrition based on predetermined parameters. Testing and evaluation is carried out on systems implemented in a hydroponic environment. The app gives users the ability to monitor and manage lettuce plant nutrient levels in real-time remotely. By using lettuce as a test crop, this research provides specific insights into effective nutrient management in a hydroponic context. This system aims to increase the efficiency and productivity of hydroponic farming, while providing users with convenience and accessibility through a digitally connected mobile application. The results obtained by using an automation system produce a monitoring system that is no less accurate than using direct monitoring. Overall the error value using the TDS sensor was found to be between 0%-3% and the error value on the pH sensor was 1%-4%. Thus, this research contributes to the development of modern agriculture. This system for monitoring and regulating nutrients in hydroponics can help farmers increase productivity, optimize resource use, and support sustainable agriculture in the future.
Genetic algorithm-based chicken manure weight prediction system development Hudaya, Rida; Wirayoga, Septriandi; Sarosa, Moechammad; Yusuf, Muhammad; Prayugo, Armanda Dwi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i2.pp1247-1260

Abstract

This research presents design and implementation of internet of things (IoT) based monitoring and predictive system for evaluating chicken manure weight and environmental conditions in poultry housing. The proposed system integrates MQ-137 sensor for ammonia detection, DHT22 sensor for temperature and humidity measurement, and load cell modules for manure weight monitoring. All sensor data are transmitted in real time to cloud platform, enabling continuous environmental assessment. A 30-day experimental study was conducted using two controlled chicken drum models, each containing 15 broiler chickens and provided with different feed types to observe variations in manure production and air quality. Sensor calibration results indicate high accuracy, with average error of 0.31% for ammonia readings and 0.10% for manure weight measurement. Experimental findings show that feed type A generates lower manure weight, reduced ammonia concentration, and more stable temperature conditions compared to feed type B, suggesting improved feed efficiency and better overall chicken health. A genetic algorithm (GA) was employed to optimize regression model predicting manure weight using ammonia concentration and temperature as input features. The GA-optimized model achieved strong predictive performance, with root mean square error (RMSE) of 0.358 g and coefficient of determination (R2) value of 0.992. The results demonstrate that proposed system provides reliable, scalable, and data-driven solution for smart poultry monitoring and early health detection.
COMPARATIVE ANALYSIS OF YOLOV5SM, YOLOV8, AND YOLOV11 FOR IMAGE-BASED TEMPEH QUALITY RECOGNITION Isa Mahfudi; Mila Kusumawardani; Moechammad Sarosa; Chandrasena Setiadi
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 4 (2026): JITK Issue May 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i4.7930

Abstract

Tempeh is a traditional Indonesian fermented food whose quality is influenced by fermentation and environmental conditions. Quality assessment is still commonly performed manually, leading to subjectivity and inconsistency. This study compares three modern object detection models—YOLOv5sM, YOLOv8, and YOLOv11—for digital image–based tempeh quality recognition. A dataset of 1,000 images (500 good and 500 defective) was collected using a Logitech C270 camera under controlled lighting conditions. YOLOv5sM was trained with data augmentation (Mosaic, flip, rotation), while YOLOv8 and YOLOv11 were trained without augmentation to isolate architectural differences. All models were trained for 100 epochs using identical hyperparameters and evaluated on a 10% test set. Results show that YOLOv11 achieved the highest accuracy (98%), outperforming YOLOv8 (94%) and YOLOv5sM (88%). Although mAP@0.5 reached 99.5% across models, stricter evaluation using mAP@0.5:0.95 revealed performance differences (96.2%, 96.9%, and 97.0%, respectively). The superior performance of YOLOv11 is attributed to its C3K2 and C2PSA modules, which enhance fine-grained feature extraction and localization precision. These findings indicate that YOLOv11 is the most suitable architecture for automated tempeh quality inspection
An Analysis of Linguistic Features Used in Business News of BBC and The Guardian Website Alda Rizky Nur Afida Abdullah; Mariana Ulfah Hoesny; Nugrahaningtyas Fatma Anyassari
JLT Jurnal Linguistik Terapan JLT Volume 15 No 2, 2025
Publisher : UPT P2M Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jlt.v15i2.7621

Abstract

This research analyzed and classified linguistic features found in 16 business news from BBC and The Guardian in January 2024 edition. The business news consist of 300 words approximately. Adapting qualitative method and descriptive analysis to collect the data, the research adopted David Crystal’s theory, which specifically divided linguistic features into five categories, namely lexical, grammatical, discourse, orthographic, and graphic features. The findings of this research mentioned that there are 4 linguistic features identified: lexical, grammatical, discourse, and orthographic. Moreover, the linguistic features mostly found is grammatical features in branch of conjunctions, which have crucial role in establishing coherence and clarity in news writing to make communication effectively. Adopting a case study approach, this research provides the insight and understanding how linguistic features influence the context of business news.
Developing a Bilingual Digital Story to Promote Honesty and Environmental Awareness in Natural Tourism Settings Mariana Ulfah Hoesny
Journal of Informatics and Vocational Education Vol. 9 No. 2 (2026): Journal of Informatics and Vocational Education - July
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v9i2.3472

Abstract

Improving reading skills in junior high school students is a challenge due to low motivation and a lack of engaging materials. This design and development research (DDR) project aimed to address this by developing a digital bilingual storybook for junior high school students. The storybook features illustrations, moral values, and settings based on local nature tourism. The study utilized the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) development model to guide the creation process. Data were collected through teacher interviews, students' questionnaires, expert validation, and product testing. The findings indicated that the developed storybook is highly feasible and received positive feedback from both students and teachers. This storybook not only helps students comprehend bilingual texts but also boosts their motivation and builds character through a connection to their local culture. The result suggests that this material is a valuable tool for enhancing reading skills and instilling positive values in students.
Co-Authors A. Mifta Haerat A. S. Ahmad A. S. Noer AA Sudharmawan, AA Abdul Muqit Achmad Sjaifullah Adhisuwignjo, Supriatna Adi Susilo Agung Teguh Wibowo Almais Agus Naba Aisah Aisah Aisah Aisah Aji Seto Arifianto Akhlis Rizza, Muhammad Alda Rizky Nur Afida Abdullah Alvin Nouval Aly Imron Amalia Eka Rakhmania Amalia Eka Rakhmania Ardian Wahyu Setiawan Aris Budianto, Aris Asa Wisesa Betari Atiqah Nurul Asri Aula, Farisa Afza Ayatullah, Mohamad Dimyati Ayu Sulasari Azhima, Silmi Ath Thahirah Al B. Riyanto Begum Nabiila Bima Eka Samudra Cabuquin, Jomar C. Cahyani, Hilda Calvin Andika Pratama Chandrasena Setiadi D.J. Djoko H. Santjojo Dede Ropik Yunus Dedy Harto Devi Khanthi Dwi Bhakti Dewi Purwati Dimas Firmanda Al Riza Dimas Firmanda Al Riza Dimas Wahyu Wibowo Dodit Suprianto Eka Adhitya Dharmawan Ekananda Sulistyo Putra Elta Sonalitha Erni Yudaningtyas Evan, Agil Fahmi, Ichsan Faisal Rahutomo Fajrin, Rahma Annisa Fengky Adie Perdana, Fengky Adie Fredy Windana Ghiaska Nabilah Witka Hadi Suyono Hadiwiyatno Hadiwiyatno Halimah, Adik Nur Hapsari, Ratih Indri Hariyadi, Aad Harsanti, Winda Hayatun Nufus Henny Purwaningsih Herman Tolle Hilmy Bahy Hakim Hudaya, Rida Hudiono Hudiono Isa Mahfudi Isa Mahfudi Isnaini Nur Safitri Juanda, Enjang Akmad Juhari Juhari, Juhari Kristina Widjayanti, Kristina Kusumawardani, Mila Lestari, Pritantina Yuni Lia Agustina Lis Diana Mustafa M. Aziz Muslim M. Nanak Zakaria, M. Nanak Ma'rifah, Puteri Nurul Mariya Al Qibtiya Mentari Tika Putri Ningrum Mila Kusumawardhani Mochammad Junus Mochammad Taufik Moh. Abdullah Anshori Muh Bambang Purwanto Muhammad Aziz Muslim Muhammad Ridwan Muhammad Yusuf Mujib Ridwan Mulyani Azis, Yunia Muna, Nailul Nadia Hanayeen Nailul Muna Nawaluddin, Shafa Yasmin Nila Alia Noviatus Solekhah, Noviatus Nugrahaningtyas Fatma Anyassari Nurafni Eltivia Nuraini, Salsabila Andhika Nurdin, Muhammad Nurdin Rosyidi Nurul Fahmi Arief Hakim Nurul Hidayati Nurul Hidayati Onny Setyawati Paulus Lucky Tirma Irawan Peruzzi, Erico Prayugo, Armanda Dwi Purnomo Budi Santoso Purnomo Budi Santoso Putri Elfa Mas'udia Putri Elfa Mas'udia Putri Elfa Mas’udia Putri Elfa Masudia Putri Elfa Mas`udia Putri Elfa Mas’udia Putri Elfa Mas’udia Putri Elfa Mas’udia Putri, Fidia Sabilla Rachmad Saptono Rafi, Barra Ratna Ika Putri Reista Fatikah Maldhani Ribka Inestya Simanungkalit Rieke Adriati Wijayanti Roisatin, Umi Anis Romadlon, Shofiyul Irchami Rr Rachmawati Rr Rachmawati Rulianah, Sri Saavedra, Analyn D. Safitri, Isnaini Nur Sahriar Hamza Saida Ulfa Sakinah, Yanik Lailinas Sapto Wibowo Saputra, Dede Irawan Sari, Zamah Sari, Zamah Selviana, Vuvut Septarina, Amalia Agung Septriandi Wirayoga Sri Widoretno Stania, Ummi Rizki Alfi Sugeng Riyanto Suhari Suhari Suhari Sumari, Arwin Suprapto Suprapto Sussy Susanti Suyono, Achmad Suyono, Hadi Syani, Syafika Shalshabilla Tiara estu amanda Tridon Yang Astami Umi Anis Roisatin Usman Zulhijah Muhamma6 Wahyu Bambang Try Atmaja Waluyo Waluyo Waluyo Waluyo Waluyo Widjajanti, Kristina Wijaya, Mokhamad Hadi Winendra, RR Sekar Ayu Devi Wirayoga, Septriandi Wiyono Wiyono Yani Ratnawati Yulianto Yulianto Yunia Mulyani Azis Yunia Mulyani Azis Zamah Sari Zamah Sari