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The rapid development of technology in the era of the Industrial Revolution 4.0 has driven the education sector to continuously adapt to the evolving demands of digital-based industries. One of the key technological innovations supporting this transformation is the Internet of Things (IoT), which enables data acquisition, real-time monitoring, and remote control of systems through internet networks. In response to these developments, a community service program was conducted to enhance the understanding and technical skills of students at SMK Negeri 1 Sindang through the provision and utilization of an IoT Trainer Kit Simulator as a practical learning medium. This activity aimed to bridge the gap between theoretical knowledge and industry-relevant technological applications by introducing students to hands-on IoT system implementation. The program included demonstrations and guided practice on the use of sensors, microcontrollers, and web-based monitoring platforms to simulate real-world industrial scenarios. The results indicate that students showed high enthusiasm and active participation throughout the activity. Moreover, participants were able to grasp the fundamental concepts of IoT systems, understand component integration, and recognize the relevance of IoT applications in supporting automation and digital transformation. Overall, this community service activity contributed positively to strengthening students’ digital competencies and preparedness for the demands of the contemporary industrial and technological landscape.

A fracture occurs when bone continuity is disrupted due to external pressure or force that exceeds the bone's capacity. Fractures constitute a medical emergency requiring immediate treatment. A primary surgical intervention for this condition is the Open Reduction and Internal Fixation (ORIF) procedure, which aims to reposition broken bone fragments to their normal anatomy. This procedure is considered crucial for achieving proper bone union and minimizing the potential for postoperative complications. As a consequence of the surgical incision and tissue trauma, patients commonly experience postoperative pain. The management of this pain can broadly be categorized into two approaches: pharmacological and non-pharmacological. Among non-pharmacological methods, cold compress therapy has proven effective in alleviating pain in patients following ORIF surgery. The sensation of pain can be alleviated through the application of a cold pack by inhibiting sensory nerve conduction and suppressing local inflammation. Simultaneously, cryotherapy also reduces blood flow to the injury site, which in turn limits blood extravasation and the accumulation of edema fluid. A descriptive case study analysis of four patients with acute pain after lower extremity ORIF surgery. The effectiveness of the intervention was measured using the Numeric Rating Scale (NRS).: The application of cold compresses using cold packs for 3 days to 4 respondents before the cold compress was applied was on a pain scale of 6–7 (moderate to severe category), after the intervention the pain scale became 2–3 (mild category). The results indicate that cold compress therapy in patients with lower extremity post-ORIF fractures is effective in reducing pain levels. Therefore, cold compress therapy is recommended as a non-pharmacological therapy to reduce pain in patients with fractures after ORIF.

The progressive consolidation of navigational instruments into Integrated Bridge Systems (IBS) has fundamentally transformed the sensory and cognitive architecture of modern maritime watch-keeping, creating a paradox of technological sophistication: while IBS enhances navigational efficiency under nominal operating conditions, it simultaneously generates profound human factors vulnerabilities when sensor inputs degrade, fail, or are intentionally disrupted. Despite the safety-critical nature of this vulnerability, empirical human factors research specifically addressing deck officer situational awareness under degraded IBS sensor conditions — particularly in the context of GPS spoofing, radar shadowing, and AIS anomalies — remains insufficiently developed in the maritime research literature. This study investigates the human factors dimensions of IBS situational awareness degradation among deck officers at Sekolah Tinggi Ilmu Pelayaran (STIP) Jakarta, Indonesia, examining how officers perceive, respond to, and recover from degraded sensor scenarios in simulator-based environments. Employing a qualitative research design, data were generated through semi-structured interviews with senior deck officers, navigation simulation instructors, and maritime human factors experts, supplemented by structured observation of IBS simulator degradation scenario sessions. Analysis proceeded through thematic analysis, cross-group comparison, and narrative synthesis. Findings reveal four critical human factors failure patterns under degraded IBS conditions: automation complacency, cross-verification skill atrophy, alert saturation mismanagement, and manual navigation competency erosion — all of which are systematically underprepared for within current STCW-aligned deck officer training curricula. The study proposes a competency-based degraded operations training framework as a principled response to these findings, with direct implications for maritime simulator curriculum design and STCW competency standard revision.

People with visual impairment face barriers in cash transactions, particularly in identifying banknote denominations and verifying authenticity, which can reduce independence and increase vulnerability to fraud. This issue is also closely linked to the financial inclusion agenda, as access to reliable information on the value and authenticity of cash is a prerequisite for safe transactions among vulnerable groups. This community service program aimed to improve users’ competence through individualized, home-visit–based education and mentoring on an optical–UV sensor–based banknote denomination and authenticity detector with audio feedback. The program was implemented in collaboration with the Kebumen branches of PERTUNI and ITMI from October to December 2025. The intervention stages included an initial needs assessment, structured training using a concise module, hands-on practice through transaction scenarios, and follow-up mentoring. Evaluation employed a pre–post knowledge test, a practical performance checklist, and a usability questionnaire. Results indicated that the mean knowledge score increased from 55.1 to 80.7, and the success rate of denomination identification improved from 60.7% to 90.0%. This approach is relevant as an individualized mentoring model for blind communities when group-based training is difficult to implement.

Starfruit (Averrhoa bilimbi L.), commonly known in Indonesia as belimbing wuluh, is widely used as a natural acid in traditional cuisine. It is often processed into dried sour starfruit (asam sunti), which can last 1–1.5 years. However, traditional sun-drying methods are inefficient due to weather dependency, long processing times, and inconsistent product quality and color. This study aims to design and develop a tunnel-type starfruit dryer equipped with a blower system and heat control based on the Arduino Mega 2560. The research employs a quantitative method to evaluate tool performance. The dryer is cylindrical and supported by key components, including LPG gas as a heat source, a blower for air circulation, and a drum holder. Drying is conducted in six stages, each lasting 120 minutes, totaling 12 hours to achieve optimal dryness. Temperature monitoring at three points (T1, T2, T3) uses a MAX6675 sensor with a thermocouple connected to the Arduino Mega 2560, while weight measurement is done manually. Results indicate the tool functions effectively. A denser drying chamber and proper blower installation are recommended to ensure even heat distribution and improved drying efficiency for community use.

Starfruit (Averrhoa bilimbi L.), commonly known in Indonesia as belimbing wuluh, is widely used as a natural acid in traditional cuisine. It is often processed into dried sour starfruit (asam sunti), which can last 1–1.5 years. However, traditional sun-drying methods are inefficient due to weather dependency, long processing times, and inconsistent product quality and color. This study aims to design and develop a tunnel-type starfruit dryer equipped with a blower system and heat control based on the Arduino Mega 2560. The research employs a quantitative method to evaluate tool performance. The dryer is cylindrical and supported by key components, including LPG gas as a heat source, a blower for air circulation, and a drum holder. Drying is conducted in six stages, each lasting 120 minutes, totaling 12 hours to achieve optimal dryness. Temperature monitoring at three points (T1, T2, T3) uses a MAX6675 sensor with a thermocouple connected to the Arduino Mega 2560, while weight measurement is done manually. Results indicate the tool functions effectively. A denser drying chamber and proper blower installation are recommended to ensure even heat distribution and improved drying efficiency for community use.

Boiler merupakan komponen vital dalam operasional Pemnagkit Listriik Tenaga Sampah, Dimana sampahmenjadi bahan bakar Utama yang diolah menjadi panas yang dipergunakan untuk mendidihkan airdidalam boiler. Operasional boiler memerlukan pengawasan ketat terhadap parameter suhu, tekanan, danlevel air untuk mencegah risiko kecelakaan kerja dan inefisiensi energi. Namun, sistem pemantauankonvensional seringkali masih bergantung pada pengecekan manual yang berisiko terjadi kesalahanmanusia (human error). Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistemkontrol otomatis boiler berbasis Internet of Things (IoT) menggunakan mikrokontroler ESP32 sebagai unitpemroses utama. Sistem ini dilengkapi dengan sensor suhu, sensor tekanan, dan Level Switch untukmendeteksi level air secara real-time. Data dari sensor dikirimkan ke aplikasi Blynk melalui jaringan Wi-Fi, yang memungkinkan operator melakukan pemantauan dan pengendalian jarak jauh melaluismartphone. Hasil pengujian menunjukkan bahwa sistem mampu mengotomatisasi pengisian air danpengeluaran uap dengan tingkat akurasi yang tinggi serta latensi pengiriman data yang minimal.Implementasi sistem ini diharapkan dapat meningkatkan standar keselamatan kerja, efisiensi operasional,dan memperpanjang usia pakai komponen boiler melalui pemeliharaan preventif yang lebih akurat.Kata Kunci: Boiler, IoT, ESP32, Sistem Kontrol Otomatis, Monitoring Real-time.

Adanya risiko pencemaran lingkungan dan ledakan yang disebabkan oleh tekanan balik pada aliran gasbuang sehingga diperlukan pembuatan sistem pengapian (ignitor) otomatis dimana gas buang dapatterbakar sebelum dilepaskan ke lingkungan. Perangkat ini menggunakan modul MAX6675, sensortermokopel tipe-K, mikrokontroler ESP32, aktuator ignitor elektrik, tampilan LCD I2C, dan platformBlynk untuk monitoring jarak jauh. Pipa Ignitor yang berfungsi untuk menghasilkan api kecil suhunyaakan dideteksi oleh sensor termokopel, dimana besar kecilnya temperatur akan diberikan oleh termokopelmelalui modul MAX6675 kepada mikrokontroller, lalu diolah oleh mkrokontroller. Hasil dari pengolahanmikrokontroller akan diberikan kepada ignitor untuk memerintahkan apakah ignitor On atau Ignitor Off.Suhu dan status ignitor ditampilkan melalui LCD dan Blynk pada monitoring jarak jauhnya. Rentang suhuuji 0°C-100°C, pengujian mengukur waktu respons ignitor, akurasi suhu, dan efektivitas pembakaran.Hasil penelitian menunjukkan bahwa sensor sangat akurat (selisih <1%), sistem dapat mengaktifkanignitor secara Otomatis (SUHU1 untuk pembacaan sensor) sesuai ambang suhu yang ditetapkan (ignitorON di bawah 100 °C dan OFF di atas 100 °C), Serta terdapat sistem Manual (SUHU2) yang dapat disebutjuga sistem bypass yang mengaktifkan ignitor hanya dengan mengaktifkan tombol FIRE. Jarak antara busidan elektroda pemantik ssebesar 50 mm merupakan jarak untuk mendapatkan nyala api terbaik. Sistemotomatis maupun manual dari ignitor ini dapat dimonitor melalui LCD, Blynk dan pembacaan faultnyadapat bekerja sesuai dengan perancangan.

13Kalibrasi Instrumen Proses Evaporator sebagai Upaya MenjaminKeselamatan Pengolahan Limbah Radioaktif Cair(Calibration of Evaporator Process Instruments to Ensure the Safety ofLiquid Radioactive Waste Treatment)Dzulfikri Pangestu1,2*, Sugianto2 , Krismanto21Program Studi Teknik Elektro, Institut Teknologi Indonesia2Instalasi Pengelolaan Limbah Radioaktif, Direktorat Fasilitas Ketenaganukliran,Badan Riset dan Inovasi NasionalAbstrakUnit evaporasi pada fasilitas pengolahan limbah radioaktif cair IPLR-BRIN telah beroperasi sejak1989, sehingga berpotensi mengalami degradasi komponen dan instrument drift yang dapatmemengaruhi akurasi pengukuran proses. Ketidakakuratan instrumen proses pada titik-titik kritisseperti laju aliran, level, tekanan, suhu, dan densitas berpotensi menempatkan operasi di luar bataskeselamatan yang ditetapkan oleh BAPETEN. Untuk memastikan keandalan sistem pengukuran,dilakukan kegiatan kalibrasi internal terhadap 22 instrumen proses yang digunakan dalam operasievaporasi. Kegiatan ini mencakup pengujian instrumen berbasis arus 4–20 mA dan sensor suhuberbasis resistansi menggunakan peralatan standar seperti current source, multimeter digital, danresistance decade box. Setiap titik uji divalidasi melalui empat kali pengulangan untuk menilai presisidan konsistensi pembacaan. Hasil kalibrasi menunjukkan bahwa seluruh instrumen masih beradadalam kondisi kerja yang baik, dengan penyimpangan terhadap nilai acuan komisioning berada padarentang yang sangat kecil. Estimasi ketidakpastian pengukuran berulang didominasi oleh nilaimendekati nol, menandakan bahwa variasi acak hampir tidak terjadi dan instrumen memiliki presisiyang tinggi serta tidak mengalami drift signifikan. Selain itu, seluruh sistem alarm proses meliputiparameter level, tekanan, suhu, dan densitas berfungsi pada nilai set dan reset yang sesuai bataskeselamatan. Temuan ini menegaskan bahwa instrumen proses pada unit evaporasi masih memenuhipersyaratan teknis dan keselamatan operasional, serta menggarisbawahi pentingnya pelaksanaankalibrasi internal secara berkala sebagai bagian dari pemeliharaan preventif untuk menjagakeandalan fasilitas dalam jangka panjang.

Dementia is a progressive neurocognitive disorder often accompanied by behavioral and psychological symptoms such as agitation, anxiety, and depression. Pharmacological treatments provide only modest benefits while introducing significant risks, which highlights the need for safer, non-pharmacological alternatives. This literature review examines the role of virtual reality in dementia care, with a focus on its integration with therapies such as music, reminiscence, sensory stimulation, and cognitive training. Evidence from prior research suggests that virtual reality can enhance cognitive functions, reduce symptoms, and improve emotional well-being while also strengthening patient–caregiver interaction. However, challenges related to usability, accessibility, cost, and long-term effectiveness continue to limit adoption. Gaps in research, including limited cultural diversity, inconsistent reporting of intervention design, and a lack of large-scale longitudinal trials, emphasize the need for future work exploring cross-cultural feasibility and AI-driven personalization. Overall, virtual reality represents a promising and evolving non-pharmacological intervention that has the potential to transform dementia care by improving quality of life and reducing reliance on medication.

This study aimed to analyze the effect of parent empowerment in optimizing tummy time on head control in infants aged 0–6 months at community health posts in Jatisampurna, Bekasi. Early motor development requires adequate sensory–motor stimulation, yet many parents have limited knowledge and practice of prone positioning activities. A quasi-experimental one-group pretest–posttest design was employed involving nine healthy infants selected through purposive sampling. Parents received education and practical training on tummy time and were instructed to implement a home program for two weeks with a minimum duration of 30 minutes per day. Head control was assessed before and after the intervention using the Head Control Scale across prone, supine, pull-to-sit, and supported sitting positions. The results demonstrated improvements in head control scores in all positions, with the most notable gains observed in infants who had lower baseline abilities. The findings indicate that repeated prone stimulation enhances postural control through increased neck and trunk muscle activation and improved sensory–motor integration. Parent empowerment also increased knowledge, adherence to home stimulation, and active participation in child development monitoring. This community-based intervention shows potential as a promotive and preventive strategy to support early motor development through family-centered approaches at primary health services.

Pneumonia remains a leading cause of morbidity and mortality worldwide, particularly in resource-limited settings and among elderly populations, where timely diagnosis and continuous monitoring are often constrained by limited clinical infrastructure. This study presents an edge–cloud–integrated framework for early pneumonia risk monitoring, leveraging multimodal wearable sensors and deep learning to support continuous short-duration monitoring. The proposed system is designed to operate in near real time under simulated deployment conditions, continuously acquiring and analyzing physiological signals (respiratory rate, heart rate, SpO₂, and body temperature) alongside event-driven acoustic biomarkers (cough sounds) within a distributed architecture. A lightweight edge module performs local signal preprocessing and anomaly triage, selectively transmitting salient information to a cloud-based multimodal deep learning model for refined risk estimation and interpretability analysis. The framework was evaluated using a multi-source dataset comprising public repositories (MIMIC-III and Coswara) and a clinically supervised wearable study conducted in two Nigerian hospitals, resulting in 718  hours of quality-controlled multimodal monitoring data. In a pooled multi-source evaluation, the system achieved an AUC of 0.95, while in a clinically realistic local-only evaluation, the AUC was 0.86, reflecting a consistent but preliminary diagnostic signal. These results highlight the importance of local data adaptation for real-world applicability and suggest that multimodal AI can provide meaningful early risk indicators under resource constraints. Beyond predictive performance, this work demonstrates the feasibility of integrating multimodal learning, edge–cloud computation, and explainable analytics into a deployment-aware, privacy-preserving monitoring framework for low-resource healthcare environments.

Improper water management in rice cultivation can lead to water stress, which reduces productivity. Conventional monitoring has limitations on large-scale lands, necessitating more efficient remote sensing technologies. This study aims to develop a water stress identification system for rice plants in the late vegetative phase using multispectral drone imagery integrated with an Artificial neural network (ANN). The research method employs an experimental approach with six water availability levels in Karyamukti Village, Sumedang. Field reference data were obtained through soil moisture sensors converted into Available Water (AW) values. Image processing stages included orthomosaic reconstruction, leaf object segmentation, and transformation of vegetation indices (NDVI, NDRE, GNDVI, etc.) as model inputs. The results show that the ANN model with a four-hidden-layer architecture achieved training and validation accuracies of 94–95%. In the independent testing phase, the model produced an accuracy of 94.60% with an F1-Score of 93.33%. Spatial visualization of the prediction results indicates a consistent water condition distribution across rice plots. In conclusion, the integration of multispectral drones and ANN provides an accurate non-destructive solution for spatial monitoring of water availability in rice plants.

Indramayu mango is a seasonal fruit that is highly favored due to its delicious taste and high nutritional content. However, high mango production is often not supported by adequate post-harvest facilities, particularly in terms of fruit ripeness classification. Currently, mango ripeness classification is still performed manually, which tends to be subjective and inconsistent. To address this issue, this study proposes a ripeness detection system for Indramayu mangoes by integrating the TGS2602 gas sensor and the YOLOv11 algorithm based on image processing. The TGS2602 sensor is used to detect ethylene gas emitted by ripe mangoes, while YOLOv11 is employed for visual image analysis of the fruit. This study aims to evaluate the system’s performance in classifying ripe and unripe mangoes, as well as analyze the integration between the gas sensor and the object detection model. The test results show that the TGS2602 sensor can detect increased ethylene gas concentration in ripe mangoes, while YOLOv11 demonstrates high accuracy in detecting mangoes based on visual images, with precision and recall close to 1.0. The system was also tested under various lighting conditions, including dark environments, and still performed well, although with a slight decrease in accuracy under low-light conditions.

Pengunaan peralatan elektromedik merupakan faktor krusial dalam pemantauan kesehatan bayi dan anak terutama pada akurasi hasil yang di peroleh. Sesuai dari data yang didapat bahwa mitra telah memiliki sarana medis dasar yang memadai, namun diperlukan standarisasi manajemen pemeliharaan untuk menjaga fungsionalitas alat dalam jangka panjang. Kegiatan pengabdian masyarakat ini bertujuan untuk memperkuat kapasitas teknis para pengasuh dalam pengoperasian dan perawatan peralatan medis secara mandiri. Metode yang digunakan meliputi pemetaan kondisi alat (inventarisasi), sosialisasi prosedur teknis, serta simulasi praktik pemeliharaan preventif. Hasil kegiatan menunjukkan adanya peningkatan pemahaman praktis pengasuh mengenai aspek teknis alat, seperti perawatan mandiri, perawatan sensor oximeter, dan manajemen penyimpanan perangkat elektronik. Sebagai bentuk keberlanjutan program, telah disusun "Buku Saku SOP Perawatan Peralatan Medis" yang berfungsi sebagai panduan operasional harian bagi staf pengasuh. Luaran dari pengabdian ini memberikan dampak positif bagi mitra berupa tersedianya panduan sistem perawatan yang lebih terorganisir. Simpulan dari kegiatan ini menunjukkan bahwa integrasi antara edukasi teknis dan penyediaan panduan tertulis mampu mengoptimalkan masa pakai alat medis serta menjamin validitas hasil pemeriksaan kesehatan anak. Sinergi ini diharapkan dapat menjadi model bagi lembaga sosial dalam mewujudkan layanan kesehatan mandiri yang berkualitas

Konflik manusia–gajah merupakan permasalahan serius di kawasan Taman Nasional Way Kambas, Lampung, yang berdampak pada kerugian ekonomi, gangguan sosial, dan ancaman keselamatan manusia serta satwa liar [1], [2]. Salah satu pendekatan mitigasi yang efektif adalah penerapan sistem peringatan dini berbasis teknologi telekomunikasi dan Internet of Things (IoT) [3], [4]. Penelitian ini bertujuan menganalisis kebutuhan dan kinerja jaringan telekomunikasi yang sesuai untuk mendukung sistem peringatan dini konflik manusia–gajah. Metode meliputi analisis kebutuhan sistem, perancangan arsitektur jaringan, perbandingan teknologi komunikasi (GSM/4G, NB-IoT, dan LoRaWAN), serta simulasi skenario pengiriman data dari node sensor. Data empiris diperoleh dari simulasi performa jaringan (jangkauan, delay, konsumsi daya, dan packet delivery ratio). Hasil analisis menunjukkan bahwa LoRaWAN memiliki keunggulan dalam jangkauan dan efisiensi energi untuk wilayah konservasi yang minim infrastruktur [5], [6]. Sistem yang diusulkan mampu mengirimkan data deteksi keberadaan gajah secara near real-time ke pusat pemantauan dan selanjutnya didistribusikan sebagai peringatan kepada petugas dan masyarakat sekitar. Penelitian ini diharapkan menjadi referensi dalam pengembangan sistem peringatan dini konflik manusia–gajah berbasis telekomunikasi di Indonesia.

This research investigates intelligent cooling system design for main ship engines operating in tropical waters, integrating advanced machinery engineering with human factors to address thermal management challenges affecting engine performance, reliability, and crew operational effectiveness. Tropical maritime environments impose severe cooling demands through elevated seawater temperatures (28-32°C), high ambient conditions (28-35°C), and accelerated biofouling, reducing conventional cooling system effectiveness by 15-25% while increasing maintenance burdens and operational risks. Through qualitative analysis involving marine engineers, chief engineers with tropical operational experience, cooling system manufacturers, naval architects, automation specialists, and maritime training institutions, this study examines how intelligent cooling systems incorporating variable-speed pumps, adaptive control algorithms, predictive maintenance, and crew-centered interfaces can optimize thermal management while supporting effective human-machine collaboration. Results demonstrate that intelligent systems can reduce cooling energy consumption by 20-35%, improve temperature stability by 50-65%, extend maintenance intervals by 40-80%, and enhance crew situational awareness through intuitive monitoring interfaces, while requiring comprehensive training programs developing technical understanding and operational competencies. Key implementation challenges include control system complexity, sensor reliability in harsh marine environments, integration with existing engine management platforms, crew competency development requirements, and lifecycle cost justification. Findings reveal that successful intelligent cooling system implementation requires holistic sociotechnical approach addressing machinery engineering optimization, automation technology deployment, and human capability development through coordinated design and training strategies. This research contributes to marine engineering literature by providing integrated frameworks for intelligent system design incorporating machinery performance, automation capabilities, and human factors supporting operational excellence in tropical maritime operations.

This research explores how the theology of embodiment in 1 Corinthians 6:19-20 can serve as a biblical foundation for integrating the embodied dimension in Christian Religious Education (CRE) pedagogy. The research background is the tendency of CRE in Indonesia to be highly cognitive-centric and neglect the embodied dimension, despite contemporary research showing the importance of sensory experience in constructing religious experience. The research objective is to conceptually explore the theological foundation and pedagogical implications of the theology of embodiment for CRE. The research method is library research with grammatical-historical exegesis analysis of 1 Corinthians 6:19-20 and conceptual synthesis with embodied cognition theory and body pedagogics. The findings show that the body has intrinsic sacred value as the temple of the Holy Spirit and the glorification of God occurs explicitly through the body. Religious knowledge is embodied, rooted in sensory-motor experience. The pedagogical implication is that CRE needs to integrate systematic embodied practices such as somatic inversion, participatory rituals, and cultivation of enactive mastery for experientially transformative learning. This research contributes theoretically by bridging biblical exegesis and embodied cognition theory, and provides practical direction for developing holistic CRE that integrates the body as an authentic and biblical medium for learning faith.

The development of automation and robotics technology has driven innovation in various industrial fields, particularly in automatic sorting systems. Manual sorting processes often lead to inefficiencies and human errors, creating the need for an automatic, fast, and accurate system. This research employs a qualitative method which includes experimentation, testing, and system documentation. The system is designed as a robotic arm for sorting objects based on color, utilizing a TCS3200 color sensor and an ESP32 microcontroller. An ultrasonic sensor detects the presence of objects, while the sorting results are displayed through a real-time web monitoring system. The test results show that the prototype successfully sorts four primary colors (red, green, blue, and yellow) with a high level of accuracy. This research is expected to serve as a reference for the development of automation systems and robotics learning tools in both educational and industrial applications. In addition, this research also contributes to the development of technology that can increase efficiency and accuracy in industrial production processes and provide more environmentally friendly solutions by reducing the need for manual labor.

Traditional fermented foods made from glutinous rice play a significant role in Indonesia’s local food system, with fermented glutinous rice known as tape ketan being one of the most popular products. Tape ketan is produced through a fermentation process using traditional starter cultures that involve diverse microorganisms, resulting in distinctive sensory characteristics. This review article aims to examine and synthesize previous studies related to the fermentation process of tape ketan and the characterization of metabolites formed during fermentation. The study employed a qualitative approach with descriptive analysis based on a literature review of relevant national and international scientific journals. The findings indicate that tape ketan fermentation involves starch hydrolysis, sugar fermentation, and the formation of primary and secondary metabolites influenced by fermentation time and microbial composition. Primary metabolites such as simple sugars, organic acids, and alcohol contribute to the basic sensory attributes of the product, while secondary metabolites including phenolic compounds and bioactive components enhance its functional potential. The characterization of these metabolites demonstrates that tape ketan is not only a traditional fermented food but also has promising potential for development as a value-added functional food based on local wisdom.