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Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LP2M) Alamat: Graha Rektorat Lantai 6, Jl. Semarang No.5, Sumbersari, Kec. Lowokwaru, Kota Malang, Jawa Timur 65145, Indonesia
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Jurnal Inovasi Teknologi dan Edukasi Teknik
Published by Universitas Negeri Malang
ISSN : -     EISSN : 27977196     DOI : 10.17977
Core Subject : Engineering,
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering Industrial & Manufacturing Engineering
Jurnal Inovasi Teknologi dan Edukasi Teknik menerbitkan naskah terkait Teknik Sipil, Teknologi Industri, Teknik Mesin, Teknik Elektro, dan Pendidikan Kejuruan. Fokus dan lingkup jurnal meliputi Teknik Sipil, Teknologi Industri, Teknik Mesin, Teknik Elektro, dan Pendidikan Kejuruan
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 277 Documents
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DECISION INTELLIGENCE SYSTEMS FOR AUTONOMOUS PRODUCTION PLANNING AND CONTROL Okechukwu Chiedu Ezeanyim; Kenechukwu Favour Anagwu
Jurnal Inovasi Teknologi dan Edukasi Teknik Vol. 5 No. 11 (2025)
Publisher : Universitas Ngeri Malang

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Abstract

This review examines decision intelligence systems for autonomous production planning and control in Industry 4.0 manufacturing. It addresses the limits of conventional production planning and control systems, which depend on deterministic models, historical data, human expertise, and a two-tier structure of schedule generation and execution control. Such systems perform poorly when demand variability, resource constraints, machine workload changes, material shortages, and quality disruptions make released schedules suboptimal. The review synthesizes evidence from multi-agent systems, holonic manufacturing, cyber-physical production systems, digital twins, machine learning, reinforcement learning, data-driven scheduling, and prescriptive analytics. It shows how decision intelligence links data acquisition, analytics, optimization, and execution through a closed-loop sense-decide-act structure. The framework rests on four core components: data acquisition and management, analytical models, decision algorithms, and execution mechanisms. It evaluates five operational domains: dynamic scheduling, inventory and supply chain coordination, resource allocation, predictive maintenance, and resilient production control. Numerical evidence strengthens the review. Digital twin literature shows 38% use simulation models to represent physical systems and predict future states, while 29% integrate optimization into simulation models. A validated multi-agent logistics case reported savings of 2.6 million pallet-days per year through better use of terminal free time. The review also identifies six unresolved barriers: data quality and integration, model interpretability, scalability, real-time implementation, human-system interaction, and lack of standard frameworks. Future systems should combine explainable AI, edge-cloud computing, digital twin-based optimization, hybrid control, and standardized evaluation protocols to achieve adaptive, scalable, and trusted autonomous production control.
INTEGRATION OF ETHNO-BIOLOGY AND INDIGENOUS KNOWLEDGE SYSTEMS (IKS) IN SECONDARY SCHOOL BIOLOGY: EFFECTS ON STUDENT ENGAGEMENT, CONCEPTUAL UNDERSTANDING, AND RETENTION IN SOUTH-EAST NIGERIA Esther Ebele Akachukwu; Okoye Paschal Olisaeloka
Jurnal Inovasi Teknologi dan Edukasi Teknik Vol. 5 No. 9 (2025)
Publisher : Universitas Ngeri Malang

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Abstract

Persistent reports from the West African Examinations Council (WAEC) and the National Examinations Council (NECO) reveal that secondary school students in Nigeria struggle to grasp abstract concepts in Biology, particularly in areas such as genetics, ecology, and cellular respiration. At the same time, students in South-East Nigeria exhibit a profound, practical understanding of local flora and fauna (for instance, the medicinal applications of Vernonia amygdalina (bitter leaf), Xylopia aethiopica (uda), and Ocimum gratissimum (scent leaf)), which they have acquired through Indigenous Knowledge Systems (IKS). Nevertheless, this ethno-biological knowledge is largely disconnected from formal educational settings. This study aimed to explore the degree to which the incorporation of Igbo ethno-biological knowledge into the teaching of challenging Biology topics enhances students' conceptual understanding, engagement, and long-term retention. A quasi-experimental pretest-posttest non-equivalent control group design was utilized. The participants consisted of 186 senior secondary school year two (SS2) students from four co-educational public schools located in Enugu and Anambra States (two experimental groups and two control groups). The experimental groups underwent a 6-week IKS-integrated Biology instruction, which included culturally contextualized lessons, indigenous classification tasks, ethno-medicinal plant analysis, and local ecological observations, while the control groups received traditional lecture-based instruction. The instruments used for assessment included the Biology Conceptual Understanding Test (BCUT, comprising 35 multiple-choice and 15 short-answer items, r=0.87), the Engagement Inventory (EI, a 5-point Likert scale, α=0.91), and the Delayed Retention Test (identical to the BCUT, administered 6 weeks after the intervention). Qualitative data were gathered from 12 focus group discussions to complement the quantitative findings. The results of the ANCOVA indicated that students in the IKS-integrated group significantly outperformed those in the control group in terms of conceptual understanding (mean experimental=72.4%, SD=9.6; control=48.3%, SD=11.2; F(1,183) =146.3, p<0.001, η²=0.44). Qualitative findings indicated that students perceived the integration of Indigenous Knowledge Systems (IKS) as "meaningful," "easier to recall," and "linking school to home." The incorporation of ethno-biology notably enhances the understanding of abstract concepts in Biology, boosts student engagement, and aids in the retention of knowledge over the long term. The study advocates for the establishment of a formal ethno-biology curriculum for senior secondary Biology, the professional development of teachers in IKS integration, and the acknowledgment of Indigenous knowledge as a valid pedagogical framework in policy.
GENERATIVE AI FOR SUPPLY CHAIN OPTIMIZATION: OPPORTUNITIES AND ETHICAL RISKS IN PROCUREMENT Godspower Onyekachukwu Ekwueme
Jurnal Inovasi Teknologi dan Edukasi Teknik Vol. 6 No. 2 (2026)
Publisher : Universitas Ngeri Malang

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The introduction of Generative Artificial Intelligence (Generative AI) technology in supply chain management has facilitated the automation of procurement processes, supplier selection, optimization of inventory management and demand forecasting among other benefits. However, the use of Generative AI in procurement processes brings forth several ethical issues including transparency, algorithmic biases, data privacy and security, accountability and displacement of jobs. This study focused on investigating the opportunities and ethical dilemmas posed using Generative AI technology in supply chain optimization, particularly procurement process. The research employed a qualitative approach through the content analysis of academic journals. The secondary data used in the study includes journal articles, conference papers, industrial reports, and policy documents. It is found out that Generative AI technology is highly efficient in improving procurement through intelligent supplier assessment, contract creation, predictive analysis, demand forecasting, inventory optimization, and real-time decision-making processes. On the other hand, the findings suggest that poor governance frameworks, low data quality, algorithm discrimination, lack of transparency, cyber-security threats, and ethical issues associated with accountability can jeopardize the sustainable implementation of the technology. It can be concluded that the incorporation of Generative Artificial Intelligence in supply chain management has many advantages ranging from increased efficiency to better decision-making capabilities, forecasting accuracy, procurement activities, and increased resilience. Unfortunately, there are various challenges facing companies in Nigeria that limit the ability to incorporate generative artificial intelligence in supply chain management.
DEFICIT IRRIGATION EFFECTS ON SOIL NUTRIENT DYNAMICS AND YIELD PERFORMANCE OF MAIZE (ZEA MAYS L.) Chike Pius Nwachukwu; Chukwuemeka Obumneme Umobi; Luke Okwuchukwu Uzoigwe
Jurnal Inovasi Teknologi dan Edukasi Teknik Vol. 5 No. 10 (2025)
Publisher : Universitas Ngeri Malang

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Abstract

A field experiment was conducted at the Experimental Farm/Workshop of the Department of Agricultural and Bioresources Engineering, Nnamdi Azikiwe University, Awka, Nigeria, to evaluate the effects of deficit irrigation on soil chemical properties, yield, and yield components of maize. The study was laid out in a randomized complete block design with three replications and six irrigation regimes based on crop evapotranspiration (ETc), namely 100% ETc (full irrigation), 80% ETc, 60% ETc, 50% ETc, 40% ETc, and 30% ETc. Measured parameters included maize yield, 1000-grain weight, cob weight, soil electrical conductivity (EC), nitrogen, phosphorus, potassium, and soil pH. Maize yield ranged from 1,420 to 2,580 kg/ha, while 1000-grain weight varied between 162 and 342 g. Cob weight ranged from 352 to 398 g. Soil EC varied between 50.8 and 55.6 µS/cm, nitrogen ranged from 1.08 to 1.86 g/kg, phosphorus ranged from 3.10 to 7.72 mg/kg, potassium ranged from 6.5 to 9.2 ppm, and soil pH ranged from 6.08 to 7.02. Analysis of variance showed significant (p < 0.05) effects of irrigation treatments on yield and most soil chemical properties. Moderate deficit irrigation improved water use efficiency and maintained soil fertility within optimal ranges, moderate deficit irrigation is a viable and sustainable strategy for maize production in Awka, as it reduces water use while maintaining high yield and improving nutrient retention.
PARAMETRIC OPTIMIZATION OF INJECTION MOLD SETTINGS FOR THE WEIGHT EFFICIENCY OF POLYPROPYLENE PLASTIC CUPS USING RESPONSE SURFACE METHODOLOGY Chukwunedum Ogochukwu Chinedum; Anizoba Daniel Chinazom; Okpala Chukwunonso Divine
Jurnal Inovasi Teknologi dan Edukasi Teknik Vol. 6 No. 1 (2026)
Publisher : Universitas Ngeri Malang

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Abstract

This novel study focuses on the parametric optimization of injection mold settings to enhance the quality of polypropylene plastic cups. A model for the optimal injection mold settings, including cooling time, mold temperature, injection pressure, and injection speed (independent variables), was developed using the response surface methodology (RSM) to optimize the polypropylene plastic cup weight (dependent variable). Weight is an essential parameter in polypropylene plastic cups, directly influencing their durability, cost, and functional application. RSM was used for the experimental design, comprising multiple iterations of mold trial testings with variations in the input variables. The RSM model developed in this study produced the following optimal solutions for the input factors: cooling time – 15s; mold temperature – 57.270 °C; injection pressure – 95 MPa; and injection speed – 50 mm/s. The optimal solution for the response variable, weight, from the RSM analysis is 32.06g. The RSM analysis produced a global desirability (Dg) of 1 (100%) for achieving the optimal solutions. The RSM model explains 80.61% of the variance in the response variable, which is a strong contribution, as indicated by the coefficient of determination (R2). The selected model was the quadratic model, as indicated by the analysis of variance (ANOVA). The square (quadratic) term of the cooling time input factor and the interactive term between the cooling time and injection pressure were the two factors that had the most significant impact on the weight response variable of the finished polypropylene plastic cup product, as shown by the ANOVA. It is recommended that manufacturers implement the optimal solutions determined in this study in their production. This approach will mitigate waste and imperfections in plastic cups and allied products when implemented in injection molding. This study demonstrated the feasibility of determining optimal mold settings and materials to enhance product quality through the design of experiments (DOE).
DEVELOPMENT OF AN IOT-ENABLED REMOTE HEALTH MONITORING SYSTEM USING BIOMEDICAL SENSORS AND CLOUD COMPUTING Zainab Abbas Fadhil
Jurnal Inovasi Teknologi dan Edukasi Teknik Vol. 6 No. 3 (2026)
Publisher : Universitas Ngeri Malang

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Remote health monitoring is now a viable computer-engineering approach for overcoming the challenge of maintaining a continuous view of a person’s vital signs when not in a hospital or other medical facility. Here, we present a computer engineering framework for a replicable IoT-enabled remote health monitoring system consisting of biomedical sensors, an embedded acquisition node, secure wireless communication, cloud data storage, and a caregiver review dashboard. This work is not intended as an approved medical device; instead, it presents a technical prototyping and simulation framework that illustrates a computer engineering pathway for system designers and architects, demonstrating how the sensing, communication, networking, data handling, security, and alert functions can come together. Our design features a wearable sensor node acquiring ECG, SpO2, HR, temperature, and motion-based activity indicators. Local filtering, packetization with quality flags, secure over-the-air transmission via MQTT or HTTPS, cloud data storage, and data interpretation as structured observations viewable by authorized individuals are employed. We introduce a transparent performance model to quantify the system load requirements, latency, duty cycle of the acquisition node, probability of dat FHIR a loss, and alert response time. Under assumptions specified herein, this model suggests a typical WiFi usage resulting in approximately 300 milliseconds of end-to-end transmission latency for the normal periodically sampled readings, while a busy cellular transmission may be acceptable for passive monitoring if coupled with buffering. We show that the quality of a remote monitoring platform stems more from the interdependent selection of sampling rates, packet sizes, communication technologies and security parameters, than from individual sensor technology selections alone
APPLICATION OF THE TOPSIS DECISION MODEL FOR EVALUATING SUSTAINABILITY OF RAINWATER HARVESTING SYSTEM IN AWKA URBAN, NIGERIA Okadigwe Emmanuel Igwebudu; Chukwuma Emmanuel Chibundo; Ogbuagu Nneka Juliana; Nwanna Emmanuel Chukwudi
Jurnal Inovasi Teknologi dan Edukasi Teknik Vol. 6 No. 4 (2026)
Publisher : Universitas Ngeri Malang

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Abstract

The abstract should be written in both English and Indonesian in one paragraph consists of maximum 250 words. The abstract should explain the purpose, method, and the result of the research concisely. An abstract should stand alone, means that no citation in the abstract. The abstract should be written in both English and Indonesian in one paragraph consists of maximum 250 words. The abstract should explain the purpose, method, and the result of the research concisely. An abstract should stand alone, means that no citation in the abstract. The abstract should be written in both English and Indonesian in one paragraph consists of maximum 250 words. The abstract should explain the purpose, method, and the result of the research concisely. An abstract should stand alone, means that no citation in the abstract. The abstract should be written in both English and Indonesian in one paragraph consists of maximum 250 words. The abstract should explain the purpose, method, and the result of the research concisely. An abstract should stand alone, means that no citation in the abstract.

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