Jurnal Inotera

Analysis of Potential Hazards at Press Stations Using the Hazard and Operability Study (Hazop) Method at XYZ Palm Oil Mill

Azhar Basyir Rantawi — 2026-07-29

A preventive approach in identifying potential hazards in satiun presses in palm oil mills is very important to prevent work accidents. This study aims to analyze potential hazards at press stations in palm oil mills using the Hazard and Operability Study (HAZOP) method, identify the causes and impacts of each potential hazard found, determine the level of risk based on the results of risk assessments, and prepare appropriate control recommendations as an effort to improve occupational safety and health in the mill environment. The results of the study showed that the level of risk at the press station varied from the Medium category (exposure to hot steam/oil and scratches on the work tools), High (slipping on the floor/slippery stairs and electric shock), to the Extreme category which is very critical in the form of the potential for workers' hands to be pinched on the screw press machineduring cleaning (possibility: 3, severity: 5). As an effort to improve work safety, integrated control recommendations were formulated which include the implementation of strict cleaning SOPs, the implementation of the Lockout/Tagout (LOTO) system on machines and electrical panels, housekeeping improvements with the installation of anti-slip step nosing materials, and the obligation to use standard PPE in a disciplined manner.

A Systematic Review of IoT-Enabled Predictive Drying for Arabica Coffee: Toward a Python-Based Digital Twin Framework for the Gayo Highlands, Aceh Tengah, Indonesia

Muhammad Ihsan — 2026-07-30

Post-harvest drying is the single most decisive determinant of Arabica coffee quality, yet in the Gayo Highlands of Aceh Tengah (950 - 1,650 m.a.s.l.) it remains an experience based, weather dependent operation conducted largely on tarpaulins and open patios. High relative humidity, frequent rainfall, and low ambient temperature routinely prolong drying beyond ten days, produce non uniform final moisture content, and expose parchment to fungal colonisation and ochratoxin risk, causing smallholders to fail the 12.5% maximum moisture threshold of SNI 01-2907-2008 and to forfeit specialty price premiums. This systematic literature review, conducted following PRISMA guidelines on peer reviewed publications from 2019–2026, synthesises three research streams that have so far evolved in isolation: (i) thin layer drying kinetics of parchment coffee, (ii) Internet of Things (IoT) architectures for solar and hybrid dryers, and (iii) digital twin methodology in food and grain drying. The review finds that existing coffee drying IoT deployments are overwhelmingly reactive while validated kinetic models (modified Midilli, Page) capable of such prediction remain confined to laboratory dryers and are never coupled to field sensor streams. Digital twin research in drying has concentrated on grain and fruit, leaving coffee, and highland smallholder contexts in particular, unaddressed. From this synthesis the review derives seven research gaps and proposes SIKOPI-DT, a contextualised five layer Python based digital twin framework in which a modified Midilli kinetic core is continuously reparameterised by low cost IoT sensors (ESP32, SHT31, load cell) to forecast the time to target moisture content and to drive predictive supplementary-heat control under Gayo weather scenarios. Synthesised evidence indicates that such a system can plausibly reduce drying time by 30–50%, cut specific energy consumption by 15–30%, and improve moisture uniformity relative to open-sun practice. A three phase experimental validation roadmap and a smallholder economic feasibility analysis are presented, positioning this review as the theoretical foundation for a physical prototype in Aceh Tengah.

Factors Influencing The Choice Of Transportation Mode Between Tapaktuan And Banda Aceh

Rini — 2026-08-08

Abstract

The development of a region is always accompanied by growth in the transportation sector. Tapaktuan is a developing city. Many residents of Tapaktuan travel to the provincial capital, Banda Aceh. Along the way, they encounter various modes of transportation. The most preferred means of mobility are private cars or public transportation. This study aims to identify the factors influencing the public’s choice of transportation mode. The method used in this study is the ranking method. A total of 80 respondents were surveyed. Data analysis indicates that the variables influencing the choice of transportation options to Banda Aceh include travel time (214), cost/fare (212), vehicle facilities (195), waiting time (181), departure frequency (155), distance (134), and ticketing system (113).

Comparison of the Performance of Machine Learning Classification Algorithms on Phishing URL Detection

Ahmad — 2026-08-08

The development of internet technology has increased the intensity of digital activities, but it has also been followed by an increase in cybersecurity threats, one of which is phishing attacks through malicious URLs. Phishing is a fraudulent method that is carried out by manipulating users through fake websites that resemble official websites to obtain sensitive information, such as usernames, passwords, and financial data. Conventional blacklist-based detection methods are considered less effective in recognizing new phishing URLs that continue to develop dynamically. Therefore, this study aims to analyze and compare the performance of various machine learning and deep learning algorithms in accurately detecting phishing URLs. The dataset used was obtained from Kaggle with a total of 11,054 data points and 31 features that represent the characteristics of phishing and legitimate URLs. The methods used include Logistic Regression, K-Nearest Neighbor, Support Vector Machine, Naive Bayes, Decision Tree, Random Forest, Gradient Boosting, CatBoost, Extreme Gradient Boosting, and Multilayer Perceptron. The research stages include data preprocessing, exploratory data analysis, data visualization, separation of training and testing data, model training, and performance evaluation using accuracy, precision, recall, and F1-score. The results showed that the Gradient Boosting algorithm provided the best performance with an accuracy of 0.974, an F1-score of 0.977, a recall of 0.994, and a precision of 0.986. The results show that the ensemble learning method is able to detect phishing URLs effectively and can be used to improve artificial intelligence-based cybersecurity systems.

Analysis of Discipline and Learning Motivation of Students' Academic Achievement in the Digital Era Using a Linear Regression Model

Medina Fikanti — 2026-08-08

The technological era has drastically changed the educational landscape, providing easier access, but also creating significant challenges. Unlimited access to information can be a significant distraction, potentially reducing the effectiveness of student learning. This negative impact can lead to a decline in discipline and motivation to learn, two crucial internal components for academic success, especially in the context of digital education. Given the importance of discipline and motivation in students' academic adjustment in this modern era, this study aims to empirically test and analyze the impact of discipline and motivation to learn on students' academic performance in the digital era using a Multiple Linear Regression model.

Development of an Interactive Tourism Website for Simeulue Promotion

Sultanu Makrifat — 2026-08-08

Tourism is a strategic sector in supporting regional economic growth, making digital media increasingly important for promotion in the information technology era. Simeulue Regency has significant natural and marine tourism potential; however, its digital promotion media is still not fully optimized. This study aims to develop an interactive tourism website to support tourism promotion and improve public access to tourism information. The system was developed using the Agile Scrum method with an iterative sprint approach. The resulting website provides destination information, interactive maps, and dynamic content management features. Black-box testing results indicate that all core functions operate correctly without significant functional errors. Therefore, the system is considered feasible as a digital tourism promotion platform and can be further enhanced in future development.