Jurnal Inotera

Spatial Autocorrelation Analysis of Nutrition Personnel as a Basis for Environmental Health Management in East Java

Carri Noer Fida Yanik — Fri, 02 Jan 2026 06:57:30 +0000

Nutrition professionals are essential for delivering effective nutrition interventions, yet their distribution is often uneven across regions. In East Java Province, Indonesia, evidence on the spatial structure of the nutrition workforce remains limited. This study aims to examine the spatial distribution of nutrition personnel across districts and municipalities in East Java, to (1) assess the presence of global spatial autocorrelation and (2) identify local clusters of relative surplus and deficit. A cross-sectional ecological design was applied using data on the number of nutrition workers in 38 districts/municipalities. Each unit was georeferenced using centroid coordinates. A K-Nearest Neighbors (KNN) spatial weights matrix was constructed based on geographic proximity and row-standardized. Global spatial autocorrelation was evaluated using Moran’s I with permutation tests, while Local Indicators of Spatial Autocorrelation (LISA) were used to detect significant local clusters and spatial outliers. Results were visualized through Moran scatterplots and LISA significance and cluster maps generated in R. Moran’s I indicated weak and statistically non-dominant global spatial autocorrelation, suggesting an absence of strong province-wide clustering. However, LISA revealed distinct local patterns. High–high clusters of nutrition personnel were concentrated in the metropolitan core, particularly around Surabaya, Sidoarjo, and Gresik, whereas several southern, western, and peripheral districts formed low–low clusters, indicating contiguous areas of relative deficit. Isolated high–low and low–high outliers were also identified. The distribution of nutrition personnel in East Java is characterized by modest global dependence but marked local inequalities. Integrating spatial analysis into human-resources-for-health planning can support more targeted and equitable allocation of nutrition workers, especially towards identified low–low clusters and spatial outlier districts.

Design and Implementation of a Cryptography Key Management System API Using SoftHSM and PKCS#11

Rivaldo Hardiansyah, Nurhasanah, Fadly Ariadi — Tue, 06 Jan 2026 02:20:59 +0000

This paper presents the design and implementation of a Cryptography Key Management System (KMS) API that leverages SoftHSM as secure key storage and the PKCS#11 (Cryptoki) standard as the cryptographic interface. Motivated by the need to protect sensitive organizational data and to comply with regulations, the system centralizes key lifecycle operations—generation, storage, use for AES-based encryption/decryption, and key destruction—so that key materials never leave the HSM. The study follows a waterfall-style development process comprising requirements analysis, system design, implementation, testing, and evaluation. Results show the API correctly performs cryptographic operations with keys resident in the HSM and supports basic auditing of operations. The approach demonstrates a practical, low-cost alternative to physical HSMs for small-to-medium environments while aligning with information security management practices.

Mineral Identification of Iron Ore Deposits in Menggamat, South Aceh through Mineralogical Analysis

Mislina Alif, Balkhaya, Dian Maulina , Afdhal, Hasbaini — Fri, 09 Jan 2026 03:39:53 +0000

Iron ore mineralization in the Menggamat area, Kluet Tengah District, South Aceh Regency, has been exploited by local communities; however, detailed mineralogical studies remain limited. This study aims to identify the main ore minerals, associated minerals, microscopic textures, and paragenetic sequence of iron ore deposits using an integrated mineralogical approach. Field investigations were conducted in Simpang Dua and Simpang Tiga villages, where 31 rock samples were collected through channel sampling, chip sampling, and grab sampling methods. Macroscopic observations were followed by petrographic and mineragraphic analyses using reflected and transmitted light microscopy. The results indicate that magnetite and hematite are the dominant iron ore minerals, accompanied by sulfide minerals such as pyrite and chalcopyrite. Gangue and alteration minerals include quartz, garnet, and carbonate minerals. Mineragraphic observations reveal abundant replacement, crosscutting, intergrowth, and inclusion textures, indicating a multistage mineralization process. Magnetite represents the earliest mineral phase, subsequently replaced by hematite through oxidative alteration, followed by metasomatic replacement by garnet and late-stage quartz veining. These mineralogical characteristics and textural relationships suggest that the iron ore deposits in the study area are genetically related to skarn-type mineralization associated with hydrothermal and metasomatic processes. The results provide essential baseline data for sustainable mineral resource management and preliminary environmental assessment in South Aceh.

Analysis and Design of Android-Based Guestbook Management Applications

Agus Heri Yunial, Ahmad Fauzi — Mon, 19 Jan 2026 04:36:35 +0000

In increasing security in residential areas it is not enough to improve security standards regarding incoming and outgoing guests, housing managers need to optimize the use of digitalization in standardizing security systems, one of which is by designing applications that can control incoming and outgoing guests, in order to prevent the occurrence of crime in cluster-type housing. This will be applied to the central and cluster mallorca phuket housing located in the Parung Panjang area, where in the process security monitoring can be carried out in real time from the cellphone by the manager. The application made is an android-based application that inputs incoming or outgoing guest data and take photos of the guest when entering and leaving. The database used is a spreadsheet, so that it is easy to read or make reports directly by most people if they want to directly access the database without the need for special skills such as SQL and so on. Application design uses codular which is open source and can make applications faster because it reduces the program coding process.

Integrating Internet of Things Technology to Enhance Highland Vegetable Productivity : A Systemic Review with Empirical Evidence from Aceh Tengah, Indonesia

Muhammad Ihsan, Herdi Susanto, Joli Supardi, Nuzuli Fitriadi — Tue, 27 Jan 2026 04:35:20 +0000

Global food security challenges necessitate transformative approaches to enhance agricultural productivity, particularly in highland regions facing multiple production constraints. This systematic literature review examines the potential of Internet of Things (IoT) technology integration to enhance productivity of highland vegetables (potato, cabbage, and carrot) in Aceh Tengah District, Indonesia. A critical agricultural region at 1,000-2,600 m.a.s.l. Following PRISMA guidelines, we analyzed peer-reviewed publications (2020-2025) on IoT applications in vegetable production, synthesizing evidence from successful implementations across diverse geographical contexts. Empirical evidence demonstrates that precision agriculture systems incorporating soil moisture sensors, nutrient monitoring, weather stations, and disease detection algorithms achieve productivity increases of 10-20% while reducing water consumption by 20-30% and input costs by 13%. However, IoT adoption in Indonesian highland agriculture remains below 5%, constrained by infrastructure limitations, digital literacy gaps, and economic barriers. This review identifies six critical research gaps and proposes a contextualized framework for IoT implementation adapted to smallholder farming systems in highland Indonesia. The framework addresses technological, socioeconomic, and institutional dimensions essential for sustainable digital transformation of highland agriculture. A pilot project framework is proposed targeting productivity enhancement, resource efficiency, and capacity building for sustainable implementation in Aceh Tengah's unique agroecological context

Adaptive Fiscal Policy for Indonesian Coffee: A Reduced State-Space Linear Quadratic Tracking Approach

Fri, 30 Jan 2026 01:35:26 +0000

Coffee serves as a strategic commodity for Indonesia's non-oil and gas exports; however, its market dynamics are characterized by high volatility due to global price fluctuations and climate change-induced production uncertainties. Previous research has primarily utilized simultaneous equation models and static optimal control to manage export taxes. A critical limitation of these approaches is their reliance on open-loop strategies, which lack resilience against real-time stochastic disturbances. This study bridges the gap between econometrics and modern control theory by transforming the structural econometric model of the Indonesian coffee market into a reduced state-space form. We propose a Finite-Horizon Linear Quadratic Tracking (LQT) approach to design an adaptive fiscal policy. Unlike static optimization, this method synthesizes a feedback control law that automatically calibrates tax rates in response to market deviations. Simulation results for the 2025–2030 period demonstrate that the LQT-based controller reduces the Sum of Squared Errors (SSE) by 40% compared to traditional open-loop methods and exhibits superior robustness against supply-side shocks. This research provides a novel, robust decision-support tool for policymakers to maintain economic stability under uncertainty.

Caesar Chiper Algorithm In Message Security

Wasis — Mon, 02 Feb 2026 01:28:44 +0000

The Caesar Cipher algorithm is one of the classical cryptography methods used to secure messages with letter substitution techniques based on certain shifts in the alphabet. This study aims to analyze and implement this algorithm in message security in order to understand its effectiveness and limitations in the world of information security. The methods used include encryption and decryption processes with character shifts according to the specified key. Implementation is carried out using the Python programming language as a case study. The results of the study show that Caesar Cipher is effective in providing basic security for messages, but has significant weaknesses against brute force attacks because it only has 25 possible keys. Therefore, this algorithm is more suitable for use as a basis for learning in the field of cryptography or combined with other security methods to increase its level of security.

The Effectiveness of Vibrating Screen on the Composition of Feeds at PT KSP AGRO

Wed, 25 Feb 2026 05:34:49 +0000

Vibrating screen is a filter unit that plays an important role in clarification stations because it functions to separate coarse impurities from crude oil so that the quality of the oil is improved and the oil loss can be minimized. The data used in this study is in the form of bait composition consisting of oil, water, and NOS in several observation periods. The data was then evaluated to determine the relationship between the variation in the composition of the feed and the effectiveness of the resulting filtering. The results of the study show that the effectiveness of vibrating screen tend to fluctuate in each observation period. Effectiveness increases when the oil content in the feed is higher, as the oil is more easily separated from impurities.

Design and Implementation of a Mobile-Based Islamic Book Study Information System Using API Architecture and Flutter Framework at Dayah Aqil Al-Farisi

Mizanul Ahkam Ahkam, Kurniawati, Elfisa, Riska Gianda, Abubakar, Fahmi Sara — Wed, 25 Feb 2026 06:16:47 +0000

The development of mobile-based Islamic learning applications has become a solution to support independent study at Dayah Aqil Al-Farisi, especially for santri and community members who are often unable to attend in-person study sessions due to daily activities. This application, built using the Flutter framework and Laravel as the backend, provides digital access to classical Islamic texts (kitab), prayers, Islamic jurisprudence (Fiqh), and the biography of the Prophet Muhammad SAW. The system utilizes an API architecture to enable seamless communication between the mobile app and the server, allowing users to access study materials anytime and anywhere via smartphones. The design and implementation process include requirement analysis, system modeling with Data Flow Diagrams (DFD), UI/UX design, and integration with a MySQL database. The application also features an admin panel for managing content such as kitab, news, prayers, and Fiqh materials. The result is a user-friendly platform that facilitates self-paced learning and helps preserve traditional Islamic education in a modern digital format. This study concludes that the mobile application effectively addresses attendance issues and enhances accessibility to Islamic teachings.

Protein Content and Glycemic Index of Snack Bars from Pigeon Pea and Yellow Sweet Potato

Nur Afni, Riezka Zuhriatika Rasyda, Lingga Gita Dwikasari — Sun, 01 Mar 2026 06:37:17 +0000

This study investigates the potential of Indonesia’s indigenous crops, pigeon pea and yellow sweet potato, for the development of nutritious snack bars with desirable protein content and glycemic index (GI). Eleven formulations with varying ratios of pigeon pea and yellow sweet potato (0%:100% to 100%:0%) were produced and analyzed for protein content using AOAC methods and for GI using glucose as the reference standard. Data were evaluated using one-way ANOVA followed by DMRT at a 5% significance level. Protein content ranged from 3.05 ± 0.01% to 13.64 ± 0.19%, while GI values spanned from 14.00 ± 0.65 to 76.00 ± 0.14. Increasing the proportion of pigeon pea resulted in a concurrent rise in both protein content and GI, indicating a strong positive correlation between these parameters and highlighting the challenge of formulating high-protein, low-GI snack bars from these ingredients. The findings indicate that thermal processing may enhance starch digestibility, thereby contributing to elevated GI in formulations with high pigeon pea content. A key limitation of this study is the absence of detailed analysis of processing-related factors such as heating intensity, matrix modification, and starch gelatinization that may influence glycemic response. Further investigation is required to elucidate these mechanisms.

Performance Identification of Eutectic Fatty Acid-PLA Based Phase Change Material Board Installed in a Mini-Cubicle System

Nurhanifa Aidy, Lindawati, Iqbal, Mahyuddin, Muhtadin, Muhammad Faisal, Yusrizal — Tue, 03 Mar 2026 06:01:16 +0000

Thermal comfort regulation in buildings located in hot climates, such as Indonesia, remains highly dependent on air conditioning (AC) systems, leading to substantial energy consumption. Integrating Phase Change Materials (PCM) into building envelopes offers a passive thermal management strategy to reduce cooling loads. This study investigates the thermal performance of a gypsum-based wall incorporating a eutectic fatty acid PCM (laurate–stearate) of 85:15 (wt%) modified with polylactic acid (PLA) at three PCM:PLA ratios (1:0.6, 1:0.8, and 1:1), alongside a control sample without PCM. Samples were fabricated at laboratory scale and evaluated using a mini-cubicle system under controlled charging and discharging conditions. Energy performance was assessed through temperature change rates and heat transfer (q) analysis at three measurement points (T1, T2, T3). Results demonstrate that PLA modification significantly enhances PCM performance, with the 1:0.8 ratio (bPCM) exhibiting optimal behavior. During charging, bPCM achieved the lowest temperature change rates of 4.75 °C/h at T1, 1.15 °C/h at T2, and 0.65 °C/h at T3 and the minimum heat transfer from T2 to T3 of 32.049 J. Similarly, during discharging, bPCM maintained the smallest temperature change rates of 2.2 °C/h at T1, 1.0 °C/h at T2, and 0.65 °C/h at T3 with the lowest heat transfer to the indoor zone of 32.033 J. These findings confirm that optimized PLA-modified eutectic PCM significantly improves heat absorption, latent heat storage, and thermal insulation performance compared to non-PCM and non-optimized compositions. The proposed composite wall system demonstrates strong potential for passive cooling enhancement and building energy efficiency improvement in hot-climate regions

Design and Development of an RFID-Based Student Attendance System Using Student ID Cards as Identification Media and Local Mysql Recording

Reza Irhamna, Lili Kasmini, Khairuman — Wed, 04 Mar 2026 03:58:20 +0000

This study aims to design and develop an RFID-based attendance system as a solution to the problems of conventional attendance systems, such as time inefficiency, cheating, and data loss. The system uses student ID cards (KTM) as an identification medium, is integrated with the ESP32 microcontroller and RC522 RFID reader, and is connected to a MySQL database through a website. The methodology used is research and development (R&D) with a prototype approach that includes requirement analysis, system design, implementation, and testing. Test results show that the system can read RFID cards accurately within an average time of 0.1 seconds and store attendance data in real time. System validation by experts using Aiken’s V method obtained an index value of 0.982, indicating a very valid system. User testing involving 15 students resulted in an average score of 4.85 out of 5, indicating that the system is very feasible and easy to use. This RFID-based attendance system is expected to improve efficiency and transparency in student attendance management.

Improvement of Songkok Production Process Through Defect Analysis Using Seven Tools and Failure Mode and Effect Analysis (FMEA)

Sofiyanurriyanti, Azwanda, Mahmud Basuki, Moh. Ainul Fais, Silvana Mohamad — Wed, 04 Mar 2026 08:04:58 +0000

Product defects contribute to material waste, delays in delivery, and increased production costs. This study aims to identify the causes of product defects and reduce defect levels in songkok (traditional cap) production at CV PPI using the Seven Tools method and Failure Mode and Effect Analysis (FMEA). Data were collected in August 2025, revealing three main types of defects: untidy stitching (29.47%), inaccurate sizing (32.11%), and velvet surface defects (38.42%). Defect analysis was conducted using Seven Tools, while corrective actions were determined through FMEA by calculating the Risk Priority Number (RPN). The findings show that the highest RPN value was 210 for inaccurate sizing, followed by untidy stitching (RPN 168) and velvet surface defects (RPN 140). Improvement recommendations include stricter supervision during production, periodic evaluation of tools and materials, revision of inadequate Standard Operating Procedures (SOPs), and proper selection of velvet materials that meet quality standards to ensure product consistency and customer satisfaction.

Comparison of Reinforcement Waste of Columns and Beams in the Ditsamapta Building North Sumatra Regional Police Using Conventional Method and COP

Kevin Ghozali, Agung Nur Wahid Btr, Rhini Wulan Dary — Mon, 09 Mar 2026 03:29:19 +0000

Material is one of the most important resources in construction projects, contributing 40–60% of the total cost. Reinforcing steel often leaves excess material due to cutting errors, so optimization is needed to minimize waste. This study aims to compare waste calculation using the conventional method and Cutting Optimization Pro (COP) software through a bar bending schedule. The results show that the conventional method produced waste of Ø8 14.102%, Ø10 9.480%, D10 8.385%, D12 10.444%, and D16 9.500%. With COP, the waste decreased to Ø8 2.888%, Ø10 1.855%, D10 8.087%, D12 6.980%, and D16 5.756%. Overall, the use of COP was able to reduce waste by about 5% compared to the conventional method.

Web-Based Inventory Information System at Mitra Com Electronics Business

Aryan Fauzi, Khairuman, Mukhroji — Tue, 10 Mar 2026 06:35:50 +0000

An inventory information system is important for helping Micro, Small, and Medium Enterprises (MSMEs) manage stock data accurately and efficiently. MSME Mitra Com still uses manual stock recording, which often causes data errors, delays in reporting, and difficulties in monitoring inventory conditions. This study aims to develop a web-based inventory information system to support stock management activities at MSME Mitra Com. The research method used is software engineering with a qualitative descriptive approach. The research stages include system requirement analysis, system design using Unified Modeling Language (UML), system implementation using PHP and MySQL, and system testing using the Black Box Testing method. The results show that the developed system can manage item data, record incoming and outgoing goods, and generate inventory reports automatically. The system helps improve work efficiency, reduce recording errors, and support decision-making at MSME Mitra Com.

Geographic Information System (GIS)-Based Health Service Search Information System in Banda Aceh City

Ilham Firdaus, Mukhroji, Khairuman — Wed, 11 Mar 2026 03:41:13 +0000

The rapid development of information technology has encouraged improvements in public service delivery, particularly in the health sector. However, residents of Banda Aceh City still experience difficulties in accessing fast, accurate, and integrated information regarding the locations and services of health facilities. This study aims to design and develop a web-based health service information system integrated with a Geographic Information System (GIS) to support public access to health facility information and assist data management at the Aceh Health Office. The system was developed using the Waterfall model, which includes requirement analysis, system design, implementation, testing, and maintenance stages. The proposed system provides an interactive digital map displaying hospitals and community health centers (puskesmas), complete with facility details, service types, and route navigation features. System testing using the black box method indicates that all main system functionalities operate according to user requirements. The results show that the system improves accessibility to health service information and supports more efficient management of health facility data in Banda Aceh City.

Development of an Interactive Website as an Information and Product Ordering Medium for Raja Konveksi Engineering Aceh MSME

Fadlal Ramadhan Farabi, Mik Salmina, Ully Muzakir — Wed, 25 Mar 2026 15:15:30 +0000

This study focuses on the development of an interactive website designed to function as an information and product ordering medium for Raja Konveksi Engineering Aceh MSME. This research was conducted in response to the absence of an official online platform, where promotional activities and product orders were previously handled manually through photo sharing and direct communication, resulting in limited efficiency and reach. The system was developed using the Waterfall method, encompassing requirement analysis, system design, implementation, testing, and maintenance stages. The website was built using PHP with the CodeIgniter framework, supported by a MySQL database, and integrated with HTML, CSS, JavaScript, and Bootstrap to enhance interactivity and responsiveness. System evaluation was carried out through a user satisfaction questionnaire involving 25 respondents. The findings indicate a satisfaction rate of 95.52%, categorized as very high. This result demonstrates that the developed website effectively supports information delivery and online product ordering. The implementation of this system is expected to strengthen digital promotion, broaden market access, and improve the efficiency of the ordering process for Raja Konveksi Engineering Aceh.

Reduction of Sink Mark Defects in Injection Molding of Polyoxymethylene (POM) Through Thermal Modeling and Process Parameter Optimization

Sat, 28 Mar 2026 12:28:11 +0000

This study aims to minimize sink-mark defects in polyoxymethylene (POM) injection-moulded products through thermal modelling and process parameter optimization. The end-of-packing temperature (T_EOP) was estimated using a one-dimensional transient cooling model. At the same time, the specific volume at the end of packing (v_EOP) was calculated using the Two-Domain Tait Equation of State. Volumetric (S_V) and linear shrinkage (S_L) were derived following Chen’s shrinkage framework. Results showed that v_EOP ranged from 0.1640 to 0.1764 m³/kg, S_V ranged from 13.30 to 19.40%, and S_L ranged from 4.64 to 6.94%. Higher T_EOP correlated with increased v_EOP and higher shrinkage, indicating ineffective packing. Optimization revealed that a melt temperature of 203.41 °C, combined with T_EOP of 145.02 °C and a cooling temperature of 16 °C, produced zero shrinkage in the model. These findings provide a quantitative basis for defining process control limits for melt temperature, coolant stability, and packing conditions to reduce sink marks and improve dimensional consistency of POM products.

Comparison of LSTM and Naïve Bayes in Google Play Store App Review Sentiment Analysis

Endar Nirmala, Andri Fahmi — Tue, 31 Mar 2026 08:08:04 +0000

The development of mobile application technology has driven increased user interaction through digital reviews on the Google Play Store platform. The review contains opinions that reflect the user's level of satisfaction, experience, and complaints about the app. However, the large number of reviews and variations in language expressions make manual analysis inefficient and potentially subjective. The main problem in this study is how to determine the most effective sentiment classification model to accurately identify users emotional tendencies. This study aims to compare the performance of the Naive Bayes method as a conventional machine learning model with Long Short Term Memory (LSTM) as a deep learning model based on word order in analyzing the sentiment of user reviews of Google Play Store applications. The dataset used comes from Google Play Store Reviews and goes through a pre-process process that includes text cleanup, tokenization, stopword removal, and sentiment labeling based on rating scales. The Naive Bayes model is trained using the TF-IDF representation, while the LSTM model uses an embedding sequence with standardized input padding. Evaluation uses accuracy metrics and F1-score with a ratio of 80 : 20 to train and test data distribution. The test results showed that the Naïve Bayes model achieved an accuracy of 65.78% with an F1 score of 0.5589, while the LSTM only achieved an accuracy of 45.26% with an F1-score of 0.2077. Thus, Naive Bayes was established as the best model in this study

Development of a Web-Based Tourism and Culinary Promotion Information System Using the Waterfall Method: A Case Study of Aceh

Ilham, Rita Novita, Khairuman — Fri, 03 Apr 2026 14:53:58 +0000

The rapid advancement of information technology has significantly influenced various sectors, including tourism and culinary industries, which are key drivers of regional economic growth. However, the promotion of Aceh’s tourism and culinary potential remains less effective due to the limited use of digital platforms. This study aims to design and develop a web-based information system for promoting Aceh’s tourism and culinary sectors as part of a digital investment strategy for the Aceh Investment and One-Stop Service Office (DPMPTSP). The system was developed using the Waterfall model through five stages: requirements analysis, system design, implementation, testing, and maintenance. The prototype was built using React.js for the front end and MySQL as the database; however, not all components are dynamic some website contents remain static to suit the needs of the institution and the scope of this research. The system provides integrated information about tourist destinations, traditional culinary products, and local events. Based on Blackbox testing, all features functioned properly according to specifications, and usability evaluation showed that the website is easy to use, efficient, and visually appealing. This research demonstrates that a semi-dynamic web-based information system can be an effective digital solution for promoting regional tourism and culinary potential while enhancing Aceh’s digital investment attractiveness.

Design and Construction of an Automatic Door System Based on Iris Detection Using Esp32-Cam and OpenCV Using the Rapid Application Development (RAD) Method

Nanda Angelika, Nurhasanah — Sun, 05 Apr 2026 04:18:07 +0000

Conventional home security systems typically depend on mechanical keys and passive CCTV cameras, which do not offer active access control or real-time response. This study presents the design and implementation of an automatic door system that uses iris recognition for authentication, developed with an ESP32-S3 camera and OpenCV, and integrated into a Flutter-based mobile application. The system was created using the Rapid Application Development (RAD) method to ensure flexibility and fast iteration. The prototype includes biometric iris authentication, solenoid-based door locking, live video monitoring, alarm activation, and real-time notifications. Through black-box testing, the system achieved high recognition accuracy, maintained stable operation in low-light environments, and successfully prevented unauthorized access using photo or video spoofing. Additionally, users receive instant alerts for failed access attempts or suspicious motion. The results show that integrating iris biometrics with IoT technology significantly enhances both home security and user convenience. Compared to traditional locks and CCTV systems, this approach provides a more intelligent, responsive, and secure solution for modern smart homes, offering users greater safety, automation, and peace of mind.

Application of Six Sigma to Reduce Defect in Tofu Products at UD Tahu Dua Saudara

Abdiel Khaleil Akmal, Jumelia Ardika, Dahnil Ikhwan, Zulia Ananda — Tue, 07 Apr 2026 02:37:39 +0000

Every company must experience problems related to the transportation sector. One of these problems is the TSP (Traveling Salesman Problem) where the problem is used in determining the shortest route with the requirement that the vehicles used must start and end at the same point. The above conditions were found in one of the companies engaged in the distribution of bottled water, especially the Kuades brand, located in Padang Panyang, Kuala Pesisir sub- district, Nagan Raya district, Aceh. The distribution system carried out by this AMDK company is not optimal because the distribution carried out only tries to meet the demand of each outlet or shop without taking into account the distance and travel time of the distribution. In this study using the Genetic Algorithm approach in solving problems in research. With this method, two results will be found, namely the shortest distribution path and the optimal cost. The use of the Genetic Algorithm method in solving the problem discussed provides results to achieve the optimal position, namely with the results of the shortest route is found in chromosome 2 in generation 1 being the best chromosome with a fitness value of 0.0016 and the length of the route traveled is 626 km, the optimal cost based on the distribution route that has been determined, the optimal cost result is Rp 1.38 Km Unit.

Smart Mangrove Monitoring for Resilience and Blue Carbon Governance

Abdurahman Kano Mohamad, Rustam Anwar, Romi Djafar — Tue, 07 Apr 2026 09:35:40 +0000

Mangrove ecosystems provide essential coastal protection, nursery habitat for fisheries, and blue-carbon services; however, many Indonesian coastal areas continue to experience degradation due to land conversion, pollution, and limited monitoring capacity. This article develops a technology-oriented, marine–fisheries governance approach for mangrove rehabilitation by integrating multi-source observation and decision support. The proposed framework combines multi-temporal satellite analysis (e.g., NDVI/NDWI and mangrove-specific vegetation indices), UAV shoreline mapping, and low-power Internet of Things (IoT) sensing to capture both spatial and in situ dynamics of habitat quality. IoT nodes are configured to continuously record salinity, temperature, turbidity, dissolved oxygen, and water level as operational indicators for fisheries-relevant ecosystem conditions, while remote sensing quantifies canopy cover recovery, fragmentation, and coastline change. A data pipeline is designed for near-real-time ingestion, quality control, and anomaly detection to enable early warnings and support evidence-based enforcement. To translate measurements into management actions, the study introduces measurable performance indicators aligned with rehabilitation targets, including seedling survival, canopy recovery rate, shoreline stabilization, and compliance with water-quality thresholds, complemented by community participation and institutional coordination metrics. Scenario analysis demonstrates that the integrated approach improves prioritization of restoration zones, reduces uncertainty compared with single-source assessments, and strengthens monitoring, reporting, and verification (MRV) for blue-carbon initiatives. The framework offers a scalable model for adaptive coastal management that connects ecological monitoring, fisheries sustainability, and governance accountability.

Analysis of Unemployment Patterns in Indonesia Using K-Means Clustering and Identification of Dominant Factors Using Random Forest

Yuliana , Rima Fazri Ramadhania, Asep Abdul Latip, Muhammad Farhan Harahapa — Sun, 12 Apr 2026 06:59:11 +0000

The disparity in the unemployment rate between provinces in Indonesia, exacerbated by the COVID-19 pandemic, is the main focus of this study. This study aims to (1) map the grouping of unemployment patterns in 34 provinces based on the Open Unemployment Rate (TPT) time series data for the 2020-2024 period, and (2) analyze the most significant socio-economic determinants of the formation of these patterns. Applying a two-stage methodology, cluster analysis using K-Means—validated through the Elbow Method and Silhouette Score of 0.456—succeeded in classifying the provinces into four different groups. The two prominent clusters identified were "Cluster 2: Pandemic Shock Pattern" (e.g., DKI Jakarta, West Java) which showed a surge in TPT above 10%, and "Cluster 3: Resilient Pattern" (e.g., Bali, DIY) which showed the lowest TPT rate and fastest recovery. Furthermore, the Random Forest Classifier analysis identified a hierarchy of determining factors, with the 2024 Average School Length (RLS) as the strongest predictor, followed by the 2024 Provincial Minimum Wage (UMP) and the 2024 GDP. These findings underline that the quality of human capital (education) is a more crucial factor than economic output (GDP) in shaping the resilience of the labor market. The study concludes the need for differentiated and cluster-specific unemployment policy interventions, rejecting a nationally uniform approach.

Analysis and Prediction of Student Academic Performance Using the Random Forest Algorithm

Donna Oktar Endras Wanto, Dede Sahrul Bahri — Sun, 12 Apr 2026 07:15:28 +0000

Student academic performance is one of the important indicators of success in the learning process. Therefore, a method is needed that can analyze and accurately predict students' academic performance. This study aims to analyze and predict students' academic performance using the Random Forest algorithm. The dataset used consists of 649 student records with 33 attributes covering student characteristics, family background, social activities, and academic grades. The students’ final grade (G3) is used as the target variable in the classification process.The research stages include data exploration, data preprocessing, splitting the data into training and testing sets, building the Random Forest model, and evaluating the model. The results show that the Random Forest model is able to achieve an accuracy rate of 92.31%. Testing using a confusion matrix indicates that the model has a relatively low prediction error rate. In addition, testing using the cross-validation method produces an average accuracy of 91.21%, indicating that the model has good stability. Feature importance analysis shows that previous academic grades, namely G2 and G1, are the most influential factors affecting students' academic performance. The results of this study indicate that the Random Forest algorithm can be effectively used to predict students' academic performance and can assist educational institutions in data-driven decision-making.

Classification of Heart Disease Based on Clinical Data Using the K-Nearest Neighbor Method

Abdullah Muhajir, Cendra Harmon — Sun, 12 Apr 2026 07:30:06 +0000

Heart disease is one of the leading causes of death worldwide; therefore, methods that can support early and accurate diagnosis are urgently needed. This study aims to classify heart disease based on patients’ clinical data using the K-Nearest Neighbor (KNN) method. The dataset used consists of patients’ clinical data, including attributes such as age, gender, blood pressure, cholesterol levels, maximum heart rate, and other medical attributes.The research stages include data preprocessing, transformation of categorical data into numerical form, data normalization using StandardScaler, and data splitting into training and testing sets with a ratio of 80% and 20%, respectively. The classification process is carried out using the K-Nearest Neighbor algorithm with a K value of 7. Model performance evaluation is conducted using a confusion matrix and evaluation metrics including precision, recall, f1-score, and accuracy.The results show that the KNN method is able to classify heart disease with an accuracy rate of 57%. The model demonstrates good performance on the majority class; however, its performance on the minority class remains low due to data imbalance and similarities in characteristics between classes. Therefore, the KNN method can be used as an initial approach for classifying heart disease based on clinical data, although further development is still required to improve model performance

Expert System for Diagnosing Monkeypox Using the Tsukamoto Method and Forward Chaining

Fingki Marwati, Ardianto — Mon, 20 Apr 2026 08:52:14 +0000

Monkeypox is a viral infectious disease that requires early detection to prevent wider transmission and ensure appropriate treatment. Limited public awareness and access to medical professionals may delay early diagnosis. Therefore, this study proposes the development of an Android-based expert system for early monkeypox diagnosis using the Forward Chaining inference method and the Tsukamoto fuzzy logic method. Forward Chaining is applied to perform rule-based reasoning based on user-input symptoms, while the Tsukamoto method is used to calculate the level of certainty of the diagnosis. The system was developed using the Waterfall model and tested with 20 case data samples. The evaluation results show that the system achieved an accuracy level of 85%, with 17 out of 20 diagnoses consistent with expert assessments. User testing involving 20 participants indicated that 90% of users found the application easy to use and informative. In addition, the system is capable of generating diagnostic results within 1–2 minutes, making it more efficient than manual consultation. The results demonstrate that the proposed system is effective and feasible as a decision-support tool for early monkeypox diagnosis.

Implementation of an Automatic Goods Delivery Scheduling System using a Heuristic Algorithm for Sinar Terang Buliding Store BSD

Cantika Ayu Fauziana, Galuh Saputri — Mon, 20 Apr 2026 14:58:57 +0000

This research aims to develop an automated delivery scheduling system for Toko Bangunan Sinar Terang BSD by applying a heuristic algorithm as an optimization approach for scheduling and route planning. The previous manual scheduling process often caused various inefficiencies, such as schedule conflicts, suboptimal route selection, longer travel times, and ineffective vehicle utilization. To address these issues, this study implements a heuristic algorithm capable of generating near-optimal solutions with fast computational time, especially for complex scheduling and distribution problems.The research process includes several stages: requirements analysis, system design, heuristic algorithm implementation, and system testing. The system is designed with a simple interface and structured workflow to ensure ease of use for store administrators. Black box testing demonstrates that all system functions operate according to the design, including data input, route determination, and automatic schedule generation. The implementation results show significant improvements in delivery efficiency, indicated by faster scheduling time, more optimal delivery routes, and better fleet utilization compared to the manual method. Therefore, the application of heuristic algorithms in the delivery scheduling system has proven effective in enhancing punctuality and service quality at Toko Bangunan Sinar Terang BSD. This study is expected to serve as a foundation for future system development, such as GPS integration and the use of more advanced optimization algorithms.

Numerical Modeling and Experimental Validation of Thermal Distribution in a Prototype Snakehead Fish (Channa striata) Extraction Chamber with Dual-Heater Configuration

Izhary Siregar, Ahmad Jibril, Setyawan Dwi Nugroho, Agus Purwanto — Tue, 21 Apr 2026 07:17:39 +0000

This study evaluates the thermal performance and extraction capacity of a developed steaming chamber utilizing a dual-heater configuration (2 x 200 W). A two-stage methodology was implemented: first, a numerical characterization using Computational Fluid Dynamics (CFD) to simulate convective heat distribution and fluid flow patterns; and second, an experimental validation using a physical prototype. The CFD results revealed a convection-dominated thermal field with a maximum wall temperature of 63.52°C and a center temperature of 55.22°C, maintaining a low thermal gradient of approximately 8.3°C. This uniformity ensured that fish samples remained at a stable exposure temperature of roughly 60°C during the initial heating phase. Experimental trials were conducted across a temperature range of 40–110°C and durations of 60–180 minutes. The results identified an optimal operating window between 80°C and 90°C for 120 minutes, yielding a peak extraction volume of 46.4 mL. Data trends indicated that while thermal energy is essential for liberating albumin from the tissue matrix, temperatures exceeding 100°C lead to a progressive decline in yield due to fluid evaporation and potential thermal degradation. Conversely, temperatures below 70°C proved insufficient for effective extraction. Qualitative chromatic analysis confirmed that the optimal 80–90°C range produced the most concentrated and opaque extracts.. The integration of CFD-based design and automated thermal control successfully demonstrates a robust framework for maximizing the recovery of thermosensitive fish essences in extraction chamber.

Islamic Study Schedule Search Website in Jakarta with Automatic WhatsApp Reminder Feature Using Extreme Programming Method

Fahmi Perdana Wicaksono, Galuh Saputri — Tue, 21 Apr 2026 08:33:56 +0000

This paper presents the development of a website for searching Islamic study schedules in Jakarta equipped with an automatic reminder feature via WhatsApp. The system is designed for Muslim residents in Jakarta to provide easy access to accurate and up-to-date information on Islamic study activities. Users can search schedules based on location, study theme, and preacher. The reminder feature is integrated with WhatsApp to automatically notify users before scheduled activities. The development follows the Extreme Programming (XP) methodology, which includes planning, design, coding, and testing. System testing demonstrates that all implemented features function according to requirements.

Environmental Carrying Capacity and Community-Based Governance of Mangrove Ecotourism in Tomini Bay

Rustam Anwar, Abdurahman Kano Mohamad , Syaiful Umela , Romi Djafar — Sat, 25 Apr 2026 02:10:29 +0000

Mangrove ecotourism is increasingly promoted as a pathway to reconcile conservation, livelihood diversification, and coastal resilience, yet destination growth often outpaces ecological thresholds, institutional capacity, and community readiness. Building on the literature review in the International Journals and incorporating recent studies compiled in Journals, this article presents an updated integrative review on the role of carrying capacity in sustainable mangrove ecotourism, with strategic implications for Tomini Bay, Indonesia. Using only the uploaded extraction sources, the review synthesizes advances in ecological suitability assessment, physical-real-effective carrying capacity, community participation, governance arrangements, social feasibility, and tourism management innovation across Indonesia and comparable settings. The synthesis shows that carrying capacity should not be treated merely as a visitor quota; it functions as a multidimensional governance instrument linking ecosystem integrity, visitor experience, local welfare, infrastructure limits, and enforcement capacity. Recent studies also reveal a persistent gap between technical suitability analysis and day-to-day management, especially in zoning, monitoring, promotion, digital visitor control, and benefit sharing. For Tomini Bay, the review proposes a conservation-first, community-based, and adaptive-capacity model that combines spatial zoning, phased visitor limits, ecosystem monitoring, participatory governance, and blue-economy livelihood integration. The article contributes a comparative evidence base, a strategic framework, and a research agenda for emerging mangrove destinations.