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INDONESIA
Jurnal Info Sains : Informatika dan Sains
Published by SEAN INSTITUTE
ISSN : 20893329     EISSN : 27977889     DOI : -
Core Subject : Science,
Computer Science & IT
urnal Info Sains : Informatika dan Sains (JIS) discusses science in the field of Informatics and Science, as a forum for expressing results both conceptually and technically related to informatics science. The main topics developed include: Cryptography Steganography Artificial Intelligence Artificial Neural Networks Decision Support System Fuzzy Logic Data Mining Data Science
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 468 Documents
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Performance of the K-Means Algorithm for Water Quality Clustering Siska Simamora; Paska Marto Hasugian
Jurnal Info Sains : Informatika dan Sains Vol. 16 No. 02 (2026): Info sains, 2026
Publisher : SEAN Institute

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Abstract

Clustering is an unsupervised learning technique used to group data based on the degree of similarity among object characteristics. This study aims to analyze the application of a distance formula in cluster formation using the K-Means algorithm on the Water Quality Dataset. The dataset consists of 7,999 observations and 20 columns representing various water quality characteristics. The target column, is_safe, was removed, resulting in 19 features used in the clustering process. The preprocessing stages included checking for duplicate data, handling missing values, converting data into numerical format, and applying Min-Max normalization within the range of [0,1]. Normalization was performed to standardize the scale across features, ensuring that each feature contributed proportionally to the distance calculation. The clustering process was conducted using the K-Means algorithm, with data proximity determined based on the distance formula. The results indicate that data preprocessing and the selection of an appropriate distance formula are important factors in determining proximity patterns among objects and the resulting cluster formation. The use of normalized data can reduce the dominance of features with larger value ranges, thereby enabling the clustering process to represent data characteristics more proportionally. This study demonstrates that distance formula analysis plays an important role in supporting the formation of representative clusters in water quality data.
A WireGuard Mesh Overlay Resisting Internet Provider Port Policing Aviv Maghridlo; Nardi Nardi; Marzuki Sinambela
Jurnal Info Sains : Informatika dan Sains Vol. 16 No. 02 (2026): Info sains, 2026
Publisher : SEAN Institute

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Abstract

Overlay networks built on WireGuard can make dispersed devices appear to share one local network, but two obstacles remain: endpoints behind address translation are not directly reachable, and WireGuard's fixed default port is an obvious target for provider traffic discrimination. This study aims to design and empirically evaluate a hybrid overlay that mitigates both. We built WireGuard Manager, a single-binary Windows application combining a hub-and-spoke baseline with an opportunistic direct mesh over an in-process WireGuard data plane and host-orchestrated hole punching, and evaluated it on three physical nodes across two cities and three providers using throughput, latency, and packet-loss measurements. Results show that carrying the tunnel over the default port collapsed throughput to roughly 1–4% of a control port over the identical link (from 7.6–22.1 Mbps to at most 0.33 Mbps), while a randomized stealth port restored it; direct and relayed paths were validated independently through the observed time-to-live, and a live trace captured the automatic failover between them. A secondary result is that a direct path is not always superior to a well-provisioned relay. We conclude that provider port discrimination is a decisive, reproducible factor for such overlays and that a stealth-port strategy is an effective, low-cost mitigation, within the limits of a three-node case study.
Soil Microbial Diversity across Different Land-Use Types Using a Metagenomic Approach Kasmawati Kasmawati
Jurnal Info Sains : Informatika dan Sains Vol. 16 No. 02 (2026): Info sains, 2026
Publisher : SEAN Institute

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Abstract

The conversion of natural forests into agricultural land and monoculture plantations is a major driver of soil biodiversity loss in tropical regions, including Sumatra. Soil microorganisms are essential for nutrient cycling, organic matter decomposition, and soil fertility, yet their responses to land-use change remain insufficiently understood. This study analyzed the diversity and composition of soil microbial communities across four land-use types: natural forest, secondary forest/agroforestry, oil palm monoculture, and intensive agriculture. A quantitative comparative design was applied using 20 topsoil samples (0–20 cm). Microbial communities were characterized through Illumina-based 16S rRNA gene sequencing, followed by bioinformatic analysis in QIIME2 and statistical evaluation using one-way ANOVA and Principal Coordinate Analysis (PCoA). Microbial diversity declined significantly with increasing land-use intensity, with the Shannon index decreasing from 6.42 ± 0.21 in natural forest to 4.67 ± 0.19 in intensive agriculture (F = 18.7; *p* < 0.001). Taxa richness also decreased, accompanied by a shift in dominant phyla from Acidobacteria and Chloroflexi to Proteobacteria and Firmicutes. Soil organic carbon and total nitrogen were positively associated with microbial diversity. These findings demonstrate that land-use intensification reduces soil microbial biodiversity and highlight the importance of conserving natural vegetation and promoting agroforestry to sustain soil ecosystem functions.
Evaluating Mobile Mathematics Learning Application Success Using the DeLone–McLean Information Systems Success Model Ferawati Ferawati; Lilis Stianingsih; Fiqih Hana Saputri; Rudi Setiyanto
Jurnal Info Sains : Informatika dan Sains Vol. 16 No. 02 (2026): Info sains, 2026
Publisher : SEAN Institute

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Abstract

This study evaluates the success of the Math World mobile mathematics learning application implemented at SKh YKDW Tangerang using the DeLone and McLean Information Systems Success Model. A quantitative descriptive approach was employed involving 25 special education teachers as respondents. Data were collected through a questionnaire measuring six dimensions of information system success: System Quality, Information Quality, Service Quality, System Use, User Satisfaction, and Net Benefits. The data were analyzed using descriptive statistics based on percentage scores. The results indicate that the overall success level of the application reached 78.9%, which falls into the Good category. Among the six dimensions, User Satisfaction obtained the highest score (82.9%), followed by Information Quality (82.4%), while System Use recorded the lowest score (74.1%). The findings suggest that teachers perceive the Math World application as easy to use, providing accurate and relevant learning content that supports mathematics instruction for students with intellectual disabilities. However, improvements are still needed in system reliability, technical support responsiveness, and the integration of the application into regular classroom practice to maximize its educational benefits. Overall, the study concludes that Math World is an effective learning application with considerable potential to support inclusive mathematics education.
Development of a Web-Based Geographic Information System for Mapping and Monitoring the Spatial Distribution of Dengue Hemorrhagic Fever (DHF) Cases in Manado City Christian Fendy Sumangkut; Mans L. Mananohas; Eric Alfonsius; Eliasta Ketaren
Jurnal Info Sains : Informatika dan Sains Vol. 16 No. 02 (2026): Info sains, 2026
Publisher : SEAN Institute

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Abstract

Dengue Hemorrhagic Fever (DHF) remains a major public health concern in many regions of Indonesia, including Manado City. The spatial distribution of dengue cases is strongly influenced by environmental and geographical factors, highlighting the need for an information system capable of providing timely and accurate spatial data to support disease surveillance and control. This study aims to design and develop a web-based Geographic Information System (GIS) for mapping the spatial distribution of DHF cases in Manado City. The system was developed using the Waterfall software development model, which consists of the sequential phases of requirements analysis, system design, implementation, testing, and maintenance. The application was implemented using PHP as the programming language and MySQL as the database management system, while Leaflet.js and OpenStreetMap were utilized to provide interactive geospatial visualization based on GeoJSON data. The developed system enables users to visualize the spatial distribution of dengue cases through an interactive digital map, manage epidemiological data, and access statistical summaries via a web-based dashboard. Functional evaluation using Black Box Testing demonstrated that all major system functions operated correctly and fulfilled the specified requirements. The proposed GIS application provides an effective platform for spatial disease surveillance and supports evidence-based decision-making by public health authorities in planning and implementing dengue prevention and control strategies.
A Hybrid GRU-BiLSTM Deep Learning Framework for Solar Radiation Forecasting and Photovoltaic Energy Yield Assessment in Timor Island, Indonesia Yobel Eliezer Mahardika; Agustina Rachmawardani; Marzuki Sinambela
Jurnal Info Sains : Informatika dan Sains Vol. 16 No. 02 (2026): Info sains, 2026
Publisher : SEAN Institute

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Abstract

Timor Island in East Nusa Tenggara possesses abundant solar energy resources, yet the technical feasibility of solar power plant (PLTS) development in the region has rarely been assessed using data-driven quantitative methods. This study aims to develop and validate a hybrid GRU-BiLSTM deep learning model for short-term solar radiation forecasting, to assess whether this model can be reliably extended into long-horizon autoregressive projection, to estimate the solar radiation potential and photovoltaic energy production across five locations in Timor Island, and to characterize the radiation variability relevant to PLTS design. A hybrid GRU-BiLSTM deep learning model was developed and evaluated for short-term hourly solar radiation forecasting using ERA5 reanalysis data (2015-2025), achieving R² of 0.9507-0.9584 across five locations. Because chained autoregressive projection using this model was found to be unreliable for annual-horizon estimation (R² = -0.53, +46% overestimation), a climatological approach based on 2015-2025 historical averages was applied instead for potential assessment. The results show that the five locations possess high and relatively uniform solar potential, with annual totals ranging from 2,023 to 2,109 kWh/m² (5.54-5.78 kWh/m²/day), corresponding to estimated photovoltaic energy production of 273.1-284.8 kWh/m² per year. Coefficient of variation values (69.6-71.0%) indicate substantial short-term fluctuation despite the locations' consistent seasonal pattern, with the lowest production occurring in June and the highest in October. These findings provide a quantitative basis for PLTS capacity planning and energy storage design in Timor Island, demonstrating that a validated short-term forecasting model can be meaningfully extended into practical renewable energy resource assessment.
Development of a Web-Based Decision Support System for the Selection of Computer Laboratory Assistant Candidates Using Grey Relational Analysis Fauzi H. Simbolon; Maranata Pasaribu; Sariadin Siallagan; Jenheri Rejeki Tarigan
Jurnal Info Sains : Informatika dan Sains Vol. 16 No. 02 (2026): Info sains, 2026
Publisher : SEAN Institute

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Abstract

Selecting computer laboratory assistant candidates is a multi-criteria decision problem because the decision must simultaneously consider academic performance, subject mastery, technical competence, interpersonal communication, and teaching ability. This study aims to develop a web-based Decision Support System using Grey Relational Analysis (GRA) to produce an objective, transparent, and traceable candidate ranking. The study applies a quantitative-computational approach and prototype development. Five criteria are included: grade point average with a weight of 0.20, relevant course grade 0.25, competency or technical test 0.25, interview 0.15, and microteaching 0.15. The analysis consists of decision matrix construction, normalization, ideal reference sequence determination, deviation calculation, Grey Relational Coefficient, Grey Relational Grade, ranking, and sensitivity analysis of the distinguishing coefficient. The final ranking places A3 first with a GRG of 0.7536, followed by A5 at 0.7086, A1 at 0.6518, A2 at 0.6371, and A4 at 0.4333. A3 is the main recommendation because it has the highest weighted closeness to the ideal profile. The sensitivity analysis reported in the source manuscript indicates that A3 remains in first place when the distinguishing coefficient changes, suggesting that the primary recommendation is stable. The study contributes an integrated decision model that combines academic, technical, interpersonal, and pedagogical dimensions and a web-based system design that supports decision traceability. A complete numerical audit still requires the raw decision matrix and system calculation logs.
Performance Analysis of a Three-Blade Savonius Vertical-Axis Wind Turbine Prototype for Charging a 12 V 7 Ah Maintenance-Free Battery Ihat Solihat; Firmansyah Firmansyah
Jurnal Info Sains : Informatika dan Sains Vol. 16 No. 02 (2026): Info sains, 2026
Publisher : SEAN Institute

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The increasing demand for renewable energy has encouraged the development of small-scale wind energy conversion systems for standalone electricity generation. This study evaluates the performance of a three-blade Savonius vertical-axis wind turbine prototype in charging 12 V, 7 Ah Maintenance-Free and Flooded Lead-Acid batteries. Experimental testing was conducted indoors using a blower as the wind source with three wind source distances (100 cm, 150 cm, and 200 cm), corresponding to different wind speeds. The system performance was evaluated based on wind speed, generator rotational speed, electrical current, output power, power conversion efficiency, battery charging time, and battery endurance under lamp loads of 15 W, 25 W, and 30 W. The results showed that decreasing the distance between the wind source and the turbine increased wind speed, generator rotational speed, charging current, and electrical output power while reducing the battery charging time. The highest output power was obtained at the 100 cm distance with a charging current of 3.4 A and an output power of 10.8 W. The theoretical charging time ranged from 2.0 to 2.8 h; however, the actual charging time was longer because of electrical losses, charging controller characteristics, and battery operating conditions. Battery endurance decreased as the electrical load increased, indicating that higher discharge currents accelerated battery depletion. Overall, the prototype demonstrated the feasibility of using a Savonius vertical-axis wind turbine for small-scale battery charging applications, although improvements in turbine efficiency, energy conversion, and charging system performance are required to enhance practical performance.

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