cover
Contact Name
M. Miftach Fakhri
Contact Email
fakhri.abcollab@gmail.com
Phone
+6281343505565
Journal Mail Official
dtcs@abcollab.id
Editorial Address
Jalan Cempaka Mekar Raya No. 10 Bandung, Jawa Barat, Indonesia
Location
Kota bandung,
Jawa barat
INDONESIA
Journal of Digital Technology and Computer Science
ISSN : 30310318     EISSN : 30308127     DOI : https://doi.org/10.66053/dtcs
Digital Technology and Socio-Technical Innovation, including the design, development, implementation, and evaluation of digital solutions, platforms, applications, and infrastructures that support modern socio-technical systems, digital transformation, and technology-enabled services. Computer Systems, Software, and Networking, encompassing distributed systems, computer networks, network architectures, communication protocols, network performance, next-generation connectivity, software systems, and integrated computing environments. Artificial Intelligence, Machine Learning, and Intelligent Systems, covering intelligent systems, machine learning algorithms, deep learning, natural language processing, expert systems, knowledge-based systems, computational intelligence, and applied AI across scientific, industrial, and societal domains. Decision Support, Fuzzy, and Evolutionary Systems, including decision support systems, fuzzy logic, fuzzy control, evolutionary computing, optimization algorithms, swarm intelligence, hybrid intelligent methods, and data-driven decision models. Image, Audio, and Multimedia Processing, including computer vision, image processing, sound and speech processing, multimedia analysis, signal processing, pattern recognition, and audio-visual computing applications. Information Security and Cybersecurity, focusing on information security, system security, network security, cybersecurity governance, cryptography, privacy protection, secure software engineering, threat detection, intrusion prevention, digital forensics, and cyber risk management. Cyber Crime and Digital Investigation, including cybercrime detection and analysis, cyber law and policy in digital environments, forensic investigation, online fraud, identity theft, malicious activity analysis, and digital evidence management. Social Network and Digital Security, covering security and trust in social media and online platforms, digital identity, misinformation and disinformation detection, privacy in social networks, human factors in cybersecurity, and safe digital interaction ecosystems. Operating Systems, Computer Architecture, and Embedded Computing, including operating systems, processor and memory architecture, virtualization, system-level optimization, embedded systems, real-time computing, firmware, and performance engineering. Cloud, Edge, and Ubiquitous Computing, covering cloud platforms, fog and edge computing, distributed intelligence, service orchestration, scalable infrastructures, reliability, resource management, and pervasive computing environments. Internet of Things (IoT), Sensor Networks, and Cyber-Physical Systems, including smart devices, wireless sensor networks, industrial IoT, IoT platforms, connected environments, cyber-physical systems, and real-world deployment challenges in intelligent sensing and control. Big Data, Analytics, and Data-Driven Computing, encompassing data engineering, data mining, large-scale data processing, predictive analytics, visual analytics, business intelligence, and advanced computational methods for complex datasets. Wearable Devices and Smart Sensing Technologies, including wearable computing, body-area networks, health and activity monitoring systems, smart textiles, mobile sensing, and human-centered intelligent devices. Embedded Robotics and Microcontroller Systems, including robotic systems, embedded robotics, autonomous control, low-level hardware-software integration, microcontroller-based applications, robotic sensing, and intelligent actuation systems. Micro and Nano Technology, including microelectronics, nanoelectronics, microsystems, nanosystems, MEMS/NEMS-related applications, miniaturized intelligent devices, and sensor-oriented micro/nano technological innovations. Renewable Energy and Intelligent Energy Systems, including digital technologies for renewable energy, smart energy monitoring, intelligent control systems for energy efficiency, IoT-enabled energy systems, sustainable computing, and computational methods for energy optimization. Software Engineering and Information Systems, including software design, software quality assurance, software testing, requirements engineering, enterprise systems, information systems development, human-centered software solutions, and digital service integration. Robotics, Automation, and Autonomous Systems, covering intelligent robotics, automation systems, control engineering, autonomous agents, robotic perception, human-robot interaction, and smart manufacturing applications. Human-Computer Interaction and Digital Experience, including user interface design, user experience, usability evaluation, interactive systems, accessibility, persuasive technologies, and digital behavior in technology-mediated environments. Green Computing and Sustainable Digital Systems, including energy-efficient computing, sustainable software and hardware design, green AI, carbon-aware digital infrastructures, smart resource management, and digital technologies for environmental sustainability.
Articles 53 Documents
Crude Palm Oil Moisture Reduction: Design and Implementation of an Arduino UNO-Based Automated Heating Control System Syem Vicra Lumban Gaol; Andi Prayogi; Raden Aris Sugianto
Journal of Digital Technology and Computer Science Vol. 3 No. 2 (2026): April 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/dtcs.v3i2.987

Abstract

Purpose – Crude Palm Oil (CPO) quality is strongly influenced by moisture content because excessive water can accelerate hydrolysis, increase free fatty acid formation, promote oxidation, and reduce storage stability. This study aimed to develop and functionally evaluate a low-cost Arduino-based automated heating control prototype to support laboratory-scale CPO moisture-reduction experiments. Methods – This study employed a Research and Development method with a quantitative experimental orientation. The prototype integrated Arduino UNO as the main controller, DHT22 for ambient humidity monitoring, MAX6675 with a Type-K thermocouple for direct CPO temperature measurement, I2C 16×2 LCD for data display, a two-channel 5V relay for heater switching, a 350 W water heater, and LED-buzzer indicators. Functional testing was conducted through observation of sensor readability, LCD display, relay switching, heater response, and integrated system operation. Findings – The results showed that all main components operated according to their intended functions. The system could read humidity and CPO temperature, display real-time data, activate and deactivate the heater through relay control, and provide visual and audible indicators. Research Implications – The prototype provides a functional baseline for automated CPO heating control. However, it does not directly measure actual CPO moisture content because DHT22 only reads ambient humidity. Originality – This study offers a low-cost Arduino-based prototype for supporting CPO heating-control experimentation.
Web-Based Employee Records Governance for Document Traceability and Verification in Plantation Workforce Administration Contexts Natalia Fransiska Ginting; Ritna Wahyuni; Raden Aris Sugianto
Journal of Digital Technology and Computer Science Vol. 3 No. 2 (2026): April 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/dtcs.v3i2.988

Abstract

Purpose – Employee data administration at PT. Barumun Raya Padang Langkat Binanga Estate has traditionally relied on manual procedures, creating difficulties in information retrieval, document management, verification, and administrative processing. This study aims to develop a web-based Employee Data Management Information System supporting structured, centralized, secure, and efficient personnel administration. Methods – The study employed a Research and Development approach using the Waterfall model, consisting of requirements analysis, system design, implementation, testing, and evaluation. Unified Modeling Language was used to model system processes and database interactions. The application was developed using PHP and MySQL, while functionality was evaluated through Black Box Testing. Findings – The resulting system integrates employee biodata, family information, supporting documents, verification workflows, reporting functions, and role-based access control in a centralized platform. Functional evaluation involved 15 testing scenarios covering authentication, employee data management, document handling, verification, reporting, and user access control. All tested functions produced outputs consistent with the specified requirements, indicating that the system operated correctly. The platform is expected to improve data organization, document control, verification accuracy, and administrative accessibility. Research Implications – The system is limited to employee data and document management and does not include payroll, attendance, recruitment, or performance appraisal modules. Evaluation was also restricted to functional testing. Future studies should therefore assess usability, performance efficiency, reliability, security, and user satisfaction through empirical testing. Originality – This study contributes an integrated personnel administration platform designed for plantation company operations, combining biodata, family records, supporting documents, verification mechanisms, reporting, and role-based access within a single web-based environment.
SIM PSR: A Web-Based Monitoring Platform for Cooperative-Level Smallholder Palm Oil Replanting Program Management Syarifatu Assolehah; Ritna Wahyuni; Raden Aris Sugianto
Journal of Digital Technology and Computer Science Vol. 3 No. 2 (2026): April 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/dtcs.v3i2.1006

Abstract

Purpose – The Smallholder Palm Oil Replanting Program (PSR) seeks to improve the productivity of smallholder plantations by replacing aging oil palm trees with certified superior seedlings. However, monitoring at the cooperative level is often hindered by manual record-keeping and fragmented reporting, reducing the efficiency of supervising program implementation. This study aims to develop and evaluate a web-based monitoring information system for the PSR program at Koperasi Tani Makmur Berjaya, Air Hitam Village, North Labuhanbatu Regency. Methods – The system was developed using the Waterfall methodology with UML-based system modeling and implemented using PHP and MySQL. It supports three user roles administrator, field officer, and participant with permissions tailored to operational responsibilities. Functional performance was evaluated through developer-conducted Black Box Testing across 25 functional test scenarios involving administrator, field officer, and participant roles. Findings – Functional testing demonstrated that the proposed system supports the management of participant information, land data, documents, stage-based monitoring records, and PDF report generation under controlled testing conditions. It supports monitoring for 116 participants across approximately 480 hectares in five villages. Testing confirmed that all functions operated as intended without identified functional failures. Research Implications – The proposed system provides a centralized digital platform for cooperative-level PSR monitoring. However, the findings are limited to a single cooperative implementation and developer-conducted functional testing, without independent usability evaluation, independent or advanced security assessment, or long-term operational validation beyond the basic internal security checks conducted in this study. Originality – This research presents a web-based monitoring system specifically designed for cooperative-level PSR management in Indonesia, integrating role-based access control, stage-oriented progress monitoring, and automated report generation within a unified platform.
Exploring Visual Aesthetics and Immersive Cinematography in Documentary Film Production Using 360-Degree Camera Technology Anthony Y.M. Tumimomor; Ranang Agung Sugihartono; Pande Made Sukerta; Sunardi
Journal of Digital Technology and Computer Science Vol. 3 No. 3 (2026): August 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/dtcs.v3i3.656

Abstract

Purpose – This study investigates how 360-degree camera technology transforms visual aesthetics and immersive cinematography in the documentary The Story Behind the Truck’s Screech, documenting cultural expressions displayed on truck rear panels. Methods – The study employed an exploratory qualitative design combined with experimental creative practice. Data were collected through field observation, interviews with four truck drivers, one truck painter, and one truck owner, cinematographic testing using an Insta360 X3 camera, two focus group discussions, thematic analysis, and structured expert evaluation using a five-point Likert scale. Findings – The 360-degree camera expanded conventional single-frame cinematography into omnidirectional visual capture, strengthened viewer presence, and enabled reframing techniques such as point-of-view and tiny-planet effects. Eighteen FGD participants reported greater visual freedom and immersion. Expert evaluation produced scores of 5 for attention guidance, spatial quality and composition, visual comfort, and framing uniqueness, and 4 for visual aesthetic fidelity, yielding an overall mean of 4.8 out of 5. Research implications – The findings support the practical use of 360-degree cameras in documentary production, particularly for spatially contextual cultural documentation. However, interpretation is limited by purposive sampling, a single documentary case, and context-specific production conditions. Originality – This study integrates visual ethnography, experimental cinematography, audience response, and expert assessment to demonstrate how 360-degree technology functions as both a recording tool and an aesthetic strategy in Indonesian documentary filmmaking.
Development of an Android-Based QR Code Information System for Offline-First Palm Oil Harvest Recording in Plantations Bintang Permata Hati Simanjuntak; Raden Aris Sugianto; Andi Prayogi
Journal of Digital Technology and Computer Science Vol. 3 No. 3 (2026): August 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/dtcs.v3i3.791

Abstract

Purpose – Manual palm oil harvest recording at remote plantations often causes transcription errors, duplicate records, delayed reporting, and difficulties in implementing fully online data collection because of unstable Internet connectivity. This study aimed to design and develop an Android-based palm oil harvest recording information system using Quick Response (QR) Code identification and an offline-first data architecture. Methods – This study employed a Research and Development approach using the Rapid Application Development model. Data were collected through field observations, interviews with five foremen and one administrative staff member, documentation reviews, and functional system testing. The application was developed using Android Studio and Flutter, with SQLite for local offline storage and Firebase Cloud Firestore for online data synchronization. Findings – The developed system enables QR Code-based worker identification, harvest data input, offline data storage, automatic synchronization, digital signature validation, activity-log monitoring, and report export. Black-box testing of seven functional scenarios showed that all tested features operated correctly in both offline and online conditions. Research implications – The findings indicate that an offline-first mobile architecture can support harvest recording in plantation areas with limited connectivity and low-cost devices. However, the system was tested in one plantation environment; therefore, broader implementation requires further multisite evaluation. Originality – This study contributes by integrating QR Code identification, SQLite-based offline persistence, Firebase synchronization, and Android-based field reporting into a single harvest recording system for remote palm oil plantation operations.
Assessing climate-driven meteorological drought for sustainable water resources management using the standardized precipitation index under ENSO variability: Evidence from Way Kanan regency, Indonesia Ferdy Erwanda; Aprizal; Susilowati; Any Nurhasanah
Journal of Digital Technology and Computer Science Vol. 3 No. 3 (2026): August 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/dtcs.v3i3.1178

Abstract

Purpose: This study aimed to assess the spatial and temporal characteristics of meteorological drought using the Standardized Precipitation Index (SPI) and evaluate its implications for sustainable water resources management in Way Kanan Regency, Indonesia. The study also examined the association between major drought events and El Niño–Southern Oscillation (ENSO) phases and assessed changes in irrigation water requirements under drought conditions. Method: Monthly precipitation data derived from the PERSIANN-CCS satellite for the period 2003–2025 were used to calculate SPI at 1-, 3-, 6-, and 12-month time scales. Drought intensity, frequency, duration, and spatial distribution were analysed across four major rice-producing districts. Historical drought events were subsequently compared with ENSO phases using the Oceanic Niño Index (ONI), while irrigation water requirements were estimated using the CROPWAT 8.0 model under normal and drought conditions. Findings: The results identified 2003, 2015, and 2019 as the principal meteorological drought years, with SPI-3 providing the most representative assessment of seasonal agricultural drought. Pakuan Ratu exhibited the highest drought vulnerability among the study districts. Severe drought events consistently coincided with El Niño conditions, particularly during the strong 2015 event, and resulted in substantial increases in irrigation water requirements ranging from 57.8% to 65.2% relative to normal conditions. Scenario analysis further projected irrigation water demand increases of approximately 20–65% under future El Niño conditions, depending on event intensity. Research Implications: Integrating multi-temporal SPI assessment with seasonal ENSO monitoring provides a practical framework for strengthening drought early warning systems, optimizing irrigation scheduling, and supporting climate-resilient water resources management in tropical agricultural regions. Originality: This study presents an integrated district-scale framework that combines multi-temporal SPI analysis, climate variability assessment through ENSO comparison, and irrigation water demand modelling to support evidence-based and sustainable water resources management. Unlike previous studies that primarily focused on drought characterization, this research explicitly links drought severity with irrigation water requirements, providing actionable information for adaptive agricultural water management under increasing hydroclimatic variability.
Application of Fuzzy Multi Criteria Decision Making (FMCDM) and TOPSIS in Selecting Prospective Employees Lailatul Badria; Sriani
Journal of Digital Technology and Computer Science Vol. 3 No. 3 (2026): August 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/dtcs.v3i3.1132

Abstract

Purpose – The primary objective of this research is to design and build a web-based Decision Support System (DSS) to evaluate and hire prospective candidates at Perumda Tirtanadi. To achieve this, a hybrid methodology combining Fuzzy Multi-Criteria Decision Making (FMCDM) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is implemented. The proposed system is intended to reduce subjectivity and improve the effectiveness of the employee selection process. Methods – In this framework, FMCDM is utilized to translate subjective, linguistic evaluations into precise crisp values through a defuzzification process, which subsequently establishes the relative weights of the evaluation criteria. Afterward, these weights are integrated into the TOPSIS algorithm to calculate the final rankings of the applicants across nine specific benchmarks, namely GPA, Basic Competency Test (TKD), psychological test score, attitude, communication skills, work experience, politeness, field expertise, and personal development plan. The system was implemented as a web-based application using PHP and MySQL. Findings – The developed system successfully performed automatic FMCDM weighting and TOPSIS ranking. The ranking results were consistent with manual calculations, indicating that the proposed approach was correctly implemented and capable of producing accurate candidate rankings. Research implications – This study used recruitment data from a single organization, namely Perumda Tirtanadi Medan. Consequently, the applicability of the outcomes is restricted to the specific criteria and administrative environment of this particular utility company and may not be directly generalizable to other organizations. Originality – This study integrates FMCDM for criteria weighting and TOPSIS for candidate ranking into a web-based decision support system, providing a practical and objective approach to employee selection at Perumda Tirtanadi.
Sistem Penyiraman Otomatis Bibit Kelapa Sawit Berbasis IoT Menggunakan Metode Fuzzy Sugeno Berdasarkan Kelembapan Tanah Dan Suhu Adinda Puspita; M. Fakhriza
Journal of Digital Technology and Computer Science Vol. 3 No. 3 (2026): August 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/dtcs.v3i3.1141

Abstract

Purpose – This study aims to design and implement an IoT-based automatic irrigation system for oil palm seedlings capable of determining irrigation duration based on soil moisture and ambient temperature conditions. The research addresses the limitations of manual irrigation, which may cause water deficiency or excess in the growing medium. Methods – The study employed experimental and engineering methods using an ESP32 DevKit V1 microcontroller as the control center. The system utilized an FC-28 soil moisture sensor and a DHT22 temperature sensor. Sensor data were processed using the Sugeno Fuzzy Logic method with a nine-rule base to determine irrigation duration. A relay controlled a 5V DC water pump, while Telegram was used for system monitoring and control. Findings – The system successfully generated irrigation decisions with predefined singleton outputs of 0, 5, 10, and 15 seconds and correctly executed all implemented Telegram monitoring and control commands Research implications – The system is limited by the use of the FC-28 resistive soil moisture sensor, which is susceptible to corrosion and requires periodic recalibration, while remote monitoring depends on network availability. Originality – This study differentiates itself from previous work by implementing an explicitly specified ESP32 DevKit V1, a DHT22 temperature sensor, and Telegram-based monitoring and control, whereas previous research employed a DHT11 sensor and website-based monitoring without explicitly identifying the microcontroller while using the same fuzzy input parameters and Sugeno Fuzzy Logic method.
Decision Tree Classification of Fear of Missing Out Levels in Generation Z Technology Product Purchases Kalfida Eka Wati Siregar; Aidil Halim Lubis
Journal of Digital Technology and Computer Science Vol. 3 No. 3 (2026): August 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/dtcs.v3i3.1148

Abstract

Purpose – This study used a Decision Tree to classify score-defined Fear of Missing Out (FOMO) categories associated with Generation Z technology-product purchasing, identify discriminative questionnaire items, and evaluate the stability and interpretability of the classification structure. Methods – The dataset contained 500 respondents and 13 self-developed four-point Likert items. Corrected item-total correlations, Cronbach’s alpha, and a preliminary one-factor exploratory factor analysis were examined. A stratified 80:20 split was used for an unpruned Decision Tree and a cost-complexity-pruned sensitivity model selected by five-fold training-only cross-validation. A deterministic score rule, root-split information gain, model-wide importance, and 100 repeated stratified splits were also evaluated. Findings – The unpruned Decision Tree classified 92 of 100 holdout observations correctly (92.00% accuracy; 92.35% weighted F1; 86.64% macro F1). Training-only pruning reduced the tree from 49 to 35 nodes and produced 93.00% accuracy and an 88.99% macro F1. X1 had the highest primary root-split information gain (0.6805) and ranked first in 74 of 100 repeated splits, whereas X5 ranked first in 26. Repeated-split accuracy averaged 94.13%, but balanced accuracy and macro F1 averaged 88.52% and 88.89%, respectively. The deterministic score rule achieved 100%. Research implications – The Low, Moderate, and High categories were equal-width operational score intervals and have not been externally validated. Preliminary factor analysis supported one broad common factor, but the self-developed instrument still requires independent content, construct, and criterion validation. The target was derived from the same items used as predictors, minority-class performance varied across splits, and the available records did not document ethics approval, guardian consent, or minor assent for participants younger than 18. The findings therefore describe score-category discrimination rather than causal purchasing behaviour or validated psychological severity. Originality – This study integrates interpretable Decision Tree classification, training-only pruning, psychometric diagnostics, deterministic-rule comparison, multiple feature-importance perspectives, and repeated-split stability analysis for technology-purchasing FOMO patterns.
Random Forest Algorithm with SMOTE Technique for Classifying the Mental Health of Fresh Graduates Facing Career Competition Wily Supi Ramadani; Sriani
Journal of Digital Technology and Computer Science Vol. 3 No. 3 (2026): August 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/dtcs.v3i3.1149

Abstract

Purpose – This study evaluated Random Forest with the Synthetic Minority Oversampling Technique (SMOTE) for classifying questionnaire-derived career-related psychological categories among fresh graduates and descriptively compared performance before and after class balancing. Methods – Data were collected from 250 fresh graduates using a self-developed 13-item, four-point Likert questionnaire covering seven operational dimensions. A stratified 80:20 holdout split was used for the primary comparison, while 5 × 5 repeated stratified cross-validation examined stability. Standard SMOTE and random oversampling were applied only to training data, and SMOTE-generated profiles were audited in both stored-integer and continuous-interpolation representations. Findings – On the selected holdout split, Random Forest without SMOTE achieved 96.00% accuracy and a 95.93% weighted F1-score, whereas the SMOTE model reached 100.00% for both measures by correcting two Moderate-to-Poor errors. Random oversampling achieved 98.00% holdout accuracy. Across 25 repeated validation folds, mean accuracy was 96.08% without SMOTE, 95.76% with SMOTE, and 95.92% with random oversampling; the baseline–SMOTE accuracy difference was not statistically significant (Wilcoxon p = 0.412). Research implications – This study combines a controlled comparison of baseline Random Forest, standard SMOTE, and random oversampling with synthetic-profile auditing and repeated validation, while explicitly distinguishing operational score-category reproduction from independently validated psychological prediction. Originality – This study combines a controlled comparison of baseline Random Forest, standard SMOTE, and random oversampling with synthetic-profile auditing and repeated validation, while explicitly distinguishing operational score-category reproduction from independently validated psychological prediction.