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Sebatik
Published by STMIK Widya Cipta Dharma
ISSN : 14103737     EISSN : 2621069X     DOI : -
Core Subject : Science,
Computer Science & IT
SEBATIK merupakan jurnal kumpulan artikel hasil penelitian, karya ilmiah, maupun program pengabdian masyarakat dari seluruh civitas akademik di Indonesia dalam rangka mengitegrasikan informasi. SEBATIK menyediakan layanan publikasi terbuka untuk semua kalangan umum, baik di semua lingkungan perguruan tinggi maupun keguruan dan lembaga penelitian lainnya, dengan kebebasan bertukar informasi yang didedikasikan untuk memfasilitasi kolaborasi antara peneliti, penulis maupun pembaca melalui pertukaran informasi. SEBATIK mulai diperkenalkan dan dikembangkan di lingkungan STMIK Widya Cipta Dharma sejak tahun 2001 dan terbuka lebar untuk pengembangan yang berkesinambungan. SEBATIK terbit berkala dua kali dalam setahun, yaitu Juni dan Desember, dimana setiap edisi terbitan mengandung paling sedikit 5 buah judul artikel. Jurnal ini memuat hasil-hasil kegiatan penelitian, penemuan dan pengabdian masyarakat dari bukan hanya dari dunia IT tetapi juga berbagai bidang disiplin ilmu. SEBATIK terbuka untuk topik-topik penelitian dan pengabdian seperti topik hubungan masyarakat, peningkatan ekonomi, pendidikan, infrastruktur TIK, dan lain-lain. Semoga dengan artikel-artikel dalam kultivasi para peneliti dapat saling berbagi ilmu demi memajukan Indonesia khususnya Kalimantan Timur.
Arjuna Subject : Umum - Umum
Articles 713 Documents
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A Mobile-Based Digital Solution (Mozak) for Mosque Management in the Modern Era. Adityo, R Dimas; Syafi'i, Syafi'i; Hidayat, M. Mahaputra; A.W, Satrio Cahyo; A, Sindi Hilda
Sebatik Vol. 29 No. 2 (2025): December 2025
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v29i2.2721

Abstract

The mobile-based zakat management application serves as a modern solution to enhance the transparency and efficiency of zakat management at the local level. Mozak (Mobile Zakat) is an Android-based application implemented at Masjid Al-Ikhlas, Desa Janti, Sidoarjo, aimed at facilitating the collection, distribution, and monitoring of zakat. The application is designed with a user-friendly interface, allowing muzakki to pay zakat online and helping mosque administrators manage zakat data in real-time. This study evaluates the effectiveness of the Mozak application in supporting zakat activities at Masjid Al-Ikhlas, showing an improvement in operational efficiency. Additionally, the application enhances transparency in the distribution of zakat to mustahik
Integrating Peer Counselor Training in Psychological First Aid (PFA) to Reinforce University Counseling and Disability Support Systems Silalahi, Ronald Maraden Parlindungan; Farisandy, Ellyana Dwi; Karuni, Bunga; Mutma, Fasya Syifa; Setiawan, Agustinus Agus
Sebatik Vol. 29 No. 2 (2025): December 2025
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v29i2.2724

Abstract

Psychological First Aid (PFA) is an essential competency for peer counselors to support mental health among university students. To strengthen students’ knowledge and readiness in providing early psychological support, a one-day Peer Counselor Training was conducted involving 22 psychology students (mean age = 20.73 years). The training consisted of lectures, video, case discussions, demonstrations, supervised roleplay, reflection, and assessments covering mental health concepts, psychological disorders, non-suicidal self-injury, suicidal ideation, suicide attempts, suicide, dynamics of interpersonal relationships, and the core principles of PFA. Pre- and post-training assessments showed a clear improvement in participants’ knowledge. Due to the non-normal distribution of the posttest scores, a Wilcoxon Signed-Rank Test was performed, yielding statistically significant results (Z = -4.12, p < 0.001). This finding indicates that the training effectively enhanced students’ understanding of PFA. Participants also expressed high satisfaction with the learning materials, simulations, and media used, suggesting that the training methods were engaging and useful for practical skill development. They recommended longer simulation sessions and more interactive case-based discussions for future training. Importantly, the training strengthens the role of students as active partners in campus mental health promotion. Trained peer counselors serve as an accessible first point of contact for fellow students, including those with disabilities who may face academic, emotional, or social barriers. Their presence supports early detection of distress, facilitates timely referrals to professionals, and complements the work of Counselling and Disability Service Unit (Unit Layanan Disabilitas/ULD). Through this initiative, the university’s commitment to inclusive, responsive, and student-centered mental health support is significantly reinforced.
Integration of Field Data and Citizen Science in Spatial-Based Tropical Biodiversity Information Systems Bustomi , Tommy; Adytia, Pitrasacha
Sebatik Vol. 29 No. 2 (2025): December 2025
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v29i2.2725

Abstract

Biodiversity monitoring in tropical regions is often constrained by limited field survey coverage and fragmented data. This study develops a spatial information system that integrates field data collected through an Android application, citizen science contributions from iNaturalist, and environmental indicators such as the Normalized Difference Vegetation Index (NDVI) and land cover. The integration process employs a spatial database and ETL mechanisms for data normalization, quality validation, and spatial joins with raster data. The implementation results demonstrate that the system is capable of displaying biodiversity distribution in an integrated interactive map. Although citizen science data provide significant contributions, challenges remain in terms of data quality, participation bias, and the protection of sensitive species. With appropriate methodological approaches, this system has the potential to serve as a supporting tool for biodiversity monitoring and data-driven conservation planning.
Analysis of Irrigation Water Quality in Batang Lampasi Yuni, Nola Rahma; Ekawaty, Reni
Sebatik Vol. 29 No. 2 (2025): December 2025
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v29i2.2726

Abstract

Irrigation water quality plays a key role in determining soil conditions and crop productivity. This study assessed the irrigation water quality of the Batang Lampasi Irrigation Area by analyzing a composite sample and comparing the results with FAO quality standards. Laboratory analyses included physical parameters—electrical conductivity (EC), turbidity, temperature, and odor—and chemical parameters such as pH, salinity, total Fe, total Ca, total Mg, and Sodium Adsorption Ratio (SAR). The results indicated that all measured parameters, including EC (132 µS/cm), turbidity (6.78 FTU), pH (6.44), salinity (34.32 ppm), Fe (0.904 mg/L), Ca (1.891 mg/L), Mg (1.795 mg/L), and SAR (0.467 meq/L), fall within acceptable limits set by FAO. These findings confirm that Batang Lampasi irrigation water is suitable for agricultural applications and underline the need for consistent monitoring and the development of national irrigation water quality standards.
COBIT as a Framework for Evaluating Strategic Business IT Alignment:Systematic Literature Review Abdul Muis; Mukhammad Andri Setiawan
Sebatik Vol. 30 No. 1 (2026): June 2026
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v30i1.2722

Abstract

Strategic business IT alignment is a critical factor in the success of organizational IT governance. Numerous studies have examined the use of COBIT in the context of IT governance and business IT alignment across various sectors. These studies are generally partial and limited to specific contexts or COBIT domains, resulting in a lack of a comprehensive understanding of cross sectoral patterns in the use of COBIT and the evaluation approaches applied. This literature review aims to map the use of COBIT as a framework for evaluating IT business alignment across different sectors, including the COBIT domains and evaluation approaches employed. This study adopts a Systematic Literature Review (SLR) approach following the PRISMA guidelines, which consist of identification, screening, and final selection stages. The review results indicate that COBIT implementation is distributed across four sectors, namely education (35,29%), industry (29,41%), government and healthcare (each 17,65%), with the education sector being dominant context. The APO domain is the frequently used domain, followed by EDM, DSS, BAI, and MEA. Collectively, these domains reflect an evaluation focus on strategic planning, resource management, risk management, IT service delivery, and monitoring and evaluation mechanisms. The evaluation approaches identified in the reviewed literature are predominantly assessment-based, followed by IT governance design approaches, while comparative and exploratory approaches are used in a limited number of studies. The results of this review contribute by providing a structured overview of the patterns of COBIT domain usage and evaluative approaches across sectors. These findings may serve as a reference for future research as well as for practical evaluations of business and IT strategic alignment.
Implementation of the Design Thinking Method in the Design of Mobile-Based MSME Applications (Case Study of MSME Mooara Space in Muara Badak District) Muhammad Risqi Zharfan; Azahari Azahari; Ahmad Abdul Khair
Sebatik Vol. 30 No. 1 (2026): June 2026
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v30i1.2741

Abstract

This study aims to design a mobile-based application for Micro, Small, and Medium Enterprises (MSMEs) to support digital transformation and improve service efficiency. Mooara Space MSME in Muara Badak District currently experiences limitations in managing services and delivering product information due to the absence of an integrated digital system. This condition leads to inefficiencies in operations and limited accessibility for customers. To address this issue, this research applies the Design Thinking approach, which emphasizes User-centered problem solving based on real needs and experiences. The research process consists of five main stages: empathize, define, ideate, prototype, and test. Data collection was conducted through direct observation and interviews with business owners and customers to identify key challenges and expectations. The findings were then translated into system requirements and solution concepts, which were implemented into a mobile application prototype. The developed application includes features such as product catalog, order management, payment processing, and order tracking. The evaluation results indicate that the proposed solution is able to meet User needs and improve interaction efficiency between customers and the business. Therefore, the application design is expected to enhance service quality, increase customer engagement, and support sustainable digital adoption for MSMEs.
An Analysis of Public Satisfaction with Government Services: A Multi-Method Approach Using PCA, K-Means Clustering, and Linear Regression Abuzar Gafari; Sarjon Defit; Rini Sovia
Sebatik Vol. 30 No. 1 (2026): June 2026
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v30i1.2742

Abstract

Flawless performance evaluation results across all service dimensions may potentially obscure the identification of areas for improvement and diminish objectivity in decision-making. This study aims to identify the specific service attributes influencing public satisfaction and to segment respondents based on their satisfaction levels at the Office of the Ministry of Religious Affairs in Payakumbuh City. The research integrates Principal Component Analysis (PCA), K-means clustering, and linear regression. PCA was employed to reduce data dimensionality and establish principal components; K-means clustering was utilized to group respondents based on perceptual similarities regarding service quality; and linear regression was applied to identify the most significant factors influencing public satisfaction within each segment. The data were sourced from the Public Service Survey Information System (SISULAP) application of the Payakumbuh Ministry of Religious Affairs, spanning June 2024 to October 2025, with a total of 1,950 respondents. The findings reveal that service process and efficiency are the primary factors influencing all respondent segments, with the low-satisfaction segment identified as the top priority for service improvement. The regression models demonstrate robust performance across all segments. These findings provide an empirical foundation for data-driven policymaking to enhance public service quality.
Intelligent System for Diagnosing Infectious Diseases in  Children Using the Certainty Factor and Naive Bayes Methods Based on Android Ahmad Khomsi; Syafri Arlis; S Sumijan
Sebatik Vol. 30 No. 1 (2026): June 2026
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v30i1.2743

Abstract

Infectious diseases in children remain a serious health problem due to their high vulnerability resulting from an immune system that is not yet fully developed. Limited access to medical personnel and delays in early detection often result in ineffective treatment. Therefore, this study aims to design and implement an Android-based intelligent system application capable of detecting infectious diseases in children early on by utilizing the Certainty Factor and Naïve Bayes methods. This system is designed as an expert system that mimics the way pediatricians analyze symptoms and determine preliminary diagnoses. The research methods used include collecting disease and symptom data based on the knowledge of pediatric health experts, data analysis, rule base formation, and the design and implementation of an Android-based system. The Certainty Factor method is used to handle the uncertainty of the level of confidence in the symptoms selected by the user, while the Naïve Bayes method is used to calculate the probability of disease based on historical data. The combination of these two methods aims to improve the accuracy and reliability of diagnostic results. The results of the study show that the developed expert system application is capable of providing initial diagnostic information on infectious diseases in children quickly and easily accessible to parents and health workers. This system is expected to be an effective early detection tool, support initial medical decision-making, and contribute to the development of artificial intelligence-based health technology in Indonesia.
Teacher Performance Evaluation Analysis Using K-Means Clustering Algorithm and Random Forest Classification Dito Jurinaldo; Musli Yanto; Syafri Arlis
Sebatik Vol. 30 No. 1 (2026): June 2026
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v30i1.2744

Abstract

Teacher performance assessment is a primary parameter in determining the quality of educational institutions. Evaluation systems in many elementary schools still rely on descriptive qualitative approaches. Abundant school administrative data often remain as unprocessed archival records without further analytical utilization. This condition results in school management decision-making that lacks a strong empirical foundation. This study applies data mining technology to transform administrative data into strategic information. The research focuses on SD Negeri 12 Padang Besi and involves all active teaching staff during the current academic year. The research dataset is entirely derived from internal school records. This study excludes the use of questionnaire instruments, and in-depth interview methods are not employed in the data collection process. The analysis is strictly limited to administrative aspects, without including assessments of in-class pedagogical competence. The technical implementation utilizes the K-Means Clustering algorithm to automatically identify patterns in teacher performance grouping. This process is followed by the application of the Random Forest algorithm to measure classification accuracy based on the available administrative features. The combination of these methods produces a performance mapping that is free from human subjectivity. The analytical results provide clear performance labels for each individual teacher. This study contributes to the development of a data-driven digital evaluation model. School management can use the outputs of this research as a basis for reward allocation or targeted professional development programs. This approach ensures transparency in human resource governance within the educational environment.
Deep Learning Analysis for Predicting the Approval Time of Clinical Practice Guidelines (CPG) Based on Historical Administrative Data Yuliana Pertiwi; Musli Yanto; Billy Hendrik
Sebatik Vol. 30 No. 1 (2026): June 2026
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v30i1.2745

Abstract

This study aims to predict the processing time of the approval of Clinical Practice Guidelines (CPG), which exhibits considerable variation in duration and is difficult to predict accurately. In addition, the utilization of historical hospital administrative data to build effective predictive models for estimating the duration of the CPG approval process has not yet been optimized. Therefore, this research seeks to develop a predictive model to estimate the processing time of the CPG approval process.The proposed approach employs deep learning techniques by leveraging historical administrative data as the basis for modeling. The methods applied include K-Means Clustering, Decision Tree, and Long Short-Term Memory (LSTM). K-Means Clustering is used to group CPG data based on similar administrative characteristics, enabling the identification of approval time patterns. Subsequently, the Decision Tree method is utilized to analyze the relationships among variables and to generate classification rules that explain the factors influencing the duration of the CPG approval process. Meanwhile, LSTM serves as the primary model for predicting the processing time of CPG approval.This study uses 487 CPG records collected over the period from 2020 to 2024. The evaluation results indicate that the K-Means Clustering method achieves an accuracy rate of 87,36%. This level of accuracy reflects strong clustering performance and a high degree of conformity with actual conditions, indicating that the results are suitable to be used as a foundation for further analysis in the classification and prediction stages of the CPG approval process.

Page 69 of 72 | Total Record : 713

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