cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Reza Andrea
Contact Email
reza@wicida.ac.id
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota samarinda,
Kalimantan timur
INDONESIA
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
 68   69   70   71   72 
Sentiment Analysis of Public Comments on YouTube Content Using Principal Component Analysis and Naive Bayes Dede Pratama; Sumijan Sumijan; 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.v30i1.2746

Abstract

The rapid acceleration of digital media development compels public broadcasting institutions to adapt to shifting public information consumption patterns, which are now centered on online platforms. TVRI Sumatera Barat has responded to these dynamics by leveraging YouTube as a channel for content distribution and audience engagement. However, this interaction generates a massive volume of unstructured comment text, rendering manual sentiment analysis inefficient, time-consuming, and prone to subjectivity. This study aims to address these challenges by automatically and objectively classifying user sentiment using a machine learning approach. The applied methodology integrates Principal Component Analysis (PCA) and the Gaussian Naive Bayes algorithm. PCA serves as a dimensionality reduction technique to simplify TF-IDF weighted text features without losing vital information, while Gaussian Naive Bayes was selected for classification due to its efficiency in rapidly processing the continuous numerical data resulting from the PCA transformation. The research dataset comprises 10 comments from the TVRI Sumatera Barat YouTube channel in 2024, collected via the YouTube Data API, which underwent preprocessing and labeling for positive and negative sentiments. Model validation was conducted using a confusion matrix with accuracy, precision, recall, and F1-score metrics. The test results demonstrate that the combination of PCA and Gaussian Naive Bayes effectively enhances computational efficiency and delivers precise classification performance. This research makes a significant contribution by providing a measurable method for public opinion analysis, which is essential as a basis for evaluating audience perception to improve the quality of digital broadcasting strategies in public institutions.
Model Interpretation for Student Major Selection Using Principal Component Analysis and Random Forest Antoni Antoni; Sarjon Defit; Yuhandri Yuhandri
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.v30i1.2747

Abstract

The development of information technology has had a significant impact on the education sector by providing data-driven tools to support the process of major selection. This process often causes confusion among students due to its crucial role in determining their academic and career futures. This study aims to develop an accurate and transparent recommendation system for major selection through the integration of Principal Component Analysis (PCA), Random Forest (RF), and SHAP. The research follows a systematic framework that includes data processing and model evaluation stages. PCA is applied to reduce the dimensionality of complex student data in order to improve computational efficiency and minimize information redundancy. Furthermore, the Random Forest algorithm is employed as a classification model to predict major recommendations such as Science, Social Sciences, and Religious Studies. The SHAP method is integrated to provide both mathematical and visual interpretations of the contribution of each academic feature to the model’s prediction results. The research data are obtained from the internal records of MAN 1 Payakumbuh covering the last three academic years (2022/2023–2024/2025). The dataset consists of 571 eleventh-grade students with tenth-grade academic scores and non-academic skill variables. The implementation of this model is able to provide more objective recommendations compared to conventional subjective assessments, achieving an accuracy of 88.70%. Visualization of feature contributions using SHAP enhances transparency and facilitates stakeholders’ understanding of the basis for each model decision. This study contributes to improving the efficiency of the major selection process and supports more accurate academic decision-making for students and educators.
Classification of Avocado Ripeness Levels Using Transfer Learning Based on VGG16 and VGG19 Ibnu Luthfi; Yuhandri Yuhandri; Gunadi Widi Nurcahyo
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.v30i1.2749

Abstract

The determination of avocado ripeness is still commonly performed manually, which is subjective and often inaccurate due to its reliance on human visual perception. Traditional methods, such as pressing the fruit surface, may damage avocado quality and are inefficient for large-scale distribution and marketing. This study aims to automatically classify avocado ripeness levels using a deep learning approach based on transfer learning. The proposed method employs transfer learning using Convolutional Neural Network architectures, namely VGG16 and VGG19, which have been pre-trained on the ImageNet dataset. The research stages include image pre-processing such as resizing, normalization, and data augmentation to enhance input quality. Subsequently, model training and testing are conducted by comparing the performance of both architectures using evaluation metrics. The dataset used in this study is obtained from the Kaggle platform and consists of avocado images with various ripeness levels. Experimental results indicate that both models are capable of classifying avocado ripeness with high accuracy, precision, recall, and F1-score, with the VGG19 model achieving the best performance. These findings demonstrate that the deep learning approach effectively addresses the subjectivity and inaccuracy associated with manual avocado ripeness determination. This study contributes to the development of an accurate, objective, and practical image-based avocado ripeness classification system with potential applications in agriculture and fruit distribution
Optimizing IT Service Performance Through COBIT 2019-Based Governance Design at Keling Kumang Institute of Technology Angela AL; Alva Hendi Muhammadi
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.v30i1.2753

Abstract

The Keling Kumang Institute of Technology (ITKK) is a new university in Sekadau Regency, West Kalimantan, which faces challenges in IT management to support academic and managerial operations, including delays in IS and IT infrastructure maintenance, power and internet disruptions, a lack of competent IT human resources , and limited budget and network infrastructure. The complexity of IT services such as SIAKAD, Server and Network Systems, and OJS, requires the implementation of structured IT governance so that IT services run optimally and in line with the institution's vision and mission . This study aims to find weaknesses in IT governance through an analysis of current IT capabilities (as-is) and expected conditions (to-be), as well as to develop recommendations to achieve good governance levels. This study was conducted using the COBIT 2019 framework with 4 process objective domains that have been identified through consultation with ITKK stakeholders and stakeholders, namely APO04, APO07, DSS05, and BAI06. Based on the gap analysis, APO04 has evidence work of product at the Largely Achieved level (50-84%), APO07 has significant challenges in IT HR management with a Not Achieved value (0-49%) at Level 1, DSS05 shows weaknesses in network and endpoint security aspects with a Partially Achieved value (15-49%) at Level 2, and BAI06 requires substantial improvements in IT change management with a Partially Achieved value (15-49%) at all levels. The recommendations provided include the preparation of IT governance policies that are integrated with the ITKK Strategic Plan and VMTS, improving IT HR competency through training and certification, strengthening network security infrastructure, and implementing documented IT change management procedures
The Effect of Effectiveness, Accessibility, and Ease of Service of Digitalized Sharia Banking Services from BSI Mobile to BYOND by BSI on CustomerSatisfaction at The Gandapura Branch Office Wardiyati Wardiyati; Maryam Maryam; Cut Sukmawati; Ferizaldi Ferizaldi; Teuku Zulkarnaen
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.v30i1.2791

Abstract

This study aims to determine how the effectiveness, accessibility, and ease of service affect customer satisfaction with the BYOND by BSI application at BSI KCP Gandapura. This study was motivated by the author's observation that the usage rate of the BYOND by BSI application among KCP Gandapura customers is still low, as reflected in the perception that BYOND is not yet able to provide a better service experience than BSI Mobile. Customers are also reluctant to switch because the BYOND application is considered ineffective, often experiences technical problems, is difficult to access at certain times, and has a display and features that are not yet fully user-friendly. This study used a quantitative method, where the data source used was primary data obtained by distributing questionnaires to Gandapura KCP customers who were BYOND by BSI users. The data analysis technique used was multiple linear regression analysis using SPSS software. The results showed that the effectiveness, accessibility, and ease of service partially had a positive and significant effect on customer satisfaction with the BYOND by BSI application at KCP Gandapura. Then, the simultaneous test results showed that effectiveness, accessibility, and ease of service also had a significant effect on customer satisfaction with the BYOND by BSI application at KCP Gandapura.
Recommendation System for College Major Selection Based on Academic Analysis and Student Interests at SMAN 5 Berau Using Naïve Bayes Abil Firnanda; Salmon Salmon; Kusnandar Kusnandar
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.v30i1.2797

Abstract

Choosing a college major is one of the most critical decisions faced by high school students before graduation, as it significantly influences their academic path and future career. However, many students experience difficulties in selecting a major that aligns with their academic abilities and personal interests, which often leads to mismatches during their university studies. This research aims to design and implement a recommendation system for college majors tailored to students of SMAN 5 Berau by applying the Naïve Bayes algorithm. The dataset used in this study consists of students’ academic records and interest survey results, which are processed to generate appropriate recommendations. The Naïve Bayes method is chosen due to its simplicity, efficiency, and effectiveness in handling probabilistic classification problems. The system is developed to provide objective and data-driven recommendations by integrating both academic performance and student interests. Based on the analysis, the system is able to produce relevant recommendations that assist students in making more informed and accurate decisions regarding their future majors. Furthermore, this system also supports guidance counselors in providing appropriate academic advice. Therefore, the implementation of this recommendation system is expected to improve decision-making quality and reduce the risk of mismatched major selection among students.
Recruitment of Civil Servants Following The State of Emergency at The Sawang Subdisdrict Office, North Aceh Regency Ruwaida Ruwaida; Aiyub Aiyub; Muryali Muryali; Cut Sukmawati; Ferizaldi Ferizaldi
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.v30i1.2803

Abstract

This study aims to determine the recruitment process of civil servants and its impact on professionalism and transparency at the Sawang Sub-District Office in North Aceh Regency. The method used in this study is descriptive qualitative, with data collection techniques including interviews, observation, and documentation. The data obtained was then analyzed through data reduction, data presentation, and data verification. The results of the study show that the recruitment of civil servants after the military emergency at the Sawang Subdistrict Office was simple, quick, and tended to be closed because it was more influenced by the need to maintain socio-political stability, reconciliation, and the continuity of government in a post-conflict situation than by the strict application of merit principles, so that the process did not involve open selection or competency tests. This situation has impacted the professionalism of the State Civil Apparatus, which is not yet optimal, as well as low levels of transparency, because the recruitment process is based more on social and situational considerations during the transition period. When compared to the principle of meritocracy, this recruitment practice is not entirely appropriate because it does not place qualifications, competence, potential, performance, and integrity as the main criteria, even though it can be understood as an adaptive policy by local governments to maintain peace and ensure that public services continue to run.
Prediction of the Number of New Students Using the Arima Time Series Model Case Study at Stmik Widya Cipta Dharma Eko Jheremy Oktavianus; Pitrasacha Adytia; Muhammad Ibnu Sa’ad
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.v30i1.2804

Abstract

Planning for new student admissions is an important aspect in university management because it is closely related to strategic decision-making and institutional resource allocation. This study aims to estimate the number of new students in the Informatics and Information Systems Engineering Study Program at STMIK Widya Cipta Dharma using the Autoregressive Integrated Moving Average (ARIMA) method. The data used is secondary data obtained from PDDIKTI with a period of 2015-2025. The analysis process was carried out through several stages, namely stationary testing using the Augmented Dickey-Fuller (ADF) method, model identification through Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF), parameter estimation, diagnostic tests, and forecasting processes. The results showed that the best model obtained was ARIMA (0,1,0) after first-order differentiation. The model produces residual that meets the assumption of white noise and is normally distributed. The forecast results show a tendency to decrease the number of new students in the 2026–2028 period. The model evaluation showed a very good level of accuracy in the Informatics Engineering Study Program with a Mean Absolute Percentage Error (MAPE) value of 9.64% and quite good in the Information Systems Study Program of 24.88%. Thus, the ARIMA model (0,1,0) is considered effective in supporting the planning of new student admissions in a more measurable and systematic manner.
Cigarette Sales Forecasting at Bali Jaya Store Using the Single Method Exponential Smoothing I Ketut Andri Purna Wijaya; Andi Yusika Rangan; Muhammad Ibnu Saad
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.v30i1.2805

Abstract

This study aims to forecast cigarette sales at Toko Bali Jaya using the Single Exponential Smoothing method as a quantitative approach to support more effective inventory management. The problems faced are the unstructured sales recording process and the manual determination of stock levels, which leads to inaccuracy in inventory control and potentially leads to overstocking or understocking. The Single Exponential Smoothing method was chosen because it is known to be effective in forecasting time series with fluctuating data patterns and no significant trends. The data used are cigarette sales data for 12 months which are processed to produce forecast values for the following period. The accuracy evaluation process is carried out using the Mean Absolute Percentage Error (MAPE) as an indicator of the level of forecast error. The results show that the best smoothing constant value is obtained at α = 0.3 with a MAPE value of 5.93%. This value indicates a low error rate, so the method used is able to produce forecasts that are close to the actual data. Thus, this method can be used as a basis for decision-making related to cigarette inventory management in a more systematic and measurable manner.
Gandrung Sewu Festival as a Sustainable Tourism Attraction in Banyuwangi, East Java Kanom Kanom
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.v30i1.2811

Abstract

Gandrung Sewu Festival has enriched the Banyuwangi Festival series and is recognized as part of the Karisma Event Nusantara (KEN). First held in 2012, this cultural event offers more than a traditional performance; it provides educational value for tourists through a unique and modern presentation. The festival also generates positive impacts on the local community, particularly through the active participation of Banyuwangi’s younger generation in its implementation. However, several aspects still require evaluation, both internally and externally. This study aims to formulate strategies to sustain the existence of the Gandrung Sewu Festival as a sustainable tourism attraction in Banyuwangi, East Java. The research applies a quantitative descriptive method using the Internal-External (IE) Matrix as the analytical tool. The results show that the festival’s strengths include the Gandrung dance as its core identity, strong community participation, creative annual themes, and the growth of Banyuwangi’s tourism sector. The main internal strength is its strategic location, while the key weakness is the inconsistent scheduling of the event. Externally, the greatest opportunity lies in tourism sector development, while the main threat comes from natural disasters and weather conditions. This study proposes three strategic recommendations to strengthen the festival’s sustainability. The findings are expected to serve as a reference for developing event-based sustainable tourism attractions in Indonesia.

Page 70 of 72 | Total Record : 713

 68   69   70   71   72 

Filter by Year

2012 2026


Reset
Filter By Issues
All Issue Vol. 30 No. 1 (2026): June 2026 Vol. 29 No. 2 (2025): December 2025 Vol. 29 No. 1 (2025): June 2025 Vol. 28 No. 2 (2024): December 2024 Vol. 28 No. 1 (2024): June 2024 Vol. 27 No. 2 (2023): Desember 2023 Vol. 27 No. 1 (2023): Juni 2023 Vol 26 No 2 (2022): Desember 2022 Vol. 26 No. 1 (2022): Juni 2022 Vol 26 No 1 (2022): Juni 2022 Vol 25 No 2 (2021): Desember 2021 Vol 25 No 1 (2021): Juni 2021 Vol. 24 No. 2 (2020): Desember 2020 Vol 24 No 2 (2020): Desember 2020 Vol 24 No 1 (2020): Juni 2020 Vol 23 No 2 (2019): Desember 2019 Vol 23 No 1 (2019): JUNI 2019 Vol 22 No 2 (2018): DESEMBER 2018 Vol. 22 No. 2 (2018): DESEMBER 2018 Vol 22 No 1 (2018): JUNI 2018 Vol 19 No 1 (2018): JANUARI Vol 18 No 1 (2017): JUNI Vol 17 No 1 (2017): JANUARI Vol 16 No 1 (2016): JUNI Vol 15 No 1 (2016): JANUARI Vol 14 No 1 (2015): JUNI Vol 13 No 1 (2015): JANUARI Vol 12 No 1 (2014): JUNI Vol 11 No 1 (2014): JANUARI Vol 10 No 1 (2013): JUNI Vol 9 No 1 (2013): JANUARI Vol 8 No 1 (2012): JUNI Vol 7 No 1 (2012): JANUARI More Issue