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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 420 Documents
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Classification Of Superstructure Damage In School Buildings In Nusa Penida Bali Using YOLO V7 Adnyana, Anak Agung Gede Oka Kessawa; Mahardika, I Gede Indra; Wicaksana, Gde Bagus Andhika; Kotama, I Nyoman Darma
Jurnal Info Sains : Informatika dan Sains Vol. 14 No. 04 (2024): Informatika dan Sains , 2024
Publisher : SEAN Institute

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Abstract

Structural damage in school buildings poses significant risks to safety and education quality, particularly in remote areas with limited maintenance resources. This study develops a YOLOv7-based model to detect building pillars and classify structural damages, focusing on school buildings in Nusa Penida, Bali. A dataset of 156 images, derived from an initial 521 images collected during field visits, was curated to include both damaged and intact pillars. Preprocessing and augmentation techniques, including resizing and rotation, were applied to optimize the dataset. Training was conducted over 55 epochs using Google Colab with a T4 GPU, incorporating parameter tuning to address dataset imbalance. Confidence thresholds were set at 0.7 for pillars and 0.2 for rebar detection to enhance sensitivity to underrepresented damage classes. Evaluation metrics, including the F1-score and confusion matrix, confirmed the model’s accuracy and robustness in detecting and classifying structural damages. The results demonstrate the model's potential for real-world applications in damage assessment, particularly in resource-limited settings. Future research should focus on expanding datasets, incorporating multi-class classification, and integrating real-time detection and drone-based imagery to enhance scalability and efficiency. This work contributes to developing efficient, AI-driven solutions for structural health monitoring in critical infrastructure.
An Utilization Of Sunlight As An Alternative Energy To Support Energy Independence In Pematang Serai Village Zuraidah Tharo; Vina Arnita; Dwi Permatasari Barus; Jones Gultom
Jurnal Info Sains : Informatika dan Sains Vol. 14 No. 04 (2024): Informatika dan Sains , 2024
Publisher : SEAN Institute

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Abstract

The utilization of renewable energy (RE) is a crucial solution to reduce dependence on depleting fossil fuels that negatively impact the environment. One of the most promising RE sources is solar energy, given Indonesia's tropical climate and abundant sunlight. This study aims to educate and raise awareness among the community of Pematang Serai Village, Langkat Regency, about using solar energy as an environmentally friendly alternative to support energy independence. The methods applied include field observation, public education through lectures and discussions, and a simulation of a simple solar power plant (PLTS) installation. The findings indicate high community enthusiasm for understanding the concept of solar energy and its technological applications. The simulation suggested the need for three 100 Wp solar panels, four 12V 75 Ah batteries, a 1500 Watt inverter, and a 20 Ampere solar charge controller to power a 286-Watt water pump for five hours. This program successfully raised community awareness of the importance of transitioning to cleaner and more sustainable energy sources. Additionally, it aligns with the government's effort to achieve a 23% national energy mix target by 2025. With abundant solar energy potential, Pematang Serai Village has significant opportunities to become an energy-independent village through the implementation of solar power technology.
Analysis of Student Achievement with K-Means on Socioeconomic, Behavioral, and Psychological Factors Muhammad Iqbal; Sardo Pardingotan Sipayung; Alex Rikki Sinaga; Paska Marto Hasugian
Jurnal Info Sains : Informatika dan Sains Vol. 14 No. 04 (2024): Informatika dan Sains , 2024
Publisher : SEAN Institute

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Abstract

This study aims to analyze students' academic achievement based on socio-economic, behavioral, and psychological factors using the K-Means clustering method. The data used include various variables such as family income, internet access, learning motivation, stress levels, and student attendance. The results of the analysis show that students can be grouped into three different clusters: Cluster 1 consists of students with good socio-economic backgrounds, high motivation, and better academic achievement; Cluster 2 shows students with higher levels of stress that affect their achievement even though they have adequate access to education; and Cluster 3 reflects students from less supportive socio-economic backgrounds, with limited internet access and low study time, so their achievement is lower than other clusters. The Davies-Bouldin Index (DBI) calculation result of 0.63 shows a fairly good cluster separation. This analysis reveals that socio-economic factors have a significant impact on students' academic achievement, while psychological aspects such as motivation and stress levels also play an important role in determining learning success. Intervention programs focused on stress management and increasing access to education are recommended for students from Cluster 2 and Cluster 3 to improve their academic outcomes. This study provides insight into the importance of socio-economic and psychological factors in shaping students' academic achievement.
The Influence of Organizational Culture and Big Data Analytics on Employee Performance Mediated by Organizational Support at PT XYZ Operating in the Consumer Goods Sales Industry Christine Febriana Sitorus; Yohana Cahya F. Palupi Meilani
Jurnal Info Sains : Informatika dan Sains Vol. 14 No. 04 (2024): Informatika dan Sains , 2024
Publisher : SEAN Institute

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Abstract

This study investigates the influence of organizational culture and big data analytics on employee performance, with organizational support as a mediating variable. Conducted at PT XYZ, a company in the essential goods sales industry (including rice, eggs, fruits, and vegetables), the research involved 90 employees using a quantitative approach. Data collection utilized questionnaires with a 5-point Likert scale, and the analysis employed Partial Least Squares Structural Equation Modelling (PLS-SEM) to explore relationships among variables. The results revealed several key insights. First, big data analytics does not significantly organizational support, while organizational culture positively and significantly affects it. Second, organizational support does not significantly impact employee performance, but both big data analytics and organizational culture have direct positive effects on employee performance. Third, mediation testing showed that organizational support does not mediate the relationship between big data analytics and employee performance, nor between organizational culture and employee performance. Based on these findings, it is recommended that PT XYZ prioritize enhancing employee capabilities, particularly among leaders, in communication and collaboration, to better utilize company support, such as systems and big data analytics. Additionally, establishing a strong organizational culture can significantly boost employee performance by fostering a supportive and comfortable work environment. The study highlights the importance of integrating technology and culture to achieve organizational success.
Prediction Model Using Machine Learning: Analysis Of Determinants Of Customer Churn At PT XYZ Riena Pribadi Gronloh; Hendra Achmadi
Jurnal Info Sains : Informatika dan Sains Vol. 14 No. 04 (2024): Informatika dan Sains , 2024
Publisher : SEAN Institute

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Abstract

This study aims to identify the factors influencing customer churn at PT XYZ, a B2B application-based company selling essential goods. Machine learning algorithms such as Random Forest and Logistic Regression were used to predict churn based on demographic and behavioral variables, including age, membership duration, monthly transaction averages, spending value, and product variety. Transaction data from January 2023 to August 2024 was analyzed to understand partner behavior patterns. The results indicate that the Random Forest algorithm provides more accurate predictions than Logistic Regression, based on evaluation metrics such as accuracy, precision, recall, and ROC-AUC. This study provides strategic insights for PT XYZ to reduce churn and maintain customer purchase retention through a data-driven approach.
Integration Of CRISP-DM And Machine Learning In Residential Sales Decision Making In The Middle And Upper Middle Class At Pt XYZ Patrik Mario Agata; Hendra Achmadi
Jurnal Info Sains : Informatika dan Sains Vol. 14 No. 04 (2024): Informatika dan Sains , 2024
Publisher : SEAN Institute

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Abstract

This study was conducted to predict the effect of monthly income on 6 other demographic variables. Research data was obtained through internal questionnaire data of PT XYZ involving 393 respondents of middle residential class and 47 respondents of upper middle residential class. Data collection done with a field questionnaire containing 6 demographic questions. The data was analyzed using the CRISP-DM integration method and the Random Forest analysis method. The results of this study state that middle-class residential targets with variables such as Monthly Expenditure and Age Group have a significant influence on Monthly Income and upper-middle-class residential targets with variables such as Age Group, Employment Status and Occupation have a significant influence on Monthly Income.
Meta Analysis of Morphological Charteristics of Local Durian (Durio SPP) Hajar Setyaji; Metha Monica
Jurnal Info Sains : Informatika dan Sains Vol. 14 No. 04 (2024): Informatika dan Sains , 2024
Publisher : SEAN Institute

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Abstract

The durian plant is a native Indonesian plant that produces fruit that is very popular with the public because of its distinctive taste, aroma and texture of the pulp. The high demand for superior durian fruit is a challenge because of the high variation in the quality of durian fruit. The meta-analysis of the morphological character of durian plants aims to provide an overview of the distribution of the morphological study of local durian plants. The research method was carried out by conducting research on the morphology of durian plants using the keyword google search engine by limiting it to journals written by Indonesians, selecting, and extracting related morphological parameters and analyzing them qualitatively. The results of the study showed that the morphology of durian fruit received the first priority, followed by durian leaves and seeds. Conclusion The morphology of local durian plants as a first step in finding superior durian seedlings still shows the diversity of measurements of morphological characteristics.
Performance and Energy Efficiency Analysis of Nanofluid-based Engine Cooling System Zulfan, Zulfan
Jurnal Info Sains : Informatika dan Sains Vol. 14 No. 04 (2024): Informatika dan Sains , 2024
Publisher : SEAN Institute

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Abstract

This investigation is intended to examine the performance and energy-efficient characteristics of nanofluid-based engine cooling systems. A qualitative method was employed with a case study approach to investigate the application of nanofluids in industrial engine cooling systems. The data set was constructed through the use of in-depth interviews, direct observation, and the analysis of relevant technical documentation. The resulting findings indicated that the implementation of nanofluids has the potential to enhance the heat transfer capacity and energy efficiency of the cooling system, with improvements observed in comparison to the performance of conventional fluids. The effectiveness of the system is influenced by a number of factors, including the concentration of nanoparticles, the specific nanomaterial utilized, and the operational parameters. The insights gained from this investigation offer significant value for the advancement of nanofluid-based refrigeration technology
Strategy for Implementing @Asahpolapikir TikTok Account Content as a Learning Media for Students Kurniawan, Jasen; Aripradono, Heru Wijayanto; Ardiansyah, Muhammad
Jurnal Info Sains : Informatika dan Sains Vol. 14 No. 04 (2024): Informatika dan Sains , 2024
Publisher : SEAN Institute

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Abstract

In this digital era social media has become an inseparable part. This can lead to various issues such as stress triggered by negative behaviors like body shaming and cyberbullying on social media, but social media TikTok can be utilized as an educational platform, particularly for enhancing media literacy and analytical skills. Through TikTok, students can explore various topics such as education, health, beauty and culinary arts. Additionally, TikTok serves as a platform for religious outreach, where professionals and the general public share knowledge through short videos. The focus of this research is the TikTok account @asahpolapikir, owned by Tjokro Wimantara who has built a strong personal brand through consistent content on education, business, entrepreneurship, and marketing strategies. With 2.1 million followers, @asahpolapikir won the TikTok Awards in the Best of Learning and Education category for its impactful content. This study adopts a qualitative approach using descriptive methods. The content posted by @asahpolapikir that garnered the most views and likes focuses on the challenges faced by undergraduate students in finding jobs and the importance of work experience. Additionally, the content about renting shop spaces for business purposes also received a high response, with 1.3k comments, due to its relevance to students interested in entrepreneurship. It can be concluded that the content strategy of the TikTok account @asahpolapikir prioritizes content with an educational approach, awareness of reality, and practical solutions, which are effective in capturing attention and increasing interaction on TikTok.
UX Analysis and UI Development of iOS-Based Bali Calendar Application with Double Diamond Method Darma Paramartha, I Gusti Ngurah; Ariesta, Ni Luh Wina Sinta; Gama, Adie Wahyudi Oktavia; Prathama, Gede Humaswara
Jurnal Info Sains : Informatika dan Sains Vol. 14 No. 04 (2024): Informatika dan Sains , 2024
Publisher : SEAN Institute

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Abstract

The Bali Calendar iOS application is designed to make it easier for users to access information related to the traditional Balinese calendar, such as determining rahina. However, the current features of the application are not yet optimal. Based on reviews on the App Store, many users have suggested adding features such as searching for dewasa ayu, otonan, Tri Sandhya alarms and chants, panca sembah, and daily prayers. The purpose of this research is to understand user needs and design the interface of the Bali Calendar iOS application based on user feedback to improve user satisfaction. The research method used is the Double Diamond approach, which consists of two phases: the research phase and the design phase. Each phase comprises two stages. The research phase includes the discover and define stages, while the design phase encompasses the develop and deliver stages. The outcome of this research is a prototype design for the Bali Calendar iOS application, which will be tested by users. The prototype design is evaluated using concept testing to assess the concept and usability testing to evaluate the prototype design. The results of the usability testing achieved high scores, indicating that the design is satisfactory and effectively meets user needs.

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