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INDONESIA
Jurnal Informasi dan Teknologi
Published by Universitas Putra Indonesia YPTK Padang
ISSN : 27149730     EISSN : 27149730     DOI : https://doi.org/10.37034/jidt
Core Subject : Science,
Computer Science & IT
Jurnal Informasi & Teknologi media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai penelitian Rekayasa Sistem, Teknik Informatika/Teknologi Informasi, Manajemen Informatika dan Sistem Informasi. Sebagai bagian dari semangat menyebarluaskan ilmu pengetahuan hasil dari penelitian dan pemikiran untuk pengabdian pada Masyarakat luas dan sebagai sumber referensi akademisi di bidang Teknologi dan Informasi.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 22 Documents
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Search results for , issue "2025, Vol. 7, No. 2" : 22 Documents clear
Text Data Classification Using the SVM Model on the LMDB Minecraft Dataset Bayu Yoga Astario; Tukino; Agustia Hananto; Fitria Nurapriani; Elfina Novalia
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.620

Abstract

Text classification is a fundamental task in Natural Language Processing (NLP) aimed at categorizing text data into predefined classes. This study implements a Support Vector Machine (SVM) model to classify text data from the LMDB Minecraft Dataset, which contains user reviews of the Minecraft movie. The research involves text preprocessing, TF-IDF feature extraction, and SVM model training. The classification results are evaluated using accuracy, precision, recall, f1-score, and confusion matrix metrics. The comment data is also analyzed based on the timing of their appearance in the movie. All processes are visualized in diagrams; the final results are saved in Excel format. The SVM model performs adequately on informal and domain-specific language data, providing a foundation for future research in similar text classification contexts.
Implementation Clustering Diabetes Suffering Areas Using Web-Based Dbscan Algorithm North Aceh District Abdillah, Ahmad Fauzi; Dinata, Rozzi Kesuma; Maryana
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.622

Abstract

Diabetes has shown a significant increase in Indonesia, including in the North Aceh District. This research implements the DBSCAN algorithm (Density-Based Spatial Clustering of Applications with Noise) web-based method to map diabetes distribution patterns in 27 North Aceh sub-districts. This system was built using the PHP programming language and database MySQL. Proses clustering utilizing data on population, number of sufferers, and number of deaths from 2021-2023 obtained from Prima Inti Medika Hospital and Cut Meutia RSU, with parameters epsilon = 0.5 and MinPts = 3. Results clustering shows an increase in high-risk areas from year to year. In 2021, 2 high-risk sub-districts were identified, Dewantara and Lhoksukon, increasing to 3 sub-districts in 2022 Dewantara, Lhoksukon, and Nisam, in 2023 to 4 sub-districts Dewantara, Lhoksukon, Nisam and Muara Batu. The resulting web-based system succeeded in visualizing diabetes distribution patterns and can be used to plan more effective and targeted health programs.
Prediction Of Industrial Waste Using The Autoregressive Integrated Moving Average Method Roslaini, Roslaini; Abdullah, Dahlan; Suwanda, Rizki
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.624

Abstract

This study presents the development of a web-based industrial waste prediction system using the Autoregressive Integrated Moving Average (ARIMA) method to forecast the volume of liquid and solid waste generated by PT Pupuk Iskandar Muda (PIM). The predictive model is built upon historical waste data collected between 2020 and 2023, serving as the foundation for the statistical analysis. The system is developed using the Flask web framework, offering an interactive and user-friendly interface, while SQLite3 is employed as a lightweight local database solution for efficient data handling. The ARIMA (1,1,1) model was selected based on stationarity testing and examining ACF and PACF patterns. The results suggest that the model can moderately capture prediction trends, although limitations in accuracy are evident. For 2024, liquid waste is projected to decrease from 30,600 tons in January to 29,400 tons in December. In contrast, solid waste displays a more stable trend, with an average monthly generation of approximately 23.2 tons. Model performance was evaluated using the Mean Absolute Percentage Error (MAPE) method, yielding high error rates—166.11% for liquid waste and 100% for solid waste, highlighting the significant impact of data quality and completeness on prediction accuracy. The system generates visual outputs through interactive graphs and tables accessible via a web browser, supporting data-driven decision-making. This research is a predictive tool for PT PIM and a reference for future development of technology-driven waste management systems to promote environmental sustainability.
The Influence of Economic Factors on Investment Decisions in Property & Real Estate Sub-Sector Companies Listed on the Indonesia Stock Exchange for the Period 2020-2023 Oktavia, Dina; Nisfi, Fiya Lailatin; Purdianto, Ario
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.625

Abstract

This study aims to determine the effect of economic factors on investment decisions, especially in property and real estate companies listed on the Indonesia Stock Exchange for 2020-2023. The financial factors that are the focus of this research are inflation and interest rates, with investment decisions proxied by the Price Earning Ratio (PER). The sample in this study consisted of 8 companies selected using a non-probability sampling method with a purposive sampling technique. Meanwhile, the research population includes all property and real estate companies listed on the Indonesia Stock Exchange, including as many as 94 companies. The method used in this research is a quantitative method with an associative approach. Data analysis was carried out using multiple linear regression techniques to measure the effect of inflation and interest rates on investment decisions. The results showed that inflation positively and significantly influences investment decisions as measured by Price Earning Ratio (PER). This means that an increase in inflation drives an increase in PER, which indicates that investors still have optimism about the prospects for investment in the property and real estate sector despite inflationary pressures. Conversely, interest rates have a positive and significant effect on investment decisions, which means that an increase in interest rates causes a decrease in PER. This shows that when interest rates increase, investors tend to shift their investments to safer instruments, thereby reducing interest in property and real estate stocks.
Artificial Intelligence and Bias in Religious Auhtority Hanik L. Tarwiyyah
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.626

Abstract

This research examines the complex interaction between Artificial Intelligence (AI) and religious authority. The main focus of the study is the significant risk of algorithmic bias, which emerges as AI becomes increasingly integrated into various aspects of life, including the religious sphere. The potential for bias in AI systems can affect the interpretation of doctrine, religious education, and even the legitimacy of spiritual leadership. This study uses a qualitative approach through document analysis and case studies to understand how AI, defined as the ability of computational systems to mimic human intelligence, can inadvertently reinforce religious prejudices and stereotypes. The results show that AI bias can manifest in various harmful forms. These forms include religious stereotypes, religious misinformation or "hallucinations," and the reinforcement of existing prejudices. Furthermore, the study also found a transformation of religious authority from traditional to digital, influenced by algorithmic logic and metric culture. In response to these challenges, various religious authorities have issued ethical guidelines emphasizing the importance of human responsibility, transparency, accountability, and the protection of human dignity in the development and use of AI
Analysis of Hardness Level in Enim River for Demineralization Water Process in Thermal Power Plant Tanjung Enim Fajri, Asri Alfiah; Tb. Ade Rahmatullah; Gurruh Dwi Septano; Nasaruddin
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.632

Abstract

Demineralization water is removal of dissolved ionic mineral impurities present in water and other liquids. Mineral content in water can cause crusts in power plant equipment such as boilers and turbine, lowering yield and selectivity values in the reaction process. The aim of the research is to diagnose the conditions of water process Tanjung Enim thermal power plant with standard value of ASME CRTD Vol. 34 and Power Plant water treatment standard. Demineralization Water treatment process starts from Multimedia Filter (MMF), Carbon Filter (CF), Reverse Osmosis (RO), Electrodeionization. Demineralization water sampling taken in January, february, march and April. The water sampling used in RAW Water, Feed RO, Electrodeionization process, feed water and boiler drum to measure the parameters of pH, conductivity, turbidity, Fe, Cl2 and Si02, P04 and ions of Na+, Fe+, Cu+ some of parameters result the fluctuative value but still in both of water treatment standard.
The Impact of Digital Marketing Strategies on Consumer Behavior in Emerging Markets di Sendys Swalayan Kota Palangka Raya Toendan, Rita Yuanita; Hansly Tunjang; Peridawaty; Ina Karuehni
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.642

Abstract

This study investigates the impact of digital marketing strategies social media marketing, content marketing, and influencer marketing on consumer behavior in emerging markets, with a focus on Sendys Swalayan in Palangka Raya City, Indonesia. As digital technology increasingly reshapes consumer engagement, businesses in developing regions must understand how strategic online efforts influence customer purchase decisions. Employing a quantitative approach, this study collected data from 44 respondents using structured Likert-scale questionnaires. The data were analyzed using SPSS software, including validity and reliability tests, Pearson correlation, and multiple linear regression. The findings show that all three digital marketing strategies significantly influence consumer purchase decisions, with content marketing having the strongest effect (β = 0.351, p < 0.01), followed by social media marketing (β = 0.284, p < 0.01), and influencer marketing (β = 0.194, p < 0.05). These results indicate that content relevancy and perceived value are key factors that drive consumer interest and action. The study also highlights the importance of authenticity and social interaction in digital spaces, confirming the relevance of theories such as the Elaboration Likelihood Model (ELM) and Source Credibility Theory. This research contributes to the limited literature on localized digital marketing in mid-sized Indonesian cities and offers practical recommendations for retailers aiming to optimize consumer engagement. The study suggests that businesses should prioritize informative, engaging content while leveraging social media and micro-influencer collaborations that align with local cultural values. These strategies are essential for enhancing brand awareness, building trust, and influencing consumer decision-making in the digital era.Keywords: Digital Marketing, Social Media, Content Marketing, Influencer, Consumer Behavior, Purchase Decision, Emerging Markets.
The Role of Strategic Management in Tourism Business Sustainability: A Case Study on Digital Economy-Based Tourist Destinations Putra, Johni Eka; Riri Cornelia; Hapsari Widayani; Anggi Oktaviani; Muhammad Aqshel Revinzky
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.644

Abstract

This study explores the role of strategic management in supporting tourism business sustainability within digital economy-based destinations, focusing on Ciletuh-Palabuhanratu Geopark in West Java, Indonesia. The research aims to determine whether differences in the level of digital-based strategic management among tourism actors influence their sustainability performance. Using a quantitative approach, data were collected from 90 respondents categorized into three groups: low, moderate, and high digital strategy adopters. A one-way ANOVA test was conducted to examine whether significant differences existed in the economic, social, and environmental dimensions of sustainability among the groups. The results show a statistically significant difference in sustainability outcomes, with businesses in the "high" digital strategy group demonstrating the most favorable performance. Economic sustainability emerged as the most impacted dimension, driven by better revenue growth and operational efficiency. Social and environmental dimensions also improved through increased community engagement, visitor satisfaction, and adoption of eco-friendly practices. These findings indicate that digital-based strategic management not only enhances competitiveness but also strengthens long-term sustainability. The study further highlights the importance of stakeholder collaboration in maximizing the effectiveness of digital strategies. Strategic alignment between tourism actors, local government, and communities is essential to build inclusive and resilient destination ecosystems. By integrating strategic planning with digital innovation, tourism businesses can achieve sustainability that is both profitable and responsible. The results contribute to the growing discourse on digital transformation in tourism and offer practical insights for policymakers, tourism managers, and local stakeholders in digitally emerging destinations.
Mobile Application for Monitoring Toddler Development Muhammad Rafli Alfiardi; Mohammad Faishal Abyansyah; Kraugusteeliana, Kraugusteeliana
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.652

Abstract

Stunting is a condition of chronic malnutrition that occurs from early life and has long-term effects on children's physical growth and cognitive development. Children who experience stunting are at risk of having learning limitations, low productivity in adulthood, and a decrease in the quality of human resources in Indonesia. Although the national stunting figures show a decline, significant barriers remain, including low parental participation in monitoring children's growth at the Posyandu, primarily due to limited access and inadequate health literacy. To address these challenges, this research develops an education-based mobile application designed to help parents monitor their toddlers' growth while also increasing their understanding of stunting prevention. Development of applications using the Software Development Life Cycle (SDLC) Waterfall model includes data collection, needs analysis, UI/UX design, implementation, testing, and evaluation. The mobile application has main features including digital anthropometric recording, immunization schedules, educational videos, and reward points that can be exchanged at Posyandu. Results from user testing in the community show that this application is easy to use and can increase parents' knowledge about children's health, thus potentially becoming a solution or support in the national program for accelerating the reduction of stunting and achieving a healthy and quality Indonesian generation.
The Impact of Financial Literacy and Digital Finance Applications on Household Consumption Patterns in the Digital Age: Evidence from Makassar Awaluddin, Sri Prilmayanti; Andi Ummul Khair; Eka Wijaya Paula; Faisal Rizal Zainal; Deni Anggreani Sutomo
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.647

Abstract

This study aims to examine the influence of financial literacy and digital financial applications on household consumption patterns in the digital era, with a case study conducted in Tamalanrea District, Makassar City. The research uses a quantitative associative approach with a multiple linear regression method. Data were collected from 100 household respondents selected through purposive sampling, based on their active use of digital financial services such as e-wallets, mobile banking, and paylater features. The primary variables studied include financial literacy (X₁), digital financial application usage (X₂), and household consumption patterns (Y). The results show that both financial literacy and digital financial application usage significantly affect household consumption patterns, both partially and simultaneously. Financial literacy positively influences rational financial behavior, including budgeting, prioritizing needs over wants, and managing spending. Meanwhile, the use of digital financial applications also positively affects consumption patterns by increasing access and ease of transactions, although it may also trigger impulsive behavior when not controlled by financial awareness. The F-test result shows that the model is statistically significant, with an R² value of 0.627, indicating that 62.7% of the variation in household consumption patterns can be explained by the two independent variables. This study highlights the importance of strengthening digital financial literacy and developing public policies to regulate fintech platforms. Efforts should be directed at building a healthy consumption ecosystem in the digital economy through collaborative efforts between the government, education institutions, and financial technology providers.

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