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LP3M Universitas Mulia Jl. Letjen Z.A. Maulani No. 9 Kelurahan Damai Bahagia Kecamatan Balikpapan Selatan Kota Balikpapan Provinsi Kalimantan Timur Indonesia
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METIK JURNAL
Published by Universitas Mulia
ISSN : 24429562     EISSN : 25801503     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering
Media Teknologi Informasi dan Komputer (METIK) Jurnal adalah jurnal teknologi dan informasi nasional berisi artikel-artikel ilmiah yang meliputi bidang-bidang: sistem informasi, informatika, multimedia, jaringan serta penelitian-penelitian lain yang terkait dengan bidang-bidang tersebut. Terbit dua kali dalam setahun bulan Juni dan Desember.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 264 Documents
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Analisis Tren dan Prediksi Penjualan Restoran Menggunakan Model Time Series Prophet Hidayat, Kiki; Witanti, Wina; Ramadhan, Edvin
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 2 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/gd8y7q29

Abstract

Daily sales forecasting is a critical component of business planning that must adapt to the dynamics of market demand. While traditional approaches such as Single Moving Average and Trend Moment have been used in previous studies, their predictive accuracy on daily sales often remains suboptimal, with reported MAPE values up to 39.2%. Prophet, a time series model developed by Meta, offers enhanced flexibility in capturing non-linear trends, seasonality, and incorporating external regressors. This study proposes a hybrid forecasting model by combining Prophet with engineered features and external regressors, including calendar effects and recent sales statistics. The dataset consists of daily sales records that have undergone data cleaning, logarithmic transformation, and smoothing. Prophet is configured with additional monthly seasonality, national holiday indicators, and optimized parameters through grid search. Evaluation results demonstrate a substantial improvement, with the final model achieving an R² score of 0.9787 and a MAPE of 3.79%, outperforming conventional methods and aligning with the best results from recent Prophet-based studies. These findings confirm that the integration of external variables within Prophet significantly improves prediction accuracy, making it suitable for time series forecasting in various business domains with similar data patterns.
Desain Dashboard Command Center Kabupaten Bandung Barat Menggunakan Metode Design Thinking Khoirullah, Debri; Nurul Sabrina, Puspita; Ashaury, Herdi
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 2 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/9bhp6x40

Abstract

The advancement of digitalization requires local governments to provide information services that are efficient, well-structured, and user-friendly. This study aims to design the dashboard interface for the West Bandung Regency Command Center using the Design Thinking method. The approach involves five stages—empathize, define, ideate, prototype, and test—to deeply understand user needs and deliver appropriate design solutions. Data collection was conducted through interviews and observations, followed by the creation of an interactive prototype using Figma. Usability evaluation was carried out using the System Usability Scale (SUS). The results show that the redesigned dashboard presents government data in a more informative, structured, and intuitive manner and achieved a high SUS score during testing, with an average score of 75.625, categorized as Good. This study contributes uniquely to the development of user-centered government information systems, particularly in the context of command center applications. A limitation of this study is the small number of respondents in the usability test, due to the fact that the primary users of the system are executive officials who typically do not interact directly with the UI/UX. Thus, representatives from Diskominfo—who understand the interface from a technical and operational perspective—were selected as respondents. Given the limited number of personnel operating the command center, the involvement of four respondents was considered sufficient and contextually appropriate.
Pengaruh Implementasi SIPSUPER Terhadap Pengelolaan Prasarana, Sarana, dan Utilitas Umum Perumahan Ade Satriya, Muhammad Andi; Panjaitan, Maraden; Tukimun, Tukimun
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 2 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/q268je77

Abstract

This study aims to examine the implementation of the SIPSUPER (Information System for the Handover of Housing Infrastructure, Facilities, and Public Utilities) application and its impact on the management of PSU in housing areas in Samarinda City. The research is motivated by the low level of developer compliance in handing over PSU to the government, combined with weak monitoring and documentation systems, which have resulted in many PSU assets being poorly recorded. The introduction of SIPSUPER is expected to serve as a technology-based public service innovation that enhances transparency, accountability, and effectiveness in PSU management. The study adopts a quantitative approach with descriptive analysis and simple linear regression. Data were collected through questionnaires, field observations, and document reviews, then analyzed using validity and reliability tests as well as hypothesis testing. The results indicate that the implementation of SIPSUPER has been fairly successful in supporting the processes of data collection, monitoring, and the handover of PSU from developers to the local government. Moreover, the use of SIPSUPER has shown a significant effect on improving the effectiveness of PSU management, as reflected in greater data transparency, easier access to information, and more optimal government supervision. Overall, it can be concluded that SIPSUPER contributes positively to the governance of PSU in Samarinda City.
Optimasi Usability Antarmuka Sistem E-Learning dengan Penerapan Metode Design Thinking I Gede Pageh Widiastra; Ni Putu Vega Nirmala Kanti; Ni Made Dwi Laksmi; Gede Indrawan; I Made Agus Oka Gunawan
METIK Jurnal Vol. 10 No. 1 (2026): METIK Jurnal Issue Published
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mjk0m067

Abstract

The rapid development of digital technology in education has encouraged the implementation of e-learning systems as flexible and interactive learning media. However, several usability problems still exist, such as confusing navigation, unresponsive user interfaces, and limited interactive features that reduce the overall user experience. In addition, previous studies on UI/UX optimization in e-learning systems have mainly focused on visual aspects and feature development without deeply applying a user-centered approach, particularly in non-formal coding education platforms. This study aims to optimize the usability of the e-learning system interface at Les Coding Edutech Community using the Design Thinking method. The research method consists of five main stages: Empathize, Define, Ideate, Prototype, and Testing. Data collection was conducted through observations, interviews, and questionnaires distributed to 25 active students using the e-learning system. The developed interface prototype was evaluated using the System Usability Scale (SUS) method to measure system usability. The results indicate that the implementation of the Design Thinking method successfully improved the interface quality, making the system simpler, more interactive, and easier to use. The SUS evaluation produced an average score of 78, categorized as Acceptable with a Good grade. These findings demonstrate that the e-learning system has a good usability level and is capable of supporting a more effective and comfortable digital learning experience for users.
Aplikasi Deteksi Dini Penyakit Kulit Wajah Menggunakan Deep Learning Yolo V8 Berbasis Python Imam Mudin
METIK Jurnal Vol. 10 No. 1 (2026): METIK Jurnal Issue Published
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/gv816b48

Abstract

Skin diseases on the face are common health problems that can affect appearance and self-confidence, and early detection is important to prevent more severe conditions. This study proposes a facial skin disease early detection application based on Python using Deep Learning YOLOv8 and Convolutional Neural Network (CNN). YOLOv8 is utilized to detect facial areas and visualize detection results using bounding boxes, while CNN is employed to classify facial skin conditions based on extracted visual features. The system allows users to upload facial images through a graphical user interface and provides detection results in the form of disease labels, confidence scores, and descriptive information. Experimental results show that YOLOv8 is capable of detecting facial objects in real time, while the CNN classification achieves an average accuracy of approximately 88%, as evaluated using a confusion matrix and performance metrics such as precision, recall, and F1-score. The combination of YOLOv8 and CNN enhances the effectiveness of facial skin disease detection by providing both localization and accurate classification. This system can serve as a supportive tool for early identification of facial skin diseases prior to professional medical diagnosis.
Sistem Pelaporan Kerusakan Jalan dan Saluran Air Berbasis Website dengan Metode SAW Ahmad Habib; Irfan Dwi Arfianto
METIK Jurnal Vol. 10 No. 1 (2026): METIK Jurnal Issue Published
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/hh3sse63

Abstract

Road and drainage infrastructure damage significantly affects public mobility and service quality. However,  the reporting process in many regions in Indonesia is still performed manually through messaging applications, making the information incomplete, unverified, and difficult to follow up. This study develops a web-basedinfrastructure damage reporting system integrated with GPS and the Simple Additive Weighting (SAW) method to support decision-making in prioritizing repair actions. The system allows the public to submit reports by uploading photos, descriptions, and coordinates automatically captured from the device. Administrators can verify incoming reports and assign values based on four criteria: damage level, location strategic value, road usage intensity, and proximity to public facilities. The SAW method is applied to calculate the priority ranking of handling each report. The research method uses the Waterfall model consisting of requirements analysis, system design using ObjectOriented Design (OOD) and UML, implementation using Laravel, and testing using Black-Box and usability testing. The results show that the system operates well, GPS data is captured accurately, the SAW calculation generates correct priority scores, and the system is easy for users to operate. This system is expected to improve the accuracy, speed, and transparency of reporting and become a digital solution for regional agencies to support infrastructure handling based on data-driven decisions.  
Prediksi Aksebilitas Molekul Tamu pada Metal-Organic Framework dengan SMOTE dan AdaBoost-Machine Learning Moch Anjas Aprihartha; Harun Al Azies; Wahyu Aji Eko Prabowo; Usman Sudibyo; Ika Puspitasari; Indah Putianik; Fatma Ahardika Nurfaizal
METIK Jurnal Vol. 10 No. 1 (2026): METIK Jurnal Issue Published
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/45crx119

Abstract

Metal-Organic Frameworks (MOFs) are a special class of organic-inorganic hybrid materials widely known for their regular and periodic crystal structures. MOFs are composed of metal ions or clusters connected by organic linkers that form a three-dimensional lattice-shaped series. The advantage of MOFs is their ability to capture guest molecules in their pores. Based on these capabilities, MOFs can be utilized in various applications such as gas absorption and separation processes, catalysts, and therapeutic compound delivery systems. Currently, in creating new materials, the MOFs synthesis process still applies a conventional trial-and-error approach that has the potential for high failure rates. The purpose of this study is to develop a machine learning model as an efficient tool design in creating new MOFs materials before the experimental process is carried out. This study implements the SMOTE and AdaBoost methods integrated with machine learning algorithms in classifying MOFs pores based on the pore limiting diameter (PLD) size. The results obtained from the CART-Gentle AdaBoost model provide the best performance with an accuracy of 72.82%; precision 71.32%; recall 73.53%; specificity 72.88%; and f1 score 72.39%. This model is quite suitable for use in identifying MOF structures that are accessible to guest molecules compared to other classification models.
K-Means dan Random Forest Faktor Pemicu Perceraian di Seluruh Provinsi Wisnu Supri Harmito; Arief Wibowo
METIK Jurnal Vol. 10 No. 1 (2026): METIK Jurnal Issue Published
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/f1npya68

Abstract

The integration of the K-Means Clustering algorithm and the Random Forest Regressor aims to map divorce patterns in Indonesia for the 2018–2024 period. This study introduces a paradigm for categorizing variables into axis factors—such as economic issues, disputes, and abandonment—and triggering factors, which can be referred to as behavioral factors, such as apostasy, gambling, domestic violence, and so on. The clustering results show a Silhouette Score of 0.5912, with Java Island identified as the region with the highest risk and a well-defined risk zoning. The Random Forest model achieved an R-squared accuracy of 0.9563, revealing that trigger factors—specifically gambling, incarceration, apostasy, and domestic violence—possess a higher deterministic weight in precipitating divorce compared to other factors. This key finding indicates that the impact/triggering factors do not always correlate directly with the number of cases. Therefore, it recommends policy interventions focused on breaking the chain of behavioral triggers to strengthen family resilience nationwide.
Real-Time Character Matching Using Brute Force Algorithm in Typing Game-Based Learning Rio Andriyat Krisdiawan; Rifky Putra Pratama; Nida Amalia Asikin
METIK Jurnal Vol. 10 No. 1 (2026): METIK Jurnal Issue Published
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/vfc61h04

Abstract

Typing skills are an essential component of digital literacy; however, conventional typing practice methods tend to be less engaging, which negatively affects students’ motivation and typing accuracy. This study aims to design and implement a computer-based typing game–based learning system that applies the Brute Force algorithm as a real-time character matching mechanism. The system was developed using the Game Development Life Cycle (GDLC) method, which consists of the initiation, pre-production, production, testing, and release phases. The Brute Force algorithm is employed to validate the correspondence between user input and the target words displayed in the game by sequentially comparing each character. System evaluation was conducted through functional testing, algorithm performance analysis, and a User Acceptance Test (UAT) involving teachers and students. The results indicate that the Brute Force algorithm achieves high character matching accuracy, deterministic behavior, and fast response time for relatively short word lengths. The time complexity analysis demonstrates a linear pattern O(n), while still satisfying real-time feedback requirements in educational games. Furthermore, the UAT results show a high level of user acceptance, indicating that the system is stable, consistent, and feasible as a game-based typing practice medium. Therefore, the Brute Force algorithm is proven to be suitable for implementation in typing game–based learning, particularly for basic to intermediate learning scenarios.
Penerapan AI Agent Berbasis n8n untuk Otomatisasi  Operasional Pertanian Muhammad Rofiif Taqiyyuddin Nabiil; Hario Jati Setyadi; Akhmad Irsyad
METIK Jurnal Vol. 10 No. 1 (2026): METIK Jurnal Issue Published
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/2z461g10

Abstract

This study aims to develop an artificial intelligence–based agricultural automation system by integrating an AI Agent with the n8n workflow automation platform. The development addresses common challenges in agricultural operations that remain manual, such as recording daily activities, scheduling reminders for fertilization and harvesting, and limited access to real-time weather information. The system was developed using the Waterfall model, which consists of requirement analysis, system design, implementation, testing, and maintenance stages. The proposed system integrates several components, including WhatsApp as the main user interface, n8n as the workflow controller, WAHA as the communication bridge, Google Sheets as the digital database, and an AI Agent for user query processing and recommendation generation. The Black Box Testing results show that all core functions operate as expected, covering activity recording, automatic reminders, recommendation delivery, and weekly report generation. The User Acceptance Test achieved a satisfaction score of 85 percent, categorized as very good, indicating that the system is user-friendly, responsive, and beneficial for improving agricultural efficiency. This research contributes to the advancement of AI-based information systems in the agricultural sector and demonstrates that integrating an AI Agent with n8n is an effective solution for supporting agricultural digitalization and implementing smart farming at the village level.

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