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Journal Global Technology Computer
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 28096118     DOI : https://doi.org/10.47065/jogtc.v2i3.3992
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Engineering
Journal Global Technology Computer, ini memiliki bidang kajian: 1. Manajemen Informatika, 2. Sistem Informasi, 3. Game Design, 4. Multimedia System, 5. Sistem Pembelajaran Berbasis Multimedia, 6. GIS, 7. Mobile Programming, 8. Database Design, 9. Network Programming, 10. Distributed System, 11. Data Mining, 12. Sistem Pakar, 13. Kriptografi, dan 14. Sistem Pendukung Keputusan.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 12 Documents
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Search results for , issue "Vol 4 No 3 (2025): Agustus 2025" : 12 Documents clear
Penerapan Metodologi Rapid Application Development dalam Membangun Aplikasi TourGo untuk Mendukung Digitalisasi Pemesanan Tour Guide Wisata Rohmawati, Aufa Ikrimah; Andriani, Anik; Meyliana, Anastasia
Journal Global Technology Computer Vol 4 No 3 (2025): Agustus 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jogtc.v4i3.7837

Abstract

The demand for easily accessible, reliable, and informative tour guide services continues to increase along with the growth of the digital tourism industry. However, tourists still face various obstacles such as difficulty in finding professional tour guides, unclear prices, and the lack of a structured booking system. On the other hand, many tour guides do not yet have effective digital means to promote their services. This study aims to develop the TourGo application as a web-based platform that facilitates the process of searching and booking tour guides practically and safely. The method used is Rapid Application Development (RAD), which allows the development process to take place quickly through an iterative and prototyping approach. This application is designed with main features such as user registration, searching for tour guides by location and category, booking services, and a review and rating system. System testing was carried out using the black-box method and the calculation of the success rate on the tour guide interface showed a success rate of 95%, while the calculation of the success rate on the member interface showed a success rate of 91.67%, indicating a high level of user satisfaction. The results of the study indicate that the use of the RAD method is effective in producing applications that are in accordance with user needs and are able to answer problems in booking tour guides. The TourGo application is expected to be a digital solution that supports the development of technology-based tourism and increases the professionalism of local tour guide services.
Penerapan Metode Analytical Hierarchy Process (AHP) dalam Sistem Pendukung Keputusan Pemilihan Supplier di Sebuah Klinik Swasta Khoirunnisa, Khoirunnisa; Susanti, Lia
Journal Global Technology Computer Vol 4 No 3 (2025): Agustus 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jogtc.v4i3.7886

Abstract

The problem faced is the calculation is still done manually so that it causes errors in determining the selection of suppliers based on the cheapest price, discounts given, payment terms and speed of product delivery then there is no decision support system in the supplier determination process at the Medika Insani Clinic in Bekasi City because it still uses a conventional system and not a computerized system. The purpose of designing a decision support system for selecting suppliers is to make it easier for clinic owners to choose suppliers and the calculation process is computerized using the AHP method. The method used in this study is the Analytical Hierarchy Process in solving the problems that have been studied. The results obtained in this study are to produce an accurate report of the best supplier selection data at the Medika Insani Clinic so that it can help in making strategies in the future. The application system that has been designed is suitable for use in the supplier selection process at the Medika Insani Clinic because it is in accordance with the needs, so it can facilitate the administration in the data input process and report creation.
Penerapan Sistem Pakar dengan Metode Naive Bayes pada Kerusakan Motor Injeksi Sinaga, Marito Romaida; Sianipar, Lilin; Laia, Naomita; Bawamenewi, Nelis Sastraman; Surbakti, Asprina Br; Danur, Surizar Rahmi
Journal Global Technology Computer Vol 4 No 3 (2025): Agustus 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jogtc.v4i3.8190

Abstract

An injection engine is a motorized vehicle that uses a fuel injection system directly into the combustion chamber through an injector that is electronically controlled by the ECU. However, mechanics often encounter obstacles and difficulties in checking for damage to the injection engine, so that checks are still carried out manually on the injection engine. To overcome this problem, one solution is to utilize an analysis method that can help and facilitate mechanics in determining damage to the injection engine. This method was chosen with the aim of being able to identify the type of damage and provide solutions related to existing problems. The purpose of this study is to analyze and identify the types of damage to the injection engine using the Naïve Bayes method, as well as to determine the probability level of each damage so that it can provide more accurate information for the repair process. The results of the calculation test using the Naïve Bayes method show that problematic injection sensor damage is the damage with the highest value of 72.8%.
Diagnosa Gangguan Obsessive Compulsive Disorder dengan Kombinasi Metode Ripple Down Rules dan Certainty Factor Silaban, Lenni Wati; Ramadani, Sindi Fitri; Sembiring, David JM; PA, Sinek Mehuli Br
Journal Global Technology Computer Vol 4 No 3 (2025): Agustus 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jogtc.v4i3.8214

Abstract

Obsessive Compulsive Disorder (OCD) is a mental health disorder that is gaining increasing attention in the medical world and society. In Indonesia, public awareness and understanding of OCD are still low. Many OCD sufferers are unaware that they have this disorder. The main problem with OCD lies in its complex nature and difficulty in early recognition. Many OCD sufferers are unaware that their behavior is clinically abnormal because the symptoms are often considered common habits. The impact of these problems can have quite serious ongoing consequences. Individuals with OCD experience a decreased quality of life due to anxiety and compulsive behaviors that consume time and energy. In this study, the solution offered is to develop an expert system based on Ripple Down Rules (RDR) and Certainty Factor (CF). The purpose of this study is to increase public awareness and understanding of OCD, develop a system capable of making a quick and accurate initial diagnosis, facilitate the identification of OCD types, especially the Checking type, and provide support for medical personnel and psychological counselors in the initial diagnosis process. In the diagnostic calculation, the results show that Checking disorder has a percentage of 97.35%.
Pengelompokan Masyarakat Kurang Mampu Dengan Menggunakan Algoritma K-Means Data Mining Siagian, Evan Edward; Lubis, Irfansyah Nuddin; Setya, Monita; Sijabat, Ade Dermawan; Sembiring, David JM; Ginting, Meiliyani Br
Journal Global Technology Computer Vol 4 No 3 (2025): Agustus 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jogtc.v4i3.8215

Abstract

Some villages often experience difficulties in classifying economically disadvantaged communities, resulting in the distribution of social assistance sometimes being misdirected. Various grants are received, such as subsidies provided to the poor. Problems encountered include poorly managed community data, which complicates the analysis process, and the lack of a measurable grouping method, which often misdirects aid. Without an objective, data-driven grouping system, aid distribution errors will continue to recur, resulting in misdirected aid. To address these issues, one solution is the use of data mining techniques. In the past, big data management was often done manually or using conventional methods that required significant time, effort, and expense. Data mining is the process of exploring and analyzing large data sets to discover patterns, relationships, or important information that can support decision-making. The K-Means algorithm is a clustering method in data mining used to group data into groups (clusters) based on similar characteristics. The purpose of this study is to design and implement a system for grouping poor communities based on the K-Means algorithm that can assist village governments in distributing aid precisely to targets, accelerate the data analysis process, and reduce aid distribution errors. This study uses 30 population data with 5 attributes: occupation, income, dependents, home ownership, and assets. The method used in this study is the K-Means Algorithm. From the calculations that have been carried out, it is recommended that there are 3 clusters with the same results, namely cluster 1 with 10 residents, cluster 2 with 10 residents, and cluster 3 with 10 residents as well.
Penerapan Algoritma CLARANS Data Mining untuk Klasterisasi Nilai Mahasiswa Pada Penentuan Bidang Konsentrasi Harmanda, Inke; Sari, Anggun Puspita; Melasari, Melasari; Angkat, Erlita Natasya; Sembiring, David JM; Ramles, Polin
Journal Global Technology Computer Vol 4 No 3 (2025): Agustus 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jogtc.v4i3.8223

Abstract

A major challenge for educational institutions is recognizing their students' academic abilities and guiding them toward the right concentration. Grouping concentration areas for students is not easy. Grouping concentration areas will help students focus more on a concentration they are interested in and align it with their academic grades. The urgency of this research lies in the need to present a more objective, accurate, and data-driven method for grouping student concentration areas. With a recommendation system supported by data mining techniques, the process of determining concentration areas depends not only on students' personal preferences but also considers relevant academic performance patterns. This problem can be solved by utilizing data mining techniques, specifically the clustering method using the CLARANS algorithm. This study aims to analyze student data according to the weighting of certain course grades using the Clarans Algorithm, thus being able to provide decision support for grouping student grades to determine which major a student should be enrolled in. Student grade data with high (Network), medium (Programming), and low (Internet of Things) grades can be grouped into three clusters. The test results showed that 11 students were enrolled in the programming concentration, 5 students in the networking concentration, and 9 students in the Internet of Things concentration.
Implementasi Metode ARAS dan Metode Pembobotan ROC untuk Pendukung Keputusan pada Seleksi Penerimaan Karyawan Baru Arini, Wulan; Sitepu, Yanti Peronika Br; Dewani, Dewani; Fitriani, Nopita; Sembiring, David JM; Ginting, Raheliya Br
Journal Global Technology Computer Vol 4 No 3 (2025): Agustus 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jogtc.v4i3.8225

Abstract

Employees are one of the most important assets in a company. Their crucial role extends beyond carrying out daily tasks, but also through contributing ideas, innovations, and solutions that can help the company grow. Problems in the recruitment process for new employees often arise due to the large number of applicants with diverse backgrounds, abilities, and experiences. If this problem is not resolved, companies could potentially recruit employees who do not meet the required qualifications. One solution is to implement a Decision Support System (DSS). A DSS is a computer-based system designed to assist decision-makers in solving semi-structured or unstructured problems. In its implementation, a DSS can be integrated with the Additive Ratio Assessment (ARAS) method. To ensure accuracy in the ARAS calculation process, appropriate criteria weighting is required. One such weighting method is Rank Order Centroid (ROC). The purpose of this study is to implement a combination of the ROC and ARAS weighting methods to build a decision support system that can assist companies in selecting new employees who meet predetermined criteria. The combination of the ROC and ARAS methods can be an appropriate solution to overcome the problem of subjectivity, accelerate the selection process, and improve the accuracy of decision-making in hiring new employees. The process obtained a score of 1.000 on A6, indicating that the new employee was selected in the new employee selection process.
Sistem Informasi Terintegrasi Pengelolaan Catatan Kasus Konseling Siswa menggunakan User-Centered Design Prakasa, Anabela Aji; Mardhia, Murein Miksa; Aretama, Lucky Barga; Khusna, Arfiani Nur; Perwira, Luqman Tifa
Journal Global Technology Computer Vol 4 No 3 (2025): Agustus 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jogtc.v4i3.8259

Abstract

Deviant behavior in adolescents is a significant issue in education, particularly in the field of Guidance and Counseling (BK). The paper-based manual recording system makes it difficult for BK teachers to manage data such as case histories, counseling reports, and attendance. This study aims to develop a website-based BK information system using the User-Centered Design (UCD) approach and the Waterfall method. Data was collected through interviews and observations of BK teachers, followed by designing a user-friendly interface, system development, and testing. This system enables BK teachers to manage student data efficiently and allows principals to monitor reports in real time. The results of the System Usability Scale test showed an average score of 80.75 (category B, Good), and the Blackbox test showed appropriate functionality. The system proved effective, efficient, and met user needs in managing BK services in schools thus enabling BK teachers to focus more on quality counseling with data-based decision making.
Penerapan Metode MAUT dalam Penentuan Kelayakan Tenaga Kerja Indonesia Keluar Negeri dengan Pembobotan ROC Ginting, Leonardo; Edelweis, Edelweis; Irpanto, Irpanto; Hulu, Zulima Berkat; Sembiring, David JM; Surbakti, Asprina Br
Journal Global Technology Computer Vol 4 No 3 (2025): Agustus 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jogtc.v4i3.8292

Abstract

Determining the eligibility of Indonesian Migrant Workers (TKI) to travel abroad is a complex process because it involves many criteria that must be considered objectively. This study proposes the application of the Multi-Attribute Utility Theory (MAUT) method in decision-making by weighting criteria using the Rank Order Centroid (ROC) method. The ROC method is used to generate criteria weights based on priority levels, thus providing a fairer proportion in the calculation. Furthermore, the MAUT method is used to normalize the data, calculate utility values, and determine the final score of each alternative. The purpose of this study is to develop a Decision Support System model that can help determine the eligibility of Indonesian Migrant Workers (TKI) to travel abroad more objectively, measurably, and systematically, so that the selection process does not only rely on subjective considerations, but also uses a quantitative approach to improve the accuracy of the decision results. This study uses five assessment criteria with ten alternatives as data samples. The calculation results show that criteria with higher priorities have a significant influence on the final result. From the data processing process, it was obtained that Alternative A7 had the highest preference value of 0.945 and was recommended as the best alternative, followed by A3 with a value of 0.926 and A9 with a value of 0.865, while the alternative with the lowest score was A8 with a value of 0.608. The results of this study prove that the integration of the ROC and MAUT methods can produce an objective, transparent, and systematic decision support system in determining the feasibility of alternatives, as well as assisting decision makers in a more accurate and measurable selection process.
Implementasi Logika Fuzzy dengan Metode Mamdani untuk Menghitung Durasi Penyiraman Air Otomatis Garingging, Keisya Febrika S.; Khomariah, Khomariah; Astanti, Adelia; Ulfa, Adelia; Sembiring, David JM; Ginting, Devita Permatasari Br
Journal Global Technology Computer Vol 4 No 3 (2025): Agustus 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jogtc.v4i3.8335

Abstract

Savings and Loan Cooperatives (KSP) play a crucial role in providing access to financing for the public, particularly in underbanked areas. However, lending through KSPs often faces challenges related to the accuracy of creditworthiness assessments, which largely rely on subjective assessments and manual procedures, resulting in the risk of non-performing loans. This study aims to develop a creditworthiness prediction model using the Decision Tree algorithm to improve the accuracy and efficiency of the credit decision-making process. The Decision Tree algorithm was chosen for its ability to classify customers based on historical data in a manner that is easy to understand and interpret. In this study, customer data, including attributes such as Borrower Credit History, Financial Status, Income Amount, Employment Status, and Loan Amount, was used to construct a decision tree. The results showed that the Decision Tree model achieved an accuracy of 86.67%, indicating its effectiveness in predicting creditworthiness and its reliability in supporting credit granting decisions in savings and loan cooperatives. This research contributes to reducing the risk of non-performing loans and improving the efficiency of decision-making in savings and loan cooperatives through the application of data mining techniques based on historical customer data analysis.

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