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All Journal Instal : Jurnal Komputer Journal Global Technology Computer Jurnal Sains dan Teknologi Informasi Jurnal Ilmu Pengetahuan dan Teknologi Bagi Masyarakat Journal Of Computer Engineering And Information Technology
Sembiring, David JM
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Social Sciences

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Design and Construction of an Automatic Coffee Drink Mixing Machine Based on Arduino Lestari, Dini; Ashari, Runi; Nasution, Vikram Taufik; Bangun, Zuriah Rezky Br; Sembiring, David JM; Surbakti, Asprina Br
JCEIT: Journal of Computer Engineering and Information Technology Vol. 1 No. 2: JCEIT: Journal of Computer Engineering and Information Technology (March 2025)
Publisher : Karya Techno Solusindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64810/jceit.v1i2.7

Abstract

The development of technological knowledge in Indonesia is growing very rapidly along with increasing technological knowledge such as automatic coffee drink mixers. This automatic coffee brewing system is defined as a system that is defined as a system that is able to make human work easier and shorten time. Therefore, we need a medium that controls via Arduino-based Android control, with the aim of making it easier to access information. This Arduino-based Android control system will make it easier to access automatic coffee drink mixers by setting the appropriate ingredient measurements needed. Through Android control, the process of making coffee drinks automatically becomes optimal and more effective in making coffee drinks. The system used in this automatic coffee drink mixer is via Android control which is carried out using the C programming language which is connected to the MIT invectore Bluetooth App. REFERENCES   Ardiyanto, A., Ariman, & Supriyadi, E. (2021). ALAT PENGUKUR SUHU BERBASIS ARDUINO MENGGUNAKAN SENSOR INFRAMERAH DAN ALARM PENDETEKSI SUHU TUBUH DIATAS NORMAL. Sinusoida, 23(1). Arif Kurniawan. (2018). Rancang Bangun Alat Pembuat Minuman Kopi Otomatis Berbasis Mikrokontroler. UNIVERSITAS TEKNOLOGI YOGYAKARTA. Arifin, N. Y., Borman, R. I., Ahmad, I., Setyaning Tyas, S., Sulistiani, H., Hardiasnyah, A., & Suri, G. P. (2021). Analisa Perancangan Sistem Informasi (Pertama). Yayasan Cendikia Mulia Mandiri. Fahmizal, Mayub, A., Arrofiq, M., & Ruciyanti, F. (2021). Mudah Belajar Arduino dengan pendekatan berbasis Fritzing, Tinkercad dan Proteus. Deepublish. Fikri Alfaridzi, M., & Agustiawan. (2020). Rancang Bangun Mesin Pembuat Air Kopi Dengan Sistem Robotik. Seminar Nasional Industri Dan Teknologi (SNIT), 1, 328–368. Firmawati, N., Farokhi, G., & Wildian, W. (2019). Rancang Bangun Mesin Pembuat Minuman Kopi Otomatis Berbasis Arduino UNO dengan Kontrol Android. JITCE (Journal of Information Technology and Computer Engineering), 3(01), 25–29. https://doi.org/10.25077/jitce.3.01.25-29.2019 FURQAN, A. (2023). PERANCANGAN APLIKASI SIMULASI TES TOEFL BERBASIS ANDROID. UNIVERSITAS ISLAM NEGERI AR-RANIRY. Hamzanwadi, Fathurrahman, I., Wajdi, M. F., Universitas Hamzanwadi, Mandala Putra, H., Universitas Hamzanwadi, Widarina, B. V., & Universitas Hamzanwadi. (2022). Sistem Informasi Geografis Pemetaan Sebaran Data Covid-19 Pada Puskesmas Kerongkong Kabupaten Lombok Timur Berbasis WebImam. Infotek : Jurnal Informatika Dan Teknologi, 5(1), 42–52. https://doi.org/10.29408/jit.v5i1.4392 Hardiyansyah, M. V. (2021). Rancang Bangun Sistem Kontrol Suhu Pada Mesin Oven Kopi Tray Rotary Berbasis Arduino. Jurnal Crankshaft, 4(1), 67–76. https://doi.org/10.24176/crankshaft.v4i1.5915 Janna, N. M., Aisma, & Arsyam, M. (2021). Makanan Dan Minuman Dalam Islam. https://doi.org/10.31219/osf.io/49us8 Khakim, L. (2023). Buku Ajar Mikrokontroler Atmega328 (Moh. Nasrudin, Ed.). PT. Nasya Expanding Management. Laksono, D. T., Ulum, M., & Hakim, L. (2020). Rancang Bangun Pembuat Kopi Otomatis Berbasis Arduino Mega. Jurnal Teknik Elektro Dan Komputer TRIAC, 7(1), 50–97. Naim, M. (2021). BUKU AJAR SISTEM KONTROL DAN KELISTRIKAN MESIN (Moh. Nasrudin, Ed.). PT. Nasya Expanding Management. Pratama, R., Saputra, Z., & Silalahi, P. (2022). MESIN MINUMAN KOPI OTOMATIS BERBASIS IOT. Prosiding Seminar Nasional Inovasi Teknologi Terapan. Samania, N., Nirsal, & Fa’rifah, R. Y. (2020). RANCANG BANGUN APLIKASI E-VOTING PEMILIHAN KETUA UMUM HIMPUNAN MAHASISWA INFORMATIKA (HMTI) UNIVERSITAS COKROAMINOTO PALOPO BERBASIS WEBSITE. D’computare: Jurnal Ilmiah Teknologi Informasi Dan Ilmu Komputer, 10(1). https://doi.org/10.30605/dcomputare.v10i1.27 Suhartono, Hartanto, T. J., Hutahaean, S. DT., Nawir, M., & Dinata, P. A. C. (2023). Buku Ajar Fisika Berbasis Inkuiri: Materi Kajian Rangkaian Listrik Arus Searah. EUREKA MEDIA AKSARA. Suryanto, A., Maliki, M. I., & Universitas Bina Sarana Informatika. (2022). Penerapan Model Rapid Application Development (RAD) Dalam Rancang Bangun Sistem Informasi Warga. Infotek : Jurnal Informatika Dan Teknologi, 5(1), 197–208. https://doi.org/10.29408/jit.v5i1.4887 Triana, D. D., & Sarifah, I. (2023). Membangun Keunggulan Kompetitif Barista dalam Pelayanan Bisnis Kopi Melalui Pelatihan di BBPLK Bekasi.
Monitoring System for Student Internships Using the Rapid Application Development (RAD) Method Kaban, Roberto; Sembiring, David JM; Br Tarigan, Ita Margaretta
Bahasa Indonesia Vol 15 No 02 (2023): Instal : Jurnal Komputer Periode (Juli-Desember)
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalkomputer.v15i02.172

Abstract

This research aims to develop a system that facilitates monitoring activities of students undergoing internships, with a case study on student internship activities at the Indonesian Institute of Technology and Business (ITB Indonesia). The system development method used is Rapid Application Development (RAD), with four structured and interdependent stages in each phase, namely Requirements planning, User Design, Construction, and Cutover. The outcome of this research is a web-based system with a responsive interface across all devices (smartphones, tablets, and laptops). The system includes features for student location-based attendance, student activity reporting at internship sites, student guidance processes with supervising mentors, as well as monitoring the guidance process of students and supervising mentors conducted by the head of the study program.
Comparison Analysis of the SAW and TOPSIS Methods in Determining the Best Teacher (Case Study at SMK Swasta PABAKU Stabat) Naim, Muhammad Akmal; Kaban, Roberto; Sembiring, David JM
JCEIT: Journal of Computer Engineering and Information Technology Vol. 1 No. 1: JCEIT: Journal of Computer Engineering and Information Technology (November 2024)
Publisher : Karya Techno Solusindo

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study compares the Simple Additive Weighting (SAW) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods for determining the best teacher at SMK Swasta PABAKU Stabat. Teacher data was collected from 19 individuals via observation, interviews, and literature review. The web-based decision support system built successfully integrated SAW and TOPSIS to select the top teacher. SAW produced rankings more aligned with manual rankings, boasting 53% accuracy, while TOPSIS yielded 32% accuracy. Additionally, SAW averaged a faster 0.10672 second execution time, contrasted to TOPSIS requiring 0.57004 seconds. Overall, this research offers meaningful insight into the effectiveness and efficiency of applying SAW and TOPSIS for best teacher selection. With superior accuracy and speed, SAW proves the more fitting and appropriate choice of the two methods. REFERENCES [1]        M. Kholis, K. Wicaksono, and R. Riskiyanto, “Analisis Reward Terhadap Kinerja Guru Di SMK Nurul Abror Al- Robbaniyyin Perspektif Ekonomi Islam,” KEADABAN, vol. 4, no. 2, pp. 46–54, Jun. 2023, doi: 10.33650/adab.v4i2.6080. [2]        S. Noer and R. S. S.A.P, “Kebijakan Pemerintah dalam Peningkatan Kualitas Mutu Guru Pendidikan Agama Islam; Analisis Sistematik Literatur Review,” tarbawi, vol. 4, no. 2, pp. 165–195, Aug. 2023, doi: 10.55380/tarbawi.v4i2.520. [3]        Rut Frida Hastuti Nduru and Nehemia Nome, “Peran Soft Skill dan Hard Skill dalam Peningkatan Kualitas Guru Pendidikan Agama Kristen Di Era 5.0,” Coram Mundo, vol. 5, no. 1, pp. 200–216, Apr. 2023, doi: 10.55606/corammundo.v5i1.178. [4]        S. B. Al Maktoum and A. M. Al Kaabi, “Exploring teachers’ experiences within the teacher evaluation process: A qualitative multi-case study,” Cogent Education, vol. 11, no. 1, p. 2287931, Dec. 2024, doi: 10.1080/2331186X.2023.2287931. [5]        E. Rhinesmith, J. C. Anglum, A. Park, and A. Burrola, “Recruiting and Retaining Teachers in Rural Schools: A Systematic Review of the Literature,” Peabody Journal of Education, vol. 98, no. 4, pp. 347–363, Aug. 2023, doi: 10.1080/0161956X.2023.2238491. [6]        D. Hao, “Study on incentive factors and incentive effect differences of teachers in universities and colleges under the view of demographic variables,” BMC Psychol, vol. 11, no. 1, p. 379, Nov. 2023, doi: 10.1186/s40359-023-01426-6. [7]        I. Finefter-Rosenbluh and K. Power, “Exploring preservice teachers’ professional vision: Modes of isolation, ethical noticing, and anticipation in research communities of practice,” Teaching and Teacher Education, vol. 132, p. 104245, Oct. 2023, doi: 10.1016/j.tate.2023.104245. [8]        J. E. Finch, K. Akhavein, I. Patwardhan, and C. A. C. Clark, “Teachers’ self-efficacy and perceptions of school climate are uniquely associated with students’ externalizing and internalizing behavior problems,” Journal of Applied Developmental Psychology, vol. 85, p. 101512, Mar. 2023, doi: 10.1016/j.appdev.2023.101512. [9]        S. Taylor and S. Charlebois, “Teaching dossier guidance for professional faculty: an evidence-based approach for demonstrating teaching effectiveness,” Front. Educ., vol. 9, p. 1284726, Mar. 2024, doi: 10.3389/feduc.2024.1284726. [10]       R. Sabharwal and S. J. Miah, “Evaluating teachers’ effectiveness in classrooms: an ML-based assessment portfolio,” Soc. Netw. Anal. Min., vol. 14, no. 1, p. 28, Jan. 2024, doi: 10.1007/s13278-023-01195-5. [11]       L. Wang et al., “Human-centered design and evaluation of AI-empowered clinical decision support systems: a systematic review,” Front. Comput. Sci., vol. 5, p. 1187299, Jun. 2023, doi: 10.3389/fcomp.2023.1187299. [12]       C. Tjahja, E. Setiawan, G. N. Cahyo, and P. Rosyani, “Penerapan Metode SAW dan Metode TOPSIS dalam Pemilihan Kepala Unit Satuan Pengamanan,” LOGIC: Jurnal Ilmu Komputer dan Pendidikan, vol. 1, no. 2, pp. 153–160, 2023. [13]       A. Pradipta, “Penerapan Metode SAW untuk Evaluasi Kinerja Karyawan di Sektor Pendidikan,” Journal of Information Systems and Technology, vol. 1, no. 1, pp. 14–21, 2024. [14]       D. Supriyadi, “Penerapan Metode Simple Additive Weighting (SAW) Dalam SPK Pencarian Perumahan Residence,” KLIK: Kajian Ilmiah Informatika dan Komputer, vol. 4, no. 4, pp. 2307–2317, 2024. [15]       Y. A. Singgalen, “Penerapan Metode TOPSIS Sebagai Pendukung Keputusan Pemilihan Layanan Akomodasi di Destinasi Wisata Pulau,” mib, vol. 7, no. 3, p. 1386, Jul. 2023, doi: 10.30865/mib.v7i3.6530. [16]       A. Iskandar, “Penerapan Metode TOPSIS Dalam Sistem Pendukung Keputusan Kelayakan Penerima Pinjaman Kredit,” JoSYC, vol. 4, no. 2, pp. 388–396, Feb. 2023, doi: 10.47065/josyc.v4i2.2879. [17]       N. N. Farih and W. Hadikurniawati, “Penerapan Metode AHP dan Metode TOPSIS Dalam Menentukan Asisten Laboratorium Komputer,” vol. 7, 2023. [18]       A. D. Wahyudi and A. R. Isnain, “Penerapan Metode TOPSIS untuk Pemilihan Distributor Terbaik,” vol. 1, no. 2, 2023. [19]       F. Ciardiello and A. Genovese, “A comparison between TOPSIS and SAW methods,” Ann Oper Res, vol. 325, no. 2, pp. 967–994, Jun. 2023, doi: 10.1007/s10479-023-05339-w. [20]       V. Pandey, Komal, and H. Dincer, “A review on TOPSIS method and its extensions for different applications with recent development,” Soft Comput, vol. 27, no. 23, pp. 18011–18039, Dec. 2023, doi: 10.1007/s00500-023-09011-0. [21]       J. Barman, B. Biswas, S. S. Ali, and M. Zhran, “The TOPSIS method: Figuring the landslide susceptibility using Excel and GIS,” MethodsX, vol. 13, p. 103005, Dec. 2024, doi: 10.1016/j.mex.2024.103005. [22]       A. Meyliana, P. T. Rapiyanta, and A. Andriani, “Application of the Rapid Application Development (RAD) Method for Web-Based Financial Management and Wood Inventory Using CodeIgniter,” vol. 4, no. 1, 2024. [23]       R. Kaban and R. J. Nasution, “Penerapan Metode Rapid Application Development (RAD) dalam Perancangan Sistem Pemesanan Menu menggunakan Quick Response (QR) Code,” MEANS, pp. 144–152, Dec. 2020, doi: 10.54367/means.v5i2.920. [24]       I. Riadi, A. Yudhana, and A. Elvina, “Analysis Impact of Rapid Application Development Method on Development Cycle and User Satisfaction: A Case Study on Web-Based Registration Service,” SJI, vol. 11, no. 1, pp. 81–94, Feb. 2024, doi: 10.15294/sji.v11i1.49590.
Development of a Student Grade Conversion System for Off-Campus Learning Activities: A Case Study of ITB Indonesia kaban, Roberto; Sembiring, David JM; Br Tarigan, Ita Margaretta; Br Tarigan, Siti Jamilah
Bahasa Indonesia Vol 17 No 06 (2025): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v17i06.398

Abstract

This study aims to develop a student grade conversion information system for off-campus learning programs at ITB Indonesia. The system integrates with the Academic Information System (SIAKAD) to automate and synchronize grade conversion from off-campus activities. It was developed using the Rapid Application Development (RAD) method, which prioritizes speed and user involvement. The grade conversion process is based on seven assessment components used during off-campus learning activities: activity planning (perencanaan kegiatan), implementation and outcomes (pelaksanaan dan hasil kegiatan), activity reporting (pelaporan kegiatan), personality and social aspects (aspek kepribadian dan sosial), student self-assessment (penilaian diri mahasiswa), peer assessment (penilaian sejawat), and assessment by field supervisors, local authorities, or receiving lecturers at partner institutions (penilaian dari guru pamong, supervisor, aparat desa, atau dosen penerima di perguruan tinggi tujuan). These components are processed and mapped into final scores grouped under academic and non-academic courses, taking into account their relevance to the Program Learning Outcomes (CPL) and Course Learning Outcomes (CPMK). The system provides a real-time dashboard for both students and academic supervisors to monitor the status of grade submission, conversion processes, and final results in a transparent and structured manner.
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.
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.
Co-Authors Aditya Ananda, Aditya AMANDA, RIZKA Angkat, Erlita Natasya Arini, Wulan Ashari, Runi Asprina Br Surbakti, Asprina Br Astanti, Adelia Bangun, Zuriah Rezky Br Br Tarigan, Ita Margaretta Br Tarigan, Siti Jamilah Dahlia, Icha Dewani, Dewani Dini Lestari, Dini Edelweis, Edelweis Fania, Liza Fitriani, Nopita Garingging, Keisya Febrika S. Ginting, Devita Permatasari Br Ginting, Gogor Abiezer Ginting, Jenni Veronika Br Ginting, Leonardo Harmanda, Inke Hulu, Zulima Berkat Irpanto, Irpanto juanda, muhammad Kaban, Roberto Khomariah, Khomariah Lubis, Irfansyah Nuddin Mehuli Br PA, Sinek Meiliyani Br Ginting, Meiliyani Br Melasari, Melasari Naim, Muhammad Akmal Nasution, Vikram Taufik PA, Sinek Mehuli Br Peranginangin, Sinek Mehuli Br Raheliya Br Ginting, Raheliya Br Ramadani, Sindi Fitri Ramles, Polin Sari, Anggun Puspita Setya, Monita Siagian, Evan Edward Sihotang, Ester Ulina Sijabat, Ade Dermawan Silaban, Lenni Wati Sitepu, Yanti Peronika Br siti nurlela Ulfa, Adelia