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All Journal Building of Informatics, Technology and Science Jurnal ABDINUS : Jurnal Pengabdian Nusantara Jurnal Teknik Informatika (JUTIF) Journal Social Science And Technology For Community Service Jurnal Pendidikan dan Teknologi Indonesia Bulletin of Computer Science Research JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Telematics and Information Technology (TELEFORTECH) Paradigma Jurnal Ilmiah Computer Science CHAIN: Journal of Computer Technology, Computer Engineering and Informatics
Priandika, Adhie Thyo
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media

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Penerapan Kombinasi Metode Entropy dan SMART Dalam Pemilihan Kepala Divisi Keuangan Yusran, Muhamad; Priandika, Adhie Thyo
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.517

Abstract

The election of the Head of the Finance Division is an important decision that requires an objective and systematic evaluation of the existing candidates. This study proposes the application of a combination of Entropy and SMART (Simple Multi-Attribute Rating Technique) methods to support the decision-making process in the election of the Head of the Finance Division. The Entropy method is used to objectively determine the weight of the criteria, based on the distribution of candidate assessment data, while the SMART method is applied to assess each candidate based on predetermined criteria. The results of the ranking of candidates for the Head of the Finance Division are based on the final score obtained by each candidate. Based on these results, candidate A5: Eko Prabowo ranks highest with a score of 0.6667, followed by A7: Gita Susanti with a score of 0.6097. These results show that Eko Prabowo is the most superior candidate to be considered as the Head of the Finance Division, based on the assessment method used in this study. The combination of these two methods allows for more accurate, transparent and accountable decision-making, as it is based on objective and structured calculations.
Sistem Pendukung Keputusan Pemberian Kredit Kendaraan Menggunakan G2M Weighting dan Metode Comprehensive Distance Based Ranking Simamora, Parningotan; Priandika, Adhie Thyo
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.518

Abstract

Providing vehicle loans is one of the important services in the financing sector that requires an objective and accurate evaluation process of prospective debtors. This research aims to develop a Decision Support System (SPK) that can assist in the selection process of providing vehicle credit by combining the G2M Weighting and Comprehensive Distance-Based Ranking methods. The G2M method is used to objectively determine the weight of criteria based on multi-assessment analysis, while the CDR method is used to conduct alternative rankings based on a comprehensive distance to ideal and non-ideal solutions. The results of the calculation using the comprehensive distance-based ranking method, Gita ranked first with a final value of -0.0098, showing that it has the closest distance to ideal conditions and the furthest from non-ideal conditions compared to other alternatives. In second place is Ahmad with a value of -0.0067, followed by Hadi in third place with a value of -0.0042. The final results show that the combination of these two methods is able to provide effective recommendations in identifying potential debtors who are most deserving of credit, taking into account all assessment criteria in a comprehensive and structured manner. This system is expected to improve decision-making accuracy, speed up the selection process, and minimize the risk of errors in vehicle lending.
Implementation of the Standard Deviation Multi-Objective Optimization by Ratio Analysis Method in Warehouse Staff Recruitment Selection Putra, Farhan Nopransyah; Priandika, Adhie Thyo
Paradigma - Jurnal Komputer dan Informatika Vol. 27 No. 2 (2025): September 2025 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v27i2.8373

Abstract

The warehouse staff selection process has a crucial role in ensuring optimal operational efficiency and logistics management. A selection approach that considers aspects of technical skills, work experience, and compatibility with the organization's culture is essential in ensuring the efficiency and effectiveness of logistics management. The labor selection process, including in the context of warehouse staff recruitment, often faces challenges due to subjectivity in decision-making. The implementation of the SD-MOORA method is the main goal in this study in the process of accepting warehouse staff to improve the objectivity and accuracy of candidate selection, the results of this study are expected to contribute to improving the efficiency of the labor selection process and support data-based decision-making in human resource management. The data used in this study consists of 8 candidates and 6 criteria in the selection of warehouse staff admission. The final outcome of optimizing the SD-MOORA method for ranking warehouse staff admissions shows that GT secured the top rank with a value of 0.3827, indicating it is the most suitable candidate according to the selection criteria. AN followed in second place with a score of 0.3752, and BD placed third with a score of 0.3579. This study significantly contributes to advancing the development of decision support systems for warehouse staff selection by applying the SD-MOORA method. By objectively considering the weighting of criteria using standard deviations, this approach enhances both the accuracy and transparency of candidate rankings.
INFORMATION TECHNOLOGY GOVERNANCE ANALYSIS USING COBIT 5 FRAMEWORK AT SMPN 18 BANDAR LAMPUNG Salsabila Indriyani; Priandika, Adhie Thyo
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 2 (2024): JUTIF Volume 5, Number 2, April 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.2.1826

Abstract

So far, the management of Information Technology at SMPN 18 Bandar Lampung has not held an information technology governance analysis, so that the application of information technology infrastructure cannot be known at the maturity level. This study aims to determine the level of maturity of the application of information technology required information technology governance analysis. The method used in the COBIT 5 framework is up to phase 4 - Plan Programe, the calculation used is by finding the statistical average or mean value in the form of the total value of the various items contained in the questionnaire. The results of this research the average maturity index value is 3.4 and (maturity level as is) in the APO, BAI, and MEA domains, at level 3 in the APO, BAI, MEA domains. Based on the results of the research, the researcher provides suggestions regarding the procedures chosen based on the research findings to help the information technology infrastructure of SMPN 18 Bandar Lampung reach the required maturity level.
Program Sekolah Binaan : In House Training Peningkatan Kompetensi Public Speaking Dalam Kepemimpinan Siswa Di SMAN 2 Gedong Tataan Sulistiyawati, Ari; Yulianti, Tien; Rahmanto, Yuri; Fitratullah, M.; Priandika, Adhie Thyo
Journal of Social Sciences and Technology for Community Service (JSSTCS) Vol 4, No 2 (2023): Volume 4, Nomor 2, September 2023
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jsstcs.v4i2.3199

Abstract

Kegiatan Pengabdian kepada Masyarakat ini dilakukan pada mitra sekolah binaan di SMA Negeri 2 Gedong Tataan. Program yang dilakukan adalah In house training peningkatan kompetensi public speaking yang melibatkan semua pengurus OSIS dan perwakilan siswa kelas X dan XI sesuai program kerja yang disetujui oleh pihak sekolah.  Permasalahan yang dialami oleh mitra yaitu: belum optimalnya kemampuan public speaking untuk menunjang kepemimpinan yang berkualitas dalam organisasi di sekolah. Solusi yang diusulkan untuk mengatasi permasalahan tersebut adalah peningkatan softskill bagi siswa terpilih untuk mengikuti bimbingan dan pelatihan public speaking dalam keterampilan berbicara. Target luaran dari kegiatan PKM Sekolah Binaan ini adalah 1) peningkatan kemampuan siswa yang diukur melalui kuesioner, 2) artikel publikasi di jurnal ABDIMAS terakreditasi nasional, 3) artikel berita kegiatan yang dishare di media massa online,  dan 4) video kegiatan di link youtube LPPM Teknokrat
Combination of Logarithmic Least Square Weighting and MAUT Method for Best Employee Selection in Retail Companies Saputra, Aditya; Priandika, Adhie Thyo
Paradigma - Jurnal Komputer dan Informatika Vol. 27 No. 1 (2025): March 2025 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/mf9wad40

Abstract

Selecting the best employees plays a crucial role in enhancing the performance of retail companies. Given that each employee has unique roles, responsibilities, and working conditions, creating a truly fair and consistent assessment standard can be challenging. Additionally, subjective factors such as personal bias or preferences of the assessor can influence the evaluation outcome. The integration of LLSW and the MAUT method in employee selection offers a systematic approach that combines precise weighting with multi-criteria utility analysis. This combination aims to improve the accuracy, objectivity, and transparency of the decision-making process. By utilizing both methods, retail companies can establish a more effective, transparent, and data-driven selection system, ensuring that the best employees are chosen based on rational and fair evaluations. The results of the employee selection process using LLSW and MAUT showed that Employee RS ranked first with the highest score of 0.7485, indicating the strongest qualifications compared to the other candidates. Employee LK and Employee ML ranked second and third with scores of 0.6035 and 0.572, respectively, demonstrating solid performance. These selection outcomes can assist companies in recruiting the most suitable workforce for their operational needs and vision, ultimately leading to improved productivity and service quality in the long run. The main contribution of this research is capable of improving accuracy and fairness in employee performance evaluation. This approach reduces the subjectivity that often occurs in conventional assessment processes in the retail sector, as well as providing a basis for transparent and measurable decision-making.
Perbandingan Random Forest dan XGBoost Untuk Prediksi Penjualan Produk E-Commerce Rumah Madu Hayatunnisa, Destaria; Permata, Permata; Priandika, Adhie Thyo; Gunawan, Rakhmat Dedi
Building of Informatics, Technology and Science (BITS) Vol 7 No 3 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i3.8491

Abstract

Inventory management is one of the main challenges for small and medium enterprises (SMEs), including Rumah Madu in Bandar Lampung, where honey stock levels are often determined based on estimation rather than precise calculation. This study aims to analyze and compare the performance of the Random Forest and XGBoost algorithms in predicting honey sales to achieve more measurable stock management. The dataset consists of 1,699 honey sales transactions that have undergone cleaning, feature transformation, and standardization processes. The variables used include honey type, unit price, day, month, holiday status, and promotion indicators. Modeling was conducted using a time-series split approach, where historical data served as the training set and recent data as the testing set. The evaluation results show that Random Forest achieved an MAE of 24.35, RMSE of 29.04, and R² of -0.9685, while XGBoost achieved an MAE of 25.50, RMSE of 30.58, and R² of -1.1825. The negative R² values indicate that both models were unable to explain data variation optimally, with performance falling below a simple baseline. Nevertheless, the feature importance analysis revealed that unit price and honey type were the dominant factors influencing sales. This study highlights the need for further model development through parameter optimization and improved data quality to enhance prediction accuracy.
Peningkatan Kemampuan Guru SMK Kridawisata di Masa Pandemi Covid-19 Melalui Pengelolaan Sistem Pembelajaran Daring Ahdan, Syaiful; Sucipto, Adi; Priandika, Adhie Thyo; Setyani, Tria; Safira, Wilga; Sari, Kevinda
Jurnal ABDINUS : Jurnal Pengabdian Nusantara Vol 5 No 2 (2021): Volume 5 Nomor 2 Tahun 2021
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/ja.v5i2.15591

Abstract

Today's online learning technology has created a new paradigm in the process of implementing learning. Face-to-face activities between teachers and students are no longer a necessity to gain knowledge in school. SMK Kridawisata has adequate facilities and infrastructure to support the learning process such as classrooms and laboratories, but there is no system that is able to apply the learning process in networks that can overcome the problems of the standardized learning process during the Covid-19 pandemic. The solution for implementing online learning systems is expected to increase productivity, especially in the learning process, and to optimize the knowledge and ability of teachers in utilizing online-based learning systems in order to overcome problems that occur when teachers are unable to attend. Online learning systems are built using a learning management system (LMS) platform with the availability of features needed in the learning process online.
Co-Authors Adi Sucipto, Adi Aditya Saputra Agus Wantoro Ahdan, Syaiful An’ars, M. Ghufroni Ari Sulistiyawati Aryani, Venty A’yun, M Qurrota Dedi Darwis Edison, Arif Rahman Fitratullah, M. Gunawan, Rakhmat Dedi Hayatunnisa, Destaria Koeswara, Wawan Lutfy, Azza’zunda Choibar Ningsih, Ristia Octaviansyah, A. Ferico Permata, Permata Prabowo, Fransiskus Wahyu Sandy Putra, Farhan Nopransyah Putri, Jeni Sagita Rifaldo, Setiawan Rohmat Indra Borman Rosella, Rosella Safira, Wilga Salsabila Indriyani Sari, Kevinda Setyani, Tria Simamora, Parningotan Tien Yulianti Very Hendra Saputra Wahyuni, Dita Septia Yuri Rahmanto Yusran, Muhamad