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All Journal Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Jurnal Teknoinfo IJID (International Journal on Informatics for Development) Jurnal Tekno Kompak Building of Informatics, Technology and Science Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Jurnal ABDINUS : Jurnal Pengabdian Nusantara Jurnal Teknik Informatika (JUTIF) JTIKOM: Jurnal Teknik dan Sistem Komputer Jurnal Teknologi dan Sistem Tertanam Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Ilmiah Infrastruktur Teknologi Informasi Jurnal Teknologi dan Sistem Informasi 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) Jurnal Ilmiah Sistem Informasi Akuntansi (JIMASIA) Paradigma Journal of Engineering and Information Technology for Community Service Journal of Computing and Informatics Research Bulletin of Informatics and Data Science Jurnal Ilmiah Computer Science CHAIN: Journal of Computer Technology, Computer Engineering and Informatics Journal of Data Science and Information System Journal of Artificial Intelligence and Technology Information Journal of Information Technology, Software Engineering and Computer Science Jurnal Media Jawadwipa Global Science: Journal of Information Technology and Computer Science AI and Developmental Insights in Education (AIDIE)
Priandika, Adhie Thyo
Universitas Teknokrat Indonesia
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 Library & Information Science Mathematics Social Sciences Other

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Kombinasi Metode Pembobotan Entropy dan MARCOS Dalam Seleksi Penerimaan Karyawan Divisi Keuangan Wahyuni, Dita Septia; Priandika, Adhie Thyo
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.5835

Abstract

The selection of employees for the Finance Division is a crucial process to ensure that the selected individuals have the appropriate skills and qualifications to handle complex financial responsibilities. The main problems in the selection of Finance Division employees often revolve around the difficulty in accurately assessing the candidate's technical skills and analytical abilities. The experience and qualifications listed on a resume do not necessarily reflect the candidate's apparent ability to handle complex financial situations or in the face of stringent regulatory challenges. This study aims to apply a combination of entropy and MARCOS weighting methods in the selection of employees of the Finance Division, in order to improve the objectivity and accuracy of the decision-making process. Through this approach, to identify candidates who best suit the company's needs and requirements based on a comprehensive multi-criteria analysis. The combination of Entropy and MARCOS weighting methods in the selection of financial division employees provides a comprehensive and objective approach in decision-making. The Entropy method is used to objectively determine the weight of the criteria based on the degree of uncertainty of the information provided by each criterion, the MARCOS method is used to evaluate and rank candidates based on their proximity to the ideal solution and the distance from the anti-ideal solution. The results of the financial division employee acceptance selection ranking show that Budi Santoso occupies the top position with the highest score of 4.8848. These results provide a clear picture of each candidate's relative position in terms of final assessment, and can serve as a basis for more targeted and objective hiring decisions.
Penerapan Kombinasi Metode Pembobotan Entropy dan Technique for Order of Preference by Similarity to Ideal Solution Dalam Pemilihan Karyawan Terbaik Ningsih, Ristia; Priandika, Adhie Thyo
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.5896

Abstract

The process of selecting the best employees often faces various challenges that can affect the objectivity and fairness of the results. One of the main issues is the objectivity of selecting the best employees, where appraisers may have personal preferences or prejudices that influence their decisions in making the best employee selection. This study aims to apply a more objective and systematic approach in assessing employee criteria and integrate these factors into a more structured decision-making process. By using the entropy weighting method to objectively determine the weight of the criteria and TOPSIS to rank employees based on their proximity to the ideal solution, this study is expected to provide a solid foundation for more accurate and reliable decision-making in human resource management. The application of a combination of entropy weighting and TOPSIS methods in the selection of the best employees offers a comprehensive and structured approach in overcoming the complexity of human resource evaluation. The entropy weighting method is used to objectively determine the weight of the criteria based on data variation, thereby reducing subjectivity in assessment. Meanwhile, TOPSIS is used to rank employees based on their proximity to the positive ideal solution and their distance from the negative ideal solution. The combination of these two methods allows decision-makers to integrate different aspects of employee criteria. The results of the ranking of the best employees gave the results of the first best employee with a final preference score of 0.97858 obtained by Aisyah, the best second employee with a final preference score of 0.79125 obtained by Misri, and the third best employee with a final preference score of 0.69712 obtained by Rudi Setiawan.
Sistem Pendukung Keputusan Pemilihan Pelanggan Terbaik Menggunakan Kombinasi Pembobotan Logarithmic Least Square dan MOORA Rifaldo, Setiawan; Priandika, Adhie Thyo
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.5897

Abstract

The best customers are individuals or groups who not only transact frequently but also provide more value to the business through loyalty, positive feedback, and referrals to others. They typically show a high level of satisfaction with the product or service offered, potentially bringing in new customers and improving the company's reputation. Selecting the best customers is often faced with a variety of issues that can affect the accuracy and effectiveness of the process. One of the main problems that occurs is the lack of a model used in determining the best customers. The purpose of this research is to implement a system that is able to effectively and accurately identify the best customers by integrating the LLS weighting technique and the MOORA method. In addition, this study also aims to overcome the shortcomings of existing weighting and evaluation methods by integrating the two techniques, providing a more robust and adaptive solution in the context of data-based decision-making. The ranking results in determining the best customers obtained the result, namely Sabtoni occupies the first position with the highest score of 0.47344. Furthermore, Zahra is in second place with a score of 0.39815, followed by Tuty with a value of 0.39498 in third place.
Kombinasi Metode Analytical Hierarchy Process (AHP) dengan Metode Weighted Product (WP) pada Sistem Pendukung Keputusan Pemilihan Rumah Ideal Wantoro, Agus; Lutfy, Azza’zunda Choibar; Permata, Permata; Priandika, Adhie Thyo; Aryani, Venty
Jurnal Pendidikan dan Teknologi Indonesia Vol 4 No 9 (2024): JPTI - September 2024
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.485

Abstract

Pemilihan rumah ideal merupakan keputusan penting yang memerlukan pertimbangan berbagai aspek untuk memastikan pilihan yang optimal. Rumah ideal biasanya dinilai dari beberapa kriteria utama, seperti harga, luas tanah, luas bangunan, jumlah kamar tidur, dan jarak lokasi dari pusat aktivitas. Namun, proses pemilihan rumah ideal sering menghadapi tantangan, seperti kesulitan dalam membandingkan berbagai alternatif yang memiliki berbagai kriteria dengan bobot yang berbeda. Penelitian ini bertujuan mengatasi permasalahan tersebut dengan menggunakan pendekatan metode sistem pendukung keputusan yaitu Pembobotan Matriks Berpasangan dari metode AHP dan Weighted Product (WP). Metode AHP digunakan untuk menentukan bobot relatif dari setiap kriteria berdasarkan penilaian dan perbandingan berpasangan. Metode WP digunakan untuk menghitung dan membandingkan alternatif berdasarkan bobot yang telah ditentukan. Data yang digunakan diambil dari situs web properti www.rumah123.com, yang mencakup informasi tentang (a) harga, (b) luas tanah, (b) luas bangunan, (c) jumlah kamar tidur, dan (d) jarak lokasi rumah di Bandar Lampung. Berdasarkan hasil analisis perhitungan menggunakan kombinasi metode Analytic Hierarchy Process (AHP), dan Weighted Product (WP) didapatkan nilai total untuk masing-masing alternatif yaitu (a) Mahkota Cluster 2 sebesar 0,2077, (b) Budaya Residence sebesar 0,2074, (c) Griya Anzana 3 sebesar 0,1968, (d) Raih Persada Residence sebesar 0,1960, (e) Ar-Rahman Residence sebesar 0,1921, (f) New Cordy Residences sebesar 0,1806, dan (g) The Rose Mansion sebesar 0,1737. Hasil perangkingan didapatkan Mahkota Cluster 2 merupakan alternatif rumah ideal terbaik di Bandar Lampung. Alternatif ini unggul dalam beberapa kriteria penting seperti jumlah kamar tidur, luas bangunan, serta harga yang kompetitif, meskipun jaraknya tidak yang terdekat dari pusat aktivitas. Penelitian ini memberikan informasi berupa rekomendasi bagi masyarakat yang ingin memilih rumah ideal agar tidak salah mengambil keputusan.
Penerapan Platform DigiLearnHub Untuk Meningkatkan Kemampuan Literasi dan Numerasi Siswa Serta Pelayanan Administrasi di SMAS Kesuma Bakti Priandika, Adhie Thyo; Saputra, Very Hendra; An’ars, M. Ghufroni; Darwis, Dedi
Journal of Social Sciences and Technology for Community Service (JSSTCS) Vol 5, No 2 (2024): Volume 5, Nomor 2, September 2024
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jsstcs.v5i2.4731

Abstract

SMAS Kesuma Bakti Bekri (SMAS-KBB) has several priority issues that need to be addressed, includingThe educational report score for literacy skills at SMAS-KBB is still categorized as poor, with a score of 33.33. The educational report score for numeracy skills at SMAS-KBB is also categorized as poor, with a score of 35.56. The management of the school's administrative and financial services system has not been optimized. Based on these priority issues, the proposed solutions areImplementing the DigiLearnHub Platform. Providing training and assistance to teachers in creating and designing engaging literacy and numeracy learning content to be used on the DigiLearnHub platform. Providing training and assistance to students on the use of the DigiLearnHub platform and the importance of improving literacy and numeracy learning as a foundation for mastering science and technology. Implementing an application that can be accessed digitally through the website and mobile for real-time School Administration System. Based on the evaluation results, there was an 84.85% improvement in teachers' ability to create literacy and numeracy learning content. Furthermore, based on post-test results conducted with students, there was an increase in the average student score, with literacy achieving 87.2 and numeracy 86.2. This indicates an improvement in literacy and numeracy learning quality, which is expected to prepare students for the ANBK. In addition, the school administrative service application has improved the school's administrative and financial services. According to survey results, 87% of students and parents expressed high satisfaction with the services provided through the school administration and financial application.
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
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.
Hybrid Music Recommendation System Using K-Means Clustering and Neural Collaborative Filtering for Spotify Playlist Personalization Rastomi Pamungkas; Permata Permata; Rakhmat Dedi Gunawan; Adhie Thyo Priandika
Building of Informatics, Technology and Science (BITS) Vol 7 No 4 (2026): March 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i4.9181

Abstract

Personalizing music recommendations has become a significant challenge on music streaming platforms such as Spotify due to the vast number of available songs and the limitations of conventional recommendation systems in accurately capturing user preferences. In addition, traditional single-method recommendation approaches often face the cold start problem, which reduces the effectiveness of generated recommendations. Therefore, this study aims to develop and evaluate a hybrid recommendation system that integrates the K-Means Clustering algorithm and Deep Collaborative Filtering based on Neural Matrix Factorization to improve the relevance of music playlist recommendations. The dataset used in this study consists of more than 15,151 Spotify songs obtained from the Spotify dataset available on Kaggle. The dataset was processed through several stages including data inspection, data cleaning, feature selection, and standardization. Audio features used in the analysis include danceability, energy, acousticness, instrumentalness, valence, tempo, and duration. The optimal number of clusters was determined using the Elbow Method and Silhouette Score, resulting in five clusters with a relatively balanced data distribution. The clustering results were then used as the basis for Cluster-Based Filtering to narrow the search space of candidate songs before being processed by the Neural Matrix Factorization model. Performance evaluation was conducted using Hit Ratio at rank 10 and Normalized Discounted Cumulative Gain at rank 10. The proposed model achieved values of 0.1110 and 0.0507, respectively, indicating that the integration of clustering and deep collaborative filtering can improve the effectiveness and personalization of music recommendation systems. This study contributes by proposing a hybrid recommendation framework that integrates clustering-based item grouping with deep collaborative filtering to improve recommendation efficiency and playlist personalization in large-scale music streaming platforms.
Co-Authors Ade Dwi Putra Ade Surahman Adi Adi Sucipto Adi Sucipto, Adi Aditya Saputra Afitra Tanthowi Agus Irawan Agus Wantoro Ahdan, Syaiful Ahmad Devin Alfitra Tantowi Anas Apririansyah Andi Nurkholis Anggun Dewi Utami Anggun Maylani Anisa Lestari Anissa Anggraini Annisa Anggraini An’ars, M. Ghufroni Ari Najeri Ari Sulistiyawati Ari Sulistiyawati Arif Budiman Aryani, Venty Bagas Aditama Bayu Pratama Bustanul Ulum Dedi Darwis Dedi Irawan Dellys Okta Wibowo Dina Ros Muryana Doni Riswanda Doni Riswanda Dwi Rahma Sari Dwi Utari Iswavigra Dyah Ayu Megawaty Ebi Supriyadi Edison, Arif Rahman Edvan Agus Pratama Eky Khoiril Ulama Erliyan Redy Susanto Farhan Nopransyah Putra Fazri Syanofri Fenty ariany Fitratullah, M. Fuad Surya Mawinar Gantar Galang Toyyibah Gunawan, Rakhmat Dedi Harry Anggono Hayatunnisa, Destaria Heni Sulistiani Ilham Nasul Fathon Muhaji. P Imam Asyrofi Alfarisi Imroatun Qoniah Intan Anggrenia Isnain, Auliya Rahman Jeni Sagita Jeni Sagita Putri Johansyah Johansyah josua Armando silalahi Junhai Wang Koeswara, Wawan Krisna Widi Nugraha Linda Fatmawati Lutfy, Azza’zunda Choibar M Qurrota A’yun Meiwidia Seftiana Mico Fahrizal Mirza Wijaya Putra Muhamad Amirudin Muhamad Yusran Muhammad Alba Muhammad Indigo Muhammad Rahadiyan Bagaskara Muhaqiqin muhaqiqin Muhtad Fadly Ningsih, Ristia Octaviansyah, A. Ferico Parjito Parjito Parningotan Simamora Pasaribu, A. Ferico Octaviansyah Pasha, Donaya Permata Permata Permata Permata Permata Permata Permata, Permata Prabowo, Fransiskus Wahyu Sandy Prasetyo Bella Ramadhanu Prastowo, Agung Tri Rahmat Dedi Gunawan Rakhmad Dedi Gunawan Rakhmat Dedi Gunawan Rastomi Pamungkas Riduan Napianto Ridwan Janata Rifaldo, Setiawan Rio Efendi Riski Etien Malovi Rizki Putra Utama Rohaniah Rohaniah Rohmat Indra Borman Rosella, Rosella S. Samsugi Safira, Wilga Salsabila Indriyani Sanriomi Sintaro Sari, Kevinda Setiawansyah Setiawansyah Setiawansyah Setiawansyah Setyani, Tria Sherly Octavia Sinta Agita Sari Stevan Corry Polanco suaidah suaidah Sumanto Temi Ardiansah Tia Nanda Pratiwi Tien Yulianti Tiwuk Widiastuti Very Hendra Saputra Wadiyan Wadiyan Wahyu Widiantoro Wahyudi, Agung Deni Wahyuni, Dita Septia Wilga Safira Yogi Suwarno YOHANA TRI UTAMI, YOHANA TRI Yulaikha Mar’atullatifah Yuri Rahmanto Yusma Indonesian