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All Journal Jurnal Teknologi Industri Pertanian Seminar Nasional Informatika (SEMNASIF) JOIN (Jurnal Online Informatika) Abdimas Pedagogi: Jurnal Ilmiah Pengabdian kepada Masyarakat JOIV : International Journal on Informatics Visualization Jurnal Abdimas BSI: Jurnal Pengabdian Kepada Masyarakat Jurnal Ecodemica : Jurnal Ekonomi Manajemen dan Bisnis Jurnal Teknik Informatika STMIK Antar Bangsa JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Ekonomi, Manajemen Akuntansi dan Perpajakan (Jemap) J I M P - Jurnal Informatika Merdeka Pasuruan Applied Information System and Management Jurnal Teknoinfo Jurnal Nasional Komputasi dan Teknologi Informasi Energi & Kelistrikan Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika CSRID (Computer Science Research and Its Development Journal) Jurnal Ilmu Komputer dan Bisnis Aisyah Journal of Informatics and Electrical Engineering Jurnal Sistem informasi dan informatika (SIMIKA) Journal of Innovation and Future Technology (IFTECH) TIN: TERAPAN INFORMATIKA NUSANTARA Journal of Intelligent Computing and Health Informatics (JICHI) Jurnal Sistem Informasi Jurnal Sains Indonesia Bulletin of Computer Science Research Journal of Students‘ Research in Computer Science (JSRCS) Journal Software, Hardware and Information Technology Jurnal Mandiri IT J-Intech (Journal of Information and Technology) Jurnal Pustaka Data : Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer Jurnal Sains dan Teknologi Jurnal Sains Informatika Terapan (JSIT) Paradigma Indonesian Journal Computer Science (ijcs) Jurnal Ilmiah Teknik Informatika dan Komunikasi Innovative: Journal Of Social Science Research Jurnal Komputer dan Teknologi (JUKOMTEK) Bulletin of Artificial Intelligence Riau Jurnal Teknik Informatika Journal of Information Technology
Sumanto, Sumanto
Universitas Bina Sarana Informatika
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COMBINATION OF LOGARITHMIC PERCENTAGE CHANGE AND GREY RELATIONAL ANALYSIS FOR BEST ADMINISTRATION STAFF SELECTION Sumanto Sumanto; Mochamad Wahyudi
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 1 (2024): JITK Issue August 2024
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i1.5564

Abstract

The best administrative staff are individuals who are able to maintain the smooth operation of the organization with high efficiency and precision. One of the main problems is subjectivity in assessment that can cause dissatisfaction among employees. Sometimes, assessments are based more on personal relationships than objective performance, thus creating a sense of unfairness. The purpose of this study, using a combination of LOPCOW and GRA in determining the best administrative staff to develop a holistic and data-driven evaluation approach for the optimal administrative staff selection process. This process involves a comprehensive assessment based on various criteria, including work efficiency, accuracy, multitasking ability, and excellence in communication and problem solving. LOPCOW provides a strong objective basis by considering significant changes in performance data through logarithmic percentage changes, while GRA helps in identifying and understanding the relationship of similarities and differences between alternatives based on given criteria. By integrating these two methods, organizations can combine the advantages of LOPCOW's objectivity with the power of GRA's relational comparison analysis, resulting in a more comprehensive and accurate performance evaluation. The results of the ranking of the selection of the best administrative staff show that the first best administrative staff was obtained by Staff Name AH with a GRG value of 0.1666, the second best administrative staff was obtained by Staff Name RW with a GRG value of 0.1569, the third best administrative staff was obtained by Staff Name ES with a GRG value of 0.1266.
Sistem Pendukung Keputusan Kelayakan Kredit Pada PT.BPR DP TASPEN Dengan Metode TOPSIS Indriani , Karlena; Sumanto , Sumanto; Christian , Ade; Ahmad Yani , Ahmad Yani; Ruli , Ahmad Rais; Marita , Lita Sari
Journal of Students‘ Research in Computer Science Vol. 4 No. 2 (2023): November 2023
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/q6t2ed19

Abstract

This study focuses on analyzing the feasibility of pension loan applicants for state civil servants at PT. BPR DP TASPEN, with a focus on the use of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) as an alternative analysis method. Previously, PT. BPR DP TASPEN uses a subjective evaluation method to assess the feasibility of loan applicants, which leads to potential risks and errors in the analysis. In this study, the authors recommend the use of TOPSIS as a support decision-making system to standardize the analytical process. TOPSIS was chosen for its efficiency in reducing the calculation time and ease of implementation. This method uses criteria and alternatives to calculate, produces the best alternative based on a weighted bobot, and provides the final decision. The results of the study indicate that TOPSIS provides a good solution for determining the feasibility of pension loan applicants. By considering criteria such as age, pension, debt, bank loan, health history, and income, only seven out of 40 loan applicants met the best criteria, which were close to the ideal positive solution. The selected applicants were recommended for approval as pension loans by the company, reducing the potential risks of credit and improving the accuracy of the selection of loan criteria.
Accurate and Objective Lecturer Appraisal System: Implementation of the LOPCOW Method Sumanto, Sumanto; Radiyah, Ummu; Supriyatna, Adi; Pujiastuti, Lise; Yani, Ahmad; Marita, Lita Sari
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol 21, No 2 (2024): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v21i2.10188

Abstract

This research proposes the use of the Logarithmic Precursor Chain-Driven Objective Weighting (LOPCOW) method to evaluate the best lecturers in universities.  The LOPCOW method ensures that the assessment covers all aspects of lecturer quality and performance, including education, research, community services, discipline, commitment, cooperation skills, and innovation. The evaluation of lecturers using the scores and ratings provided showed that CDE lecturers were the best, with the highest score of 0.715.  CDE lecturers showed high consistency in all aspects assessed, especially in education, research, and community service.  This was followed by MNO lecturers (0.676), STU lecturers (0.668), XYZ lecturers (0.637), and AFI lecturers (0.627). In conclusion, highly ranked lecturers showed strong dedication to the Tridharma of higher education, with consistent performance and a positive impact on the academic community and the general public.  Future research should focus on developing strategies to improve lecturers' teaching quality by applying new educational technologies and evaluating their impact on student learning. 
OPTIMIZING ELECTRICITY SUBSIDIES: A TOPSIS-BASED DECISION-MAKING APPROACH Amin, Ruhul; Christian, Ade; Radiyah, Ummu; Sumanto, Sumanto; Hariyanto, Hariyanto; Yani, Ahmad
Jurnal Teknoinfo Vol 18, No 1 (2024): Januari
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jti.v18i1.3608

Abstract

A individual or household is said to be in poverty if their income is insufficient to cover even the most basic requirements. According to BPS, 40% of Indonesians live in the country with the weakest economy. The use of power subsidies is one of the government's strategies for combating poverty. To combat poverty, the government works with PT. PLN to implement an electrical subsidy scheme that distributes payments to disadvantaged neighborhoods. The goal of the subsidy is to ensure the availability of power while assisting underprivileged customers and those who haven't heard from PT. PLN so they may take part in enjoying electrical energy. However, there are still challenges when there are several procedures, which makes it difficult to make judgments since they must take into account numerous factors. Using TOPSIS to solve 10 possibilities, including the following, is one way to get around the FMADM's various requirements: job, income, dependents, vehicle assets, home ownership, building area, source of drinking water, electrical power range, kind of floor, and type of house wall. According to the study's precise findings, only 11 residents out of 20 submissions received immediate recommendations for receiving power subsidies without having to wait a lengthy period. Additionally, although 9 people received recommendations for aid, only 1 received a recommendation against receiving support.
Sistem Pendukung Keputusan Rekomendasi Hotel Bintang Tiga Menggunakan Kombinasi Entropy dan Combine Compromise Solution Wahyudi, Agung Deni; Sumanto, Sumanto; Setiawansyah, Setiawansyah; Yudhistira, Aditia
Bulletin of Artificial Intelligence Vol 3 No 1 (2024): April 2024
Publisher : Graha Mitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62866/buai.v3i1.142

Abstract

Three Star Hotels are lodging places that offer the perfect balance between comfort, adequate facilities, and affordable prices. With a friendly atmosphere and professional service, the hotel welcomes guests from various backgrounds warmly. One of the problems in choosing a Three Star Hotel is confusion due to variations in quality and facilities among hotels that have similar ratings. Although they share the same categories, the standards and services offered can vary greatly. This can make potential guests find it difficult to choose the right hotel that suits their preferences and needs. In addition, some hotels may not meet guest expectations due to issues such as poor cleanliness or facilities that do not function properly, which can generate dissatisfaction. The combination of Entropy weighting and the Combine Compromise Solution method can be a powerful approach in providing three-star hotel recommendations to potential guests. By combining these two methods, it can produce more informed and objective three-star hotel recommendations. Entropy weighting helps in assessing the relative importance of each criterion, while the Combine Compromise Solution allows us to reach a compromise solution that blends different preferences and criteria. The result is recommendations that are more accurate and tailored to potential guests' needs and preferences. The recommendation results showed that AN Hotel with a value of 1,782 got 1st place, AL Hotel with 1.271 got 2nd place, and YN Hotel with 1,145 got 3rd rank.
PEMILIHAN DOSEN TELADAN BERPRESTASI DENGAN METODE MULTI ATTRIBUTE UTILITY THEORY (MAUT) Pujiastuti, Lise; Amin, Ruhul; Hariyanto, Hariyanto; Supriyatna, Adi; Christian, Ade; Sumanto, Sumanto
Journal of Innovation And Future Technology (IFTECH) Vol 6 No 2 (2024): Vol 6 No 2 (August 2024): Journal of Innovation and Future Technology (IFTECH)
Publisher : LPPM Unbaja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/iftech.v6i2.3398

Abstract

This study aims to evaluate the performance of lecturers in higher education using the Multi Attribute Utility Theory (MAUT) method. The main problem faced is the complexity of assessing lecturers based on the Tri Dharma of Higher Education-education, research, and community service-as well as the challenges of subjectivity and inefficiency in manual assessment. MAUT was chosen due to its ability to consider various assessment criteria in a structured and objective manner and follows the standardization of outstanding lecturer assessment including: Education, Research, Community Service, Discipline, Commitment, Cooperation Ability and Ability to innovate. The results showed that Adi Fajar Insani had the best performance with a total final score of 1.01, while Dian Eka Fitriani had the lowest score of 0.00. The MAUT method proved effective in providing a comprehensive and fair assessment, overcoming the limitations of traditional methods that are not thorough. The conclusion of this study is that the application of MAUT can improve the objectivity, efficiency, and accuracy of the lecturer evaluation process, thus encouraging the improvement of lecturer quality and productivity in various fields. Further research is recommended to develop more relevant assessment criteria, involve larger samples, and explore the use of more sophisticated technology to support the assessment process.
Supplier Selection Very Small Aperture Terminal using AHP-TOPSIS Framework Sumanto, Sumanto; Indriani, Karlena; Marita, Lita Sari; Christian, Ade
Journal of Intelligent Computing & Health Informatics Vol 1, No 2 (2020): September
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v1i2.6290

Abstract

There are several methods of decision making VSAT IT goods suppliers such as: Promethee, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Analytical Hierarchy Process (AHP). Decision-making in the selection of the best suppliers, we have the basis of assessment criteria, and we will also be faced with more than one alternative. If alternatives are only two, maybe still easy for us to choose, but if the alternative is a lot of choice, it is quite difficult for us to decide. Analytical Hierarchy Process (AHP) is a technique that was developed to help overcome this difficulty, because the Analytical Hierarchy Process (AHP) is a form of decision-making model with many criteria. One of the reliability of the Analytical Hierarchy Process (AHP) is able to perform simultaneous analysis and integrated between the parameters of qualitative or quantitative. In this study the authors use six criteria and alternatives 6, the results of these alternatives will be obtained perangkingan alternative used as a reference supplier selection VSAT IT goods company Total EP Indonesie
Development of a Decision Support System Based on New Approach Respond to Criteria Weighting Method and Grey Relational Analysis: Case Study of Employee Recruitment Selection Megawaty, Dyah Ayu; Damayanti, Damayanti; Sumanto, Sumanto; Permata, Permata; Setiawan, Dandi; Setiawansyah, Setiawansyah
JOIV : International Journal on Informatics Visualization Vol 9, No 1 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.1.2744

Abstract

The purpose of this research is to propose a new approach in the criteria weighting method using the RECA method, the RECA method can help provide a systematic and structured framework for determining criteria weights in multi-criteria decision making. The determination of weights using the RECA method is to increase objectivity and accuracy in the candidate assessment and selection process by determining the appropriate weight for each criterion based on responses and assessments from experts or stakeholders. Testing the RECA Method with Multi Attribute Decision Making (MADM) techniques is an important step in measuring the effectiveness of the RECA Method in the context of multi-criteria decision making. Ranking tests using Spearman correlation between the RECA method and other methods such as SAW with a correlation value of 1, MOORA with a correlation value of 0.9636, MAUT with a correlation value of 0.9515, WP with a correlation value of 0.891, SMART with a correlation value of 0.9636, and TOPSIS with a correlation value of 0.8788 show a high level of rank consistency between the RECA method and these methods. This indicates that the RECA Method has a strong ability to generate similar candidate rankings with other methods, validating its reliability and consistency in the context of multi-criteria decision making. Implications for further research include exploring the application of the RECA method in different decision-making contexts other than recruitment, such as performance evaluation, project selection, or supplier selection. Further research could investigate the integration of the RECA method with other decision-making methods or algorithms to improve its performance and applicability in complex decision environments. Comparative studies with larger sample sizes and diverse datasets can provide deeper insights into the effectiveness and reliability of the RECA method compared to other methods.
ANALISIS MACHINE LEARNING UNTUK PREDIKSI PENYAKIT PARU-PARU MENGGUNAKAN RANDOM FOREST Christian, Ade; Hariyanto, Hariyanto; Yani, Ahmad; Sumanto, Sumanto
Journal of Innovation And Future Technology (IFTECH) Vol. 7 No. 1 (2025): Vol 7 No 1 (Februari 2025): Journal of Innovation and Future Technology (IFTECH
Publisher : LPPM Unbaja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/iftech.v7i1.3906

Abstract

Lung diseases, including COPD, lung cancer, and asthma, are serious global health issues, causing over seven million deaths annually. Advanced technologies, such as deep learning and the Random Forest algorithm, have been effectively utilized to detect and classify lung diseases from imaging data with high accuracy. This study aims to demonstrate the effectiveness of Random Forest in predicting lung diseases. The dataset used consists of 30,000 records with 11 attributes, collected from Kaggle and processed using Orange software version 3.36.2. The implementation of the Random Forest algorithm was conducted with 10 decision trees and six attributes considered at each split. The model was tested using Cross Validation with 10 folds. The testing results showed an AUC value of 0.993, indicating a very high level of accuracy. A confusion matrix was used to measure the model's performance through various metrics, including accuracy, precision, recall, F1-score, and AUC. This model achieved high accuracy, with ROC AUC values of 0.453 for predicting the presence of lung disease and 0.547 for predicting its absence. These results confirm that the Random Forest algorithm is an effective predictive tool for identifying lung diseases. This study makes a significant contribution to the development of more accurate and efficient diagnostic techniques, assisting medical professionals in identifying lung diseases in patients. With a deeper understanding of how this algorithm operates in the healthcare domain, it is expected to significantly enhance the quality of patient diagnosis and care.
Klasterisasi Data Produksi Daging Sapi Menggunakan Algoritma K-Means Orange Data Mining Ramadani, Achmes Dade; Hilmy Ibrahim, Farras; Hidayat, Manarul; Habibullah, Ahmad; Sumanto, Sumanto; Kuswanto, Andi Diah
Jurnal Pustaka Data (Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer) Vol 5 No 1 (2025): Jurnal Pustaka Data (Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitekt
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakadata.v5i1.1013

Abstract

     Produksi daging sapi merupakan salah satu komponen penting dalam sektor peternakan yang mendukung ketahanan pangan nasional. Mengingat fluktuasi produksi dari tahun ke tahun dan perbedaan karakteristik antar wilayah, diperlukan metode analisis yang tepat untuk mengolah data secara efektif. Penelitian ini bertujuan untuk mengelompokkan data produksi daging sapi di Indonesia selama periode 2021 hingga 2024 menggunakan algoritma K-Means Orange Data Mining. Proses analisis mengikuti tahapan CRISP-DM, mulai dari pemahaman bisnis hingga deployment. Data yang digunakan diperoleh dari Badan Pusat Statistik dan diproses untuk menghasilkan tiga klaster utama: wilayah dengan produksi daging sapi tinggi, rendah, dan sedang. Hasil penelitian menunjukkan bahwa algoritma K-Means Orange Data Mining mampu mengelompokkan data produksi daging sapi secara efektif ke dalam beberapa klaster yang berbeda. Orange Data Mining turut membantu proses analisis data dengan tampilan antarmuka visual yang inovatif dan hasil yang mudah diinterpretasikan. Temuan ini diharapkan menjadi acuan dalam perumusan kebijakan strategis peternakan dan perencanaan distribusi produksi berbasis data. Hasil klasterisasi ini memberikan gambaran kepada pemerintah mengenai tingkat produksi daging sapi di setiap wilayah, sehingga memungkinkan pengambilan kebijakan atau langkah-langkah strategis yang lebih tepat dan sesuai dengan kondisi masing-masing wilayah berdasarkan hasil klasterisasi.
Co-Authors Achmad Rivai Syahputra Ade Budiman, Ade Ade Christian Ade Christian Ade Christian, Ade Adi Pangestu Adi Supriyatna Aditia Yudhistira Agung Wibowo Agus Buono Ahmad Habibullah Ahmad Yani ahmad yani Ahmad Yani , Ahmad Yani Andi Diah Kuswanto Andri Amico Anggreani, Namira Anita Adelia Syahfitri Apip Supiandi Ari Sulistiyawati Ari Sulistiyawati Arshad, Muhammad Waqas Arya, Yudi Aulia Rachmat, Daffa Azkia, Farah Diba Bib Paruhum Silalahi Bismo Raharjo, Yohanes Aryo Budhi Adhiani Christina Budi Santoso Budiman, Ade Surya Cahya, Titus Dwi Christian , Ade Damayanti Damayanti Dedi Darwis Dedi Triyanto DENY KURNIAWAN Dewi, Revinta Arrova Diah, Andi Dyah Ayu Megawaty Dyani Kalyana Mitta Eka Dyah Setyaningsih Eka Putri Alvi Syahrina Elisabeth Sri Hendrastuti Fahrian Faiz Djarot, Raihan Jamal Fajar Akbar Fajrian, Ihsan Fardha Hasykir Faruk Ulum Fathur Rismansyah Ganda Wijaya Ganda Wijaya, Ganda Hafis Nurdin Harianto Harianto Hariyanto HARIYANTO HARIYANTO Hartanti Hartanti Hidayat, Manarul Hilmy Ibrahim, Farras Imam Budiawan Indah Purwandani Indra Chaidir, Indra Indra, Ahmad Indriani , Karlena Indriyanti, Zahra Kiky Dwi Insani Abdi Bangsa Jumadi, Yakobus Linus Jumaryadi, Yuwan Junhai Wang Kadir, Fauwas Abdul Karlena Indriani Karlisa Priandana Kotjek, Rafie Kuswanto, Andi Diah Laura Gabriel da Silva Lia Mazia, Lia Lita Sari Marita Maharani Rona Makom Mantriwira, Daniel Mardinawat Mardinawat Marundrury, Aberahamo Onoma Megawaty, Dyah Ayu Mochamad Wahyudi Muhammad Furqon Prasetyo Nabilla, Adinda Naufal Hermawan, Rezan Nirwana Hendrastuty Noviyanto Nur Rachmat Nugraha Nurfia Oktaviani Syamsiah Oprasto, Raditya Rimbawan Paduloh Paduloh Pasaribu, A. Ferico Octaviansyah Permata, Permata Prasetyo, Romadhan Edy Pribadi, Denny Pricillia Pujiastuti, Lise Rafi Kurniawan Ramadani, Achmes Dade Ramadhan, Muhammad Gilang Ramadhani, Varla Octavia Rani, Maulidina Cahaya Rasendriya, Rafi Ratiyah* Ratiyah Reynaldi , Reynaldi Rian Hidayat Rifda Ilahy Rosihan Riska Aryanti Riska Aryanti Rizal Maulana Rizqi Ramadhani, Muhammad Roida Pakpahan Ruhul Amin Ruhul Amin Ruhul Amin, Ruhul Ruli , Ahmad Rais Rumidjan Rumidjan, Rumidjan Rusda Wajhillah Ryan Randy Suryono Sanriomi Sintaro Setiawan, Dandi Setiawansyah Setiawansyah Sri Hendrastuti, Elisabeth Sri Sugiharti SUKAMTI . Sumarna Sumarna Sumarna Sumarna Teguh Budhi Santosa Tri Widian Ratnasari Ulum, Faruk Umam, Hairul Ummu Radiyah, Ummu Vera Agustina Yanti Wahyudi, Agung Deni Wang, Junhai Wardani, Maidy Tri Wattilah, Florentina Wijaya, Filzah Yanuar Laik, Abraham Adrian Yundari, Yundari Yuri Rahmanto Zidan, Muhammad `Diah Kuswanto, Andi