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Widodo, Agung Mulyo
Universitas Esa Unggul
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Comparison of SVM, KNN, and Naïve Bayes Classification Methods in Predicting Student Transfers at BK Palu School Nugraha, William; Firmansyah, Gerry; Mulyo Widodo, Agung; Tjahjono, Budi
Asian Journal of Social and Humanities Vol. 3 No. 1 (2024): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v3i1.413

Abstract

Student transfers are a significant issue in schools and can affect the dynamics of education and student performance. This research aims to predict student transfers using a comparative analysis of three classification methods: Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Naïve Bayes. The study utilizes historical data from BK Palu School, covering the years 2022 to 2024, which includes demographic, academic, socio-economic, and student quality information. The methodology involves data collection, data preparation, algorithm selection, implementation, and evaluation of the three methods. The performance of the classification methods is assessed using metrics such as accuracy, precision, recall, and F1-score. The results indicate that SVM has the highest accuracy in predicting student transfers, followed by KNN and Naïve Bayes. This study contributes to identifying key factors influencing student transfers and offers schools a robust model to develop targeted strategies for reducing transfer rates. Ultimately, this research provides insights into optimizing student retention and improving the overall quality of education.
Enterprise Architecture Business Model Planning Using EAP Framework (Case Study: PT. Gempita Cahaya Makmur) Mutedi, Ahmad; Mulyo Widodo, Agung; Firmansyah, Gerry; Tjahjono, Budi
Asian Journal of Social and Humanities Vol. 3 No. 1 (2024): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v3i1.416

Abstract

The advancement of technology in a company has an impact on improving business quality. From this observation, architectural planning is a part that is used to build alignment between business strategy and information technology. Architecture within the business domain illustrates how a company conducts business activities and functions to achieve the company's goals. Therefore, the company's business model architecture depicts the current state of architecture by identifying business needs and activities. From this study, the business role of PT. GEMPITA CAHAYA MAKMUR, a company engaged in the procurement of goods and services, especially in the field of wholesale office stationery, printing, photocopier sales, and photocopier and laptop rentals, which has customers from medium-sized companies, large companies, both private and government. The use of the Enterprise Architecture Planning or EAP framework focuses on business architecture. The purpose of this research is expected to produce a blueprint proposal that will be beneficial for PT. GEMPITA CAHAYA MAKMUR to plan the business model architecture that will become the foundation for the design phase of application architecture.
Clustering of Child Stunting Data in Tangerang Regency Using Comparison of K-Means, Hierarchical Clustering and DBSCAN Methods Azzam Robbani, Muhammad; Firmansyah, Gerry; Mulyo Widodo, Agung; Tjahjono, Budi
Asian Journal of Social and Humanities Vol. 2 No. 12 (2024): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v2i12.422

Abstract

This study aims to analyze stunting in children in Tangerang Regency using clustering methods such as k-means, Hierarchical Clustering with Agglomerative Nesting, and Density-Based Spatial Clustering of Applications with Noise (DBSCAN). Stunting is a significant health issue affecting child growth due to chronic malnutrition and recurrent infections. The research revealed that k-means produced the best clustering results with a Silhouette Score of 0.52, indicating its effectiveness in categorizing children based on age, nutritional status, and stunting risk. The k-means method identified three clusters: Cluster 0 (ages 46-55 months, good nutrition, no stunting), Cluster 1 (ages 9-18 months, varied nutritional status, high stunting risk), and Cluster 2 (ages 27-36 months, good nutrition, no stunting). The study suggests preventive actions such as balanced nutrition education, regular health monitoring, complete immunizations, and physical activity, alongside curative measures like nutritional consultations and supplements. The findings provide a framework for targeted preventive and curative interventions, enabling Tangerang Regency's health department to effectively address and reduce stunting rates.
The Comparison Models of Earning Management, CSR, and Intellectual Capital on Firm Value Moderated by Performance Gantino, Rilla; Ruswanti, Endang; Widodo, Agung Mulyo; Iskandar, Deni
Journal of Accounting Research, Organization and Economics Vol 5, No 2 (2022): JAROE Vol. 5 No. 2 August 2022
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jaroe.v5i2.26514

Abstract

Objective This study aims to compare the effect of earnings management, corporate social responsibility (CSR), and intellectual capital on firm value moderated by performance in two different periods, 2015-2019 (before COVID-19 pandemic) and 2015-2020 (9 months of pandemic).Design/methodology This Study used two data year groups, from 2015-2019 and 2015-2020 with purposive sampling technique. The population of 5 sectors and 2 sub-sectors of companies listed on the Indonesia Stock Exchange which consists of basic and chemical industry, consumer goods, mining, Infrastructure, Utilities Transportation, various industries (excluding textile and automotive) sector and the Automotive Components, Textile Garment sub-sector.Results The results show, even though the pandemic lasted 9 months in 2020, the average return on assets (ROA) of the 2015-2020 group decreased, turns out it doesn't have much effect on the strength of ROA to moderate the variable x to y. For 2015-2019 (before COVID-19 pandemic), performance moderates the effect of earnings management, CSR, and intellectual capital on firm value in the textile, automotive and components sub-sectors, various industries, consumer goods sectors and infrastructure and for 2015-2020 (9 months of the pandemic) only textile, automotive and components sub-sectors, various industries, and infrastructure. Partially for 2015-2019, value added intellectual coefficient (VAIC) has a significant effect moderated by performance in the consumer goods infrastructure sector, and automotive, then CSR has a significant effect moderated by performance in the basic industry and textile. Earning management has a significant effect moderated by performance in the basic industry, infrastructure and automotive. The same results for 2015-2020, for earning management. VAIC has a significant effect moderated by performance in consumer goods and infrastructure sector and CSR has a significant effect moderated by performance in textile, basic industry and various industries.Research limitations/implications This study only uses secondary data for 2015-2019 and 2015-2020 and only uses 5 sectors from 9 sectors and does not compare each sub-sector.Novelty/Originality This study obtained a comparison of the model of the influence of earnings management, intellectual capital, and CSR on firm value moderated by performance for 5 sectors and 2 sub-sectors.
Predicting Technical Intern Training Program Trainee Success: A Comparative Machine Learning Analysis For Risk Mitigation Maulana, Syaban; Fatonah, Nenden Siti; Firmansyah, Gerry; Widodo, Agung Mulyo
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/1r93bf26

Abstract

Japan's demographic crisis has increased demand for the Technical Intern Training Program (TITP). However, for Sending Organizations (SOs) in Indonesia, this process carries high financial risk due to an upfront talent funding scheme, where significant costs (up to IDR 35,000,000) are paid in advance. Trainee failure (dropouts or runaways) leads to substantial bad debt. This research aims to develop and validate a robust machine learning model for risk mitigation. We compare XGBoost and Random Forest on a dataset of 784 historical trainee records, characterized by extreme class imbalance (75.5% majority class). To address prior methodological weaknesses and prevent data leakage, we implement a 10-fold stratified cross-validation pipeline incorporating StandardScaler and SMOTE. The results show XGBoost (mean macro F1-Score: 0.5470 ± 0.15) significantly outperforms Random Forest (mean macro F1: 0.5098 ± 0.15), which is confirmed as statistically significant (p=0.0384) by a paired t-test. Furthermore, SMOTE is validated as a superior imbalance strategy compared to class_weight (p=0.0076). SHAP analysis identified 'contract duration' and lifestyle factors (e.g., 'alcohol consumption') as key predictors. The final model effectively predicts 'Runaway' cases (F1=0.533) but struggles with 'Training Dropouts' (F1=0.170), indicating a key limitation and a need for temporal features in future work.
Workshop Pengenalan Aplikasi CPU OS Simulator untuk Penjadualan First-Come First-Served (FCFS) Agung Mulyo Widodo; Roesfiansjah Rasjidin; Muhamad Bahrul Ulum; Binastya Anggara Sekti; Nixon Erzed; Ryan Putra Laksana; Budi Tjahjono; Hendry Gunawawan
IKRA-ITH ABDIMAS Vol. 7 No. 3 (2023): Jurnal IKRAITH-ABDIMAS Vol 7 No 3 November 2023
Publisher : Universitas Persada Indonesia YAI

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

Abstract

CPU OS Simulator merupakan aplikasi simulator yang mendukung proses pembelajaran yang mensinergikan dari sisi perangkat keras maupun perangkat lunak. Dalam aplikasi ini terdapat modul penjadualan First Come First Serve (FCFS) merupakan algoritma penjadwalan sistem operasi yang secara otomatis mengeksekusi permintaan (request by priority) dan proses antrian sesuai urutan kedatangannya (arrival). Algoritma scheduling untuk proses (assembly dan visualisasi) dengan menggunakan CPU OS Simulator, aplikasi ini lebih mudah dioperasikan dan user-friendly bagi pengguna. Dalam algoritma jenis ini, proses yang me-request CPU terlebih dahulu mendapatkan alokasi CPU terlebih dahulu. Proses penjadualan dikelola dengan metode antrian First-In First-Out (FIFO), dalam ruang lingkup sistem operasi dengan fokus penjadualan algoritma FCFS (First Come First Serve). Metode workshop dilaksanakan secara daring menggunakan zoom cloud meeting, dengan peserta dosen yang berminat akan aplikasi tersebut dan para anak didik yang mau mengenal memahami konsep dari sistem operasi. Aplikasi CPU OS simulator merupakan salah satu aplikasi yang bersifat free-ware sehingga dapat di unduh secara gratis bagi para pengguna (dosen dan atau mahasiswa). Hasil akhir dari pelatihan bagi pengguna akan melihat dan mengerti tahapan demi tahapan dari proses intruksi hingga compile yang disajikan bentuk simulasi dan visualisasi (histogram) serta beberapa parameter dari proses tersebut (average waiting time, average burst time, tick count dan instruction count).
Risk Management Domain Application Plan Electronic Based Governance System (SPBE) Case Study: Tangerang Government Communications and Informatics Service Ipung Sutejo, Bayu Sulistiyanto; Widodo, Agung Mulyo; Firmansyah, Gerry; Tjahjono, Budi
Jurnal Indonesia Sosial Sains Vol. 4 No. 09 (2023): Jurnal Indonesia Sosial Sains
Publisher : CV. Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jiss.v4i09.878

Abstract

Various applications of SPBE have been produced by the Central and Regional Authorities and have contributed to the efficiency and effectiveness of government maintenance. Nevertheless, the results of the SPBE development show a relatively low maturity rate and a high gap between the Central Authority and the Regional Government. Based on the results of the 2018 SPBE evaluation of 616 Central and Regional Government Instances, the National SPBE Index reached a value of 1.98 with a sufficient predicate of the target SPBE index of 2.6 out of 5 levels with a good prediction. Reviewed from the access of Central and Regional Authorities, the average Central Authorities SPBE index was 2.6 with a good predicate, while the average Regional Government SPBE Index was 1.87 with a sufficient Predicate. Reviewed from the target access spread, 13.3% of Central and Regional Authorities have reached or exceeded the target SPBE 2.6 index, while 86.7% have not yet reached the SPBE 2.0 index target. This shows that there are problems in the development of the SPBE nationally. On the other hand, the development of ICT 4.0 trends is a key external factor that can drive the realization of integrated SPBE implementation and improved quality of SPBE services that make it easier for users in accessing government services. The vision is a benchmark in implementing the integrated implementation of SPBE in the Central and Regional Authorities to produce integrative, dynamic, transparent, and innovative government bureaucracy, as well as improving the quality of integrated, effective, responsive, and adaptive public services.
Implementation of Vector-Based Melody Extraction for Plagiarism Detection Using Szymkiewicz-Simpson Coefficient Wardhana, Nindyo Artha Dewantara; Widodo, Agung Mulyo; Firmansyah, Gerry; Tjahjono, Budi
Jurnal Indonesia Sosial Sains Vol. 5 No. 04 (2024): Jurnal Indonesia Sosial Sains
Publisher : CV. Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jiss.v5i04.1084

Abstract

Plagiarism is topical within the music industry. It is filled with circumstances such as the potential of massive losses coupled with a “false-positive” court ruling due to the blurred line of plagiarism factor. This research aims to solve the gray line of music plagiarism by exploring the potential of the Szymkiewicz-Simpson coefficient toward musical aspects of music. Melody and Rhythm are chosen as the main features to focus on in the research. MIDI files of music involved in court cases are used as data for the study, with limitations put on what cases can be used for the research. Using a threshold range of 0.1 to 0.25, detection accuracies for melodic plagiarism range from 45% to 60%, while rhythm plagiarism ranges from 60 to 65%. This shows that the algorithm of plagiarism detection has a tendency to detect non-plagiarism cases and is more effective towards rhythm plagiarism detection rather than melodic plagiarism detection against existing plagiarism cases.
Implementasi Algoritma Multi-Factor Evaluation Process Pada Website Sistem Pendukung Keputusan Minat Siswa Pratama, Fajar; Widodo, Agung Mulyo
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 8 No. 3 (2024): IKRAITH-INFORMATIKA Vol 8 No 3 November 2024
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikraith-informatika.v8i3.4363

Abstract

After graduating from high school, students often have difficulty in determining the right major.The challenges faced include the lack of clear guidelines and criteria in choosing a major, as wellas the selection process which is still traditional and subjective. To overcome these obstacles, thisarticle suggests the implementation of a website-based Decision Support System (DSS) using theMulti-Factor Evaluation Process (MFEP) algorithm. This DSS was developed to help studentschoose a major that suits their interests and potential. The methods used in this study includeliterature studies, observations, interviews, and questionnaires. The results of the study indicatethat the use of a web-based DSS with the MFEP algorithm is able to provide more effective andobjective recommendations in helping students choose a major.
Analyzing Coverage Probability of Reconfigurable Intelligence Surface-aided NOMA Widodo, Agung Mulyo; Wijayanto, Heri; Wijaya, I Gede Pasek Suta; Wisnujati, Andika; Musnansyah, Ahmad
JOIV : International Journal on Informatics Visualization Vol 7, No 3 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.3.2054

Abstract

Along with the explosive growth of wireless communication network users who require large frequency bands and low latency, it is a challenge to create a new wireless communication network beyond 5G. This is because installing a massive 5G network requires a large investment by network providers. For this reason, the authors propose an alternative beyond 5G that has better quality than 5G and a relatively lower investment value than 5G networks. This study aims to analyze the downlink of the cooperative non-orthogonal multiple access (NOMA) network, which is usually used in 5G, combined with the use of a reconfigurable intelligence surface (RIS) antenna with decode and forward relay mechanisms. RIS is processed with a limited number of objects utilizing Rayleigh fading channels. The scenario is created by a user who relays without a direct link for users near the base station and with a direct link for users far from the base station. Under the Nakagami-m fading channel, the authors carefully evaluated the probability of loss for various users as a function of perfect channel statistical information (p-CSI) utilizing simply a single input-output (SISO) system with a finite number of RIS elements. As a key success metric, the efficiency of the proposed RIS-assisted NOMA transmission mechanism is evaluated through numerical data on the outage probability for each user. The modeling outcomes demonstrate that the RIS-aided NOMA network outperforms the traditional NOMA network
Co-Authors Achmad Fansuri Achmad Randhy Hans Adhi Fernandes Gamaliel Adilah Widiasti Agam Aprianto Ahmad Musnansyah Ahmad Mutedi Akbar, Habibullah Alexander Alexander, Alexander Alivia Yufitri Andriana, Dian Annazma Ghazalba Arif Pami Setiaji Arisandi Langgeng Tardiana Asmara, Qiqi Azzam Robbani, Muhammad Bayu Sulistiyanto Ipung Sutejo Binastya Anggara Sekti Budi Aribowo Budi Tjahjono Budi Tjahjono Budi Tjahyono Budi Tjahyono Budi Tjahyono Budilaksono, Sularso Cahya Darmarjati Catur Agus Sulistyo Deni Iskandar Deni Iskandar Desy Prastyani Doni Antoro Dulbahri Dulbahri Dwiaji, Lingga Dwiputra, Dedy Eko Prasetyo Endang Ruswanti Erry Yudhya Mulyani Ety Nurhayati Euis Heryati Fadlilatunnisa, Fanny Fatonah, Nenden Siti Fernandes Gamaliel, Adhi Fikri Saefullah Gerry Firmansyah Gerry Firmasyah Ghazalba, Annazma Gilang Romadhanu Tartila Gunawan, Sholeh Gusti Fachman Pramudi Hadi, Muhammad Abdullah Hani Dewi Ariessanti Hartono Hartono Haryoto, Iin Sahuri Hendaryatna Hendaryatna Hendry Gunawawan Heri Wijayanto I Gede Pasek Suta Wijaya Ichwani, Arief Ilham Banuaji Irawan, Bambang Ismiyati Meiharsiwi Iwan Setiawan Izhar Rahim Joniwan Joniwan Karisma Trinanda Putra kartini, kartini Kevin Valeri Khairurrahman, Rifqi Krisogonus Wiero Baba Kaju Kundang Karsono Juman Kundang Karsono Juman Kundang Karsono Juman Kus Hendrawan Muiz Lingga Dwiaji Lisdiana Lisdiana Lisdiana Lisdiana Lukman Cahyadi Made Aka Suardana Martin Saputra Massie, Julius Ivander Maulana, Syaban Meiharsiwi, Ismiyati Meria, Lista MF. Arrozi Adhikara Muhammad Azzam Robbani Muhammad Fajrul Aslim Muhammad Hadi Arfian Mutedi, Ahmad Muttaqin, Naufal Hafizh Nina Nurhasanah, Nina Nindyo Artha Dewantara Wardhana Nixon Erzed Nizirwan Anwar Nugraha, William Nurfilael, Gagas Nurfilae Panji Ramadhan Yudha Putra Hadjarati Pratama, Fajar Prayitno Purwano SK Rachman, Riyandi Patu Rahaman, Mosiur Randhy Hans, Achmad Restamauli br Nainggolan Rian Adi Pamungkas Ricky Salim Ricky Salim Rifqi Khairurrahman RILLA GANTINO Riris Septiana Sita Dewi Rizki Faro Khatiningsih Rizky Aulia Roesfiansjah Rasjidin Ryan Putra Laksana Sholeh Gunawan Simorangkir, Holder Suhendry, Mohammad Roffi Sunardi, Sunardi Syaban Maulana Syamsul Bahri Tyara Regina Nadya Putri Ulum, Muhamad Bahrul Ummanah Ummanah, Ummanah Vitri Tundjungsari Wahid Abdul Azis Wardhana, Nindyo Artha Dewantara Wibowo, Yudha Widiasti, Adilah William Nugraha Wisnujati, Andika Yanathifal Salsabila Anggraeni Yessy Oktafriani Yohanes Bagas Ari Widatama Yudha Putra Hadjarati, Panji Ramadhan Yulhendri Yulhendri