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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sistemasi: Jurnal Sistem Informasi JOURNAL OF APPLIED INFORMATICS AND COMPUTING IJISTECH (International Journal Of Information System & Technology) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) JURIKOM (Jurnal Riset Komputer) Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Sistem Komputer dan Informatika (JSON) TIN: TERAPAN INFORMATIKA NUSANTARA Brahmana : Jurnal Penerapan Kecerdasan Buatan MEANS (Media Informasi Analisa dan Sistem) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) IJISTECH Journal of Applied Data Sciences Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Journal of Informatics Management and Information Technology KLIK: Kajian Ilmiah Informatika dan Komputer Bulletin of Information Technology (BIT) BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer BEES: Bulletin of Electrical and Electronics Engineering Journal of Artificial Intelligence and Engineering Applications (JAIEA) JOMLAI: Journal of Machine Learning and Artificial Intelligence Jurnal Teknik Mesin, Industri, Elektro dan Informatika Journal of Informatics, Electrical and Electronics Engineering Infolitika Journal of Data Science Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Irfan Sudahri Damanik
STIKOM Tunas Bangsa
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Sistem Pendukung Keputusan Penentuan Pemberian Insentif Pegawai THL Menggunakan Metode Promethee Pada Kantor Walikota Pematangsiantar Jaka Sepridho; Irfan Sudahri Damanik; Harly Okprana
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 2 No. 3 (2021): Mei 2021
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v2i3.2853

Abstract

Pematangsiantar Mayor Office is an institution that is used and functions to serve and protect the community. This paper proposes a decision support system research using the Promethee method. Promethee is one of several methods of determining the order or priority in multi-criteria analysis. This writing uses the Promethee method as a step in determining the provision of incentives for freelance daily staff at the Pematangsiantar Mayor's Office. In this study the authors took 10 alternatives with 5 assessment criteria including absenteeism, achievement, behavior, long history of work and teamwork. With the highest result obtained by alternative 9 on behalf of Triono with a value of 0.422 and the lowest result obtained by alternative 6 on behalf of Soraya with a value of -0.211.
Optimizing Disaster Response: A Systematic Review of Time-Dependent Cumulative Vehicle Routing in Humanitarian Logistics Dedy Hartama; Wanayumini Wanayumini; Irfan Sudahri Damanik
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 10 No. 3 (2024): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v10i3.29686

Abstract

Effective delivery of aid during disasters is crucial for mitigating impacts and ensuring well-being. A major challenge in humanitarian logistics is optimizing vehicle routing to maximize efficiency and minimize delivery times. which included 50 studies published between 2012 and 2022. We used the prism method to guide the process of choosing a study, which started from 200 Abstract which is identified and ends with 50 appropriate studies for in -depth analysis. This systematic literature review (SLR) examines the Time-Dependent Cumulative Vehicle Routing Problem (TDCVRP) in humanitarian logistics, identifying VRP variants, their applications, and effectiveness in disaster scenarios. Using a comprehensive search and PRISMA guidelines, the review highlights the importance of optimization models and advanced algorithms. Applications include aid delivery, evacuation management, and facility location optimization, though challenges like computational complexity and reliance on real-time data persist. The review identifies research gaps and suggests future research should focus on integrating advanced methods and improving practical applicability in disaster responses.
Global Inflation Forecasting Using Stacking Ensemble with Elastic Net Meta-Learner Integrating Random Forest, XGBoost, and LightGBM Wildhani, Fauriza; Wanto, Anjar; Damanik, Irfan Sudahri
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 3 (2026): JUTIF Volume 7, Number 3, June 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.3.5599

Abstract

Inflation dynamics have become increasingly complex due to economic volatility and nonlinear interactions, challenging the reliability of conventional forecasting models; therefore, this study develops a robust global inflation forecasting framework using a hybrid stacking ensemble that integrates Random Forest, XGBoost, and LightGBM as base learners with Elastic Net as a regularized meta-learner, applied to annual inflation data from 2000–2024 across five major economic blocs (G7, Europe, BRICS, ASEAN, and the Americas) after temporal feature engineering and time-series–preserving validation; the results demonstrate strong and consistent predictive performance, with very high accuracy in Europe (R² = 0.9282) and the G7 (R² = 0.9122), and the globally trained stacking model (R² = 0.7866) substantially outperforming the region-specific ASEAN model (R² = 0.5243), confirming the advantage of cross-country learning; this research advances informatics and computer science by providing a scalable and stable ensemble learning framework for macroeconomic time-series forecasting in volatile environments, supporting the development of AI-driven economic and policy analytics systems.
Implementation Data Mining of Employement Contract Exten-sion at Indosat Using Naïve Bayes Andini Fadila Sari; M. Safii; Dedi Suhendro; Irfan Sudahri Damanik
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (992.868 KB) | DOI: 10.59934/jaiea.v1i1.52

Abstract

Contract employees are company resources in carrying out oprasional activities for a certain time based on an agreement or contract. Every company that uses a work contrak system every year, there must be employees who are extended and not renewed. Employees will get additional contracts if they have good performance. In this case to determine whether an employee is extended or not extended his work contract, there is difficulty in determining it and requires a long time and process. Therefore, this research was conducted to help guarantee the extension of the employee’s work contract by classifier it into the labes “Eligble” and “Not Feasible” which has 4 variables for the process of employees who will be extended or not. The four variables are age, years of service, aspects of delay, achievement. In this study, the alternatives used as samples were employees at PT. Indosat Ooredoo. The number of data tested is 5 employees with two classes. From the results of the calculation of the Naïve Bayes Algorithm, it is obtained classification with 3 employees eligible class and 2 employees not eligible class. The results of this study found that the level of accuracy of 100.00%.
PREDICTION OF PRODUCT SALES RESULTS USING ADAPTIVE NEURO FUZZY INFERENCE SYSTEM (ANFIS) Dolli Sari Sinaga; Agus Perdana Windarto; Rizki Alfadillah Nasution; Irfan Sudahri Damanik
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 2 (2022): February 2022
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1579.262 KB) | DOI: 10.59934/jaiea.v1i2.73

Abstract

This study aims to optimize profits and minimize losses from product sales at X Market has achieved in the future. The data used in this study were obtained directly from X Market Trade by observing and interviewing. X Market Tradingis one of the industries that produces and sells food products to be marketed in the region and outside the region. The data to be processed is the result of the sale of food products at X Market uses the adaptive neuro fuzzy inference system (ANFIS) method which is a combination of Fuzzy Logic and Artificial Neural Networks. The data used is monthly sales data from 2018 to 2020 as many as 36 data. From a total of 36 data, it will be divided into 2 types of training and test data distribution, namely 90:10 with a total of 60 epochs and a learning rate range of 0.1 – 0.9. From the research results obtained the highest accuracy of 88.55% on 90% training data and 10% test data with a learning rate of 0.6. It was concluded that the ANFIS method could be implemented in predicting the sales of tofu. By doing this research is expected to provide input to X Market in optimizing profits and minimizing losses from product sales in the future.
Co-Authors Abdi Rahim Damanik Achmad Noerkhaerin Putra Agus Perdana Windarto Agustinus Liberty Pasaribu Andini Fadila Sari Anjelita, Mawaddah Azi Arisandi Azi Guntur Chairul Fadlan Chintya Carolina Situmorang Cici Astria Dea Dwi Rizki Tampubolon Dedi Suhendro Dedi Suhendro Dedi Suhendro Dedi Suhendro Dedy Hartama Dedy Hartama Dedy Hartama Dedy Hartama Deny Franata Pasaribu Dermawan, Sabaruddin Dewi, Rafiqa Dewinta Marthadinata Sinaga Dinda Nabila Batubara Dolli Sari Sinaga Eka Irawan Eka Irawan Eka Irawan Eka Irawan Eka Irawan Eka Irawan Eka Irawan F Fauziah Fachry Abda El Rahman Fajar Rudi Sartomo Samosir Fikri Wicaksono Frskila Parhusip Guntur, Azi Hadinata, Edrian Hanifah Urbach Sari Hanne Lore Br Siagian Hartama, Dedy Hasudungan Siahaan Hendry Qurniawan Heru Satria Tambunan Heru Satria Tambunan Heru Satria Tambunan, Heru Satria Hutasoit, Rahel Adelina Ika Okta Kirana Ilham Syahputra Saragih Ilham Syaputra Saragih Indah Pratiwi M.S Indra Gunawan Ira Audita Irawan Irawan Irnanda, Khairunnissa Fanny Irvanizam, Irvanizam Jaka Sepridho Jaya Tata Hardinata Laila Kumalasari M Fauzan M FAUZAN M Fauzan M Fauzan M. Fauzan M. Safii Manurung, Hotben Marina Rajagukguk Masduki Nizam Fadli Masitha Masitha Masitha, Masitha Mawaddah Anjelita Mian Manimpan Siahaan Mira Ariffiani Mita Ariffiani Muhammad Aliyul Amri Muhammad Fachrur Rozy Muhammad Ifnu Suhada Muhammad Ifnu Suhada Napitupulu, Flora Sabarina Nasution, Rizki Alfadillah Ningsih, Sri Rahayu Nur Arief Nur Hasanah Lubis Nurhidayana Nurhidayana Okprana, Harly P, Dini Rizky Sitorus Paulus Hendrico Silalahi Primatua Sitompul Rahel Nita Trides Siahaan Ria Annisa Saragih Ridho Hayati Alawiah Roni Kurniawan S Saifullah Sabaruddin Dermawan Sahendra Fahreza Saifullah Saifullah Sandy Putra Siregar Saputra, Widodo Saragih, Ilham Syaputra Saragih, Ria Annisa Sari, Hanifah Urbach Sari, Winda Permata Sepridho, Jaka Siahaan, Mian Manimpan Sinaga, Waris Pardingatan Siregar, Sandy Putra Siti Hadija siti rodiah Solikhun Solikhun Solikhun Sri Rahayu SRI RAHAYU Sri Rahayu Ningsih Sri Wulandari Suhada Suhada Suhada Suhada Suhada, Suhada Suhada, Muhammad Ifnu Suhendro, Dedi Sumantri Sihombing Sundari Retno Andani Susiani Susiani Susiani, Susiani Theresia Siburian Vikki, Zakial Wanayumini Wanto, Anjar Widodo Saputra Wildhani, Fauriza Winanjaya, Riki Yumni Syabrina Agustina Lubis Zulia Almaida Siregar