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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) 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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Pengelompokan Algoritma K-Means dan K-Medoid Berdasarkan Lokasi Daerah Rawan Bencana di Indonesia dengan Optimasi Elbow, DBI, dan Silhouette Hartama, Dedy; Wanayumini, W; Damanik, Irfan Sudahri
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5851

Abstract

The study examines the use of K-Means and K-Medoids algorithms in the grouping of disaster area locations in Indonesia, with the aim of identifying patterns and optimizing disaster re-sponse strategies. The data used includes geographical and historical information of various disaster events in Indonesia, such as Aceh Besar, Asahan, Badung, Bangkalan, Bekasi, and others. In the clustering process, optimization techniques such as the Elbow Method, the Da-vies-Bouldin Index (DBI), and the Silhouette Score are used to determine the optimal number of clusters. Research results show that the K-Means algorithm tends to be more stable in deal-ing with outliers than K- Means, with the results of the DBI (Davis-Booldin Index) 0.3737248981 and the cluster 7, resulting in the silhouette score of 0.868728638 and cluster 2, resulting at the elbow 98106477130.371 and claster 2. The Silhouette Score and Elbow index-es also provide a strong indication that the clustering algorithm used is capable of forming significant and meaningful clusters. The study has made important contributions to the opti-mization of clustering with three methods used so that it can be the basis for authorities in planning and implementing more effective disaster mitigation policies.
An Implementation of Hybrid CNN-XGBoost Method for Leukemia Detection Problem Hidayat, Taufiq; Hadinata, Edrian; Damanik, Irfan Sudahri; Vikki, Zakial; Irvanizam, Irvanizam
Infolitika Journal of Data Science Vol. 1 No. 1 (2023): September 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijds.v1i1.87

Abstract

Leukemia is a blood cancer in which blood cells become malignant and uncontrolled. It can cause damage to the function of the body's organs. Several machine learning methods have been used to automatically detect biomedical images, including blood cell images. In this study, we utilized a hybrid machine learning method, called a hybrid Convolutional Neural Network-eXtreme Gradient Boosting (CNN-XGBoost) method to detect leukemia in blood cells. The hybrid method combines two machine learning methods. We use CNN as the basic classifier and XGBoost as the main classification method. The aim of this methodology was to assess whether incorporating the basic classification method would lead to an enhancement in the performance of the main classification model. The experimental findings demonstrated that the utilization of XGBoost as the main classifier led to a marginal increase in accuracy, elevating it from 85.32% to 85.43% compared to the basic CNN classification. This research highlights the potential of hybrid machine learning approaches in biomedical image analysis and their role in advancing the early diagnosis of leukemia and potentially other medical conditions.
The Cumulative Capacitated Vehicle Routing Problem with Time-dependent on Humanitarian Logistics for Disaster Management Hartama, Dedy; Wanayumini, Wanayumini; Damanik, Irfan Sudahri
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.481

Abstract

This study addresses the challenges of optimizing humanitarian logistics during disaster management by developing a Cumulative Capacitated Vehicle Routing Problem with Time-Dependent factors (CCVRP-TD) model. The primary objective is to enhance delivery efficiency by incorporating time-dependent variables such as fluctuating traffic and service durations into route planning. The research contributes a novel Mixed Integer Nonlinear Programming (MINLP) framework that dynamically adapts to real-world conditions like road closures and shifting priorities. Using the MINLP approach, the model was validated through numerical experiments involving four delivery vehicles serving six customers across five routes. Results demonstrated a significant improvement in routing efficiency, with a total cumulative travel distance of 110 km and adherence to specified delivery windows, such as 9:30 AM and 10:30 AM for Customer 1. Additionally, vehicle capacity constraints were effectively managed, with individual route lengths ranging from 20 to 35 km. These findings showcase the model’s ability to balance cost minimization, service reliability, and logistical adaptability. The novelty lies in the integration of time-dependent costs and service benefits into a multi-depot framework, enabling flexible yet precise route optimization under constrained conditions. This research provides a robust tool for enhancing disaster logistics and offers practical implications for improving the responsiveness and effectiveness of humanitarian aid delivery.
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.
Implementasi Metode Apriori Dalam Pembagian Kejuruan Penerimaan Siswa Baru Di SMK Negeri 1 Siantar Saragih, Ria Annisa; Damanik, Irfan Sudahri; Saragih, Ilham Syahputra
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 6, No 1 (2021): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v6i1.282

Abstract

The purpose of this research is to determine the vocational division of the acceptance of new students that will be taken by the author with data mining techniques using a priori algorithm method. The data source used is to make observations. Match predictions can be obtained based on the results of comparisons with other students who have similarity data with student A. By using a priori algorithm obtained results that involve a collection of items that often with a high value of trust. The results of this study are data that group prospective new students based on their desired majors with a minimum support of 50% and a minimum trust of 50%, making 20 rules that are set aside. One of the rules that is formed is if the student chooses a fashion major (A4) then the department that is more suitable for students is hair and skin (A2) with a support value of 0.5 or equal to 50 and trust 100 to 0.5 or equal to 50 It is hoped that this information can provide advice to the public vocational school 1 Siantar.
Analisis Kepuasan Masyarakat Terhadap Kualitas Pelayanan Pada Pengadilan Negeri Simalungun Menggunakan Metode Algoritma C4.5 Rahayu, Sri; Damanik, Irfan Sudahri; Fauzan, M
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 6, No 1 (2021): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v6i1.273

Abstract

This study aims to analyze the level of community satisfaction with services in the District Court Simalungun using the C4.5 Algorithm method. The data source used in this study was taken with an instrument in the form of a questionnaire with closed and open answers, where the data is in the form of numbers and analyzed static descriptive. The study population was all service users in the District Court Simalungun, including Procedures, Service Time, Costs/ Tariffs, Implementing Behavior, etc. After doing the calculations manually, the verification is also done using the application, namely RapidMiner. From the analysis process, it can be seen that the responsive aspect is the most dominant aspect in determining the level of community satisfaction at the District Court Simalungun
Implementasi Algoritma K-Medoids untuk Pengelompokkan Sebaran Mahasiswa Baru Irawan, Eka; Siregar, Sandy Putra; Damanik, Irfan Sudahri; Saragih, Ilham Syaputra
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 5, No 2 (2020): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v5i2.213

Abstract

The existence of new students at a tertiary institution is a routine activity every year in a tertiary institution and can also see the sustainability of the tertiary institution. The variety of regional origin of new students makes the party from the university want to see the distribution of new students based on the origin of the school and its place of residence. STIKOM Tunas Bangsa is one of the tertiary institutions in Pematangsiantar. It aims to promote the university. K-Medoids is able to group data on the distribution of new students in STIKOM Tunas Bangsa Pematangsiantar. The clusters produced in this study are of three clusters. The validity used in this study is the validity of Silhoutte Coefficient. The validity value generated in the K-Medoids algorithm produces a validity value of -116.47 by assuming that if the non-medoids value produced S
Algoritma Promethee II Dalam Seleksi Anggota Paskibra Baru Pada SMA Negeri 4 Pematangsiantar Guntur, Azi; Damanik, Irfan Sudahri; Fauzan, M
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 6, No 1 (2021): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v6i1.283

Abstract

This study aims to conduct selection in determining the members of the New Paskibra in Pematangsiantar Public High School 4 engaged in the field of Education. Besides being based on ability, the addition of several variables and assessment indicators in the form of health variables, height, whether there is togetherness, organizational participation and so on are expected to be able to provide a clearer picture of the criteria of new Paskibra Members in Pematangsiantar 4 Public High School, especially in the best Paskibra Member data which is ambiguous. In this thesis the Promethee II method is a method implemented for determining the criteria for new post-members members and is one of the multi-criteria decision-making methods based on the concept of outranking using pairwise comparisons of alternatives based on each appropriate criterion
Analisis Kenaikan Jabatan Pegawai dengan Metode Promethee pada Kantor Kejaksaan Negeri Pematangsiantar Suhada, Muhammad Ifnu; Damanik, Irfan Sudahri; Saragih, Ilham Syahputra
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 6, No 1 (2021): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v6i1.274

Abstract

Pematangsiantar District Attorney's Office is a government agency that is engaged in the management of law and human rights. Employees are very important resources to determine the success of a work unit. Efforts to improve the quality of performance of a civil servant is a promotion. Position is a position that indicates the level of a person of the State Civil Apparatus. Promotion is an award given for work performance and service of the State Civil Apparatus. Decision Support System (SPK) which can help make it easier to determine an employee can be said to be eligible for promotion. In this study the decision-making calculation method used is Promethee with 5 criteria namely rank, Education, Discipline, Position History, Test Results. The system was built using the PHP programming language. The test results using the Questionnaire Testing show that the system can function according to the needs of users and the system is declared to have fulfilled the criteria for structural promotion of Employees at Pematangsiantar District Attorney's Office.
Menentukan Kelayakan Pelayanan Service Advisor Pada PT. Sutan Indo Aneka Mobil Pematangsiantar dengan Metode Weighted Sum Model Siahaan, Mian Manimpan; Damanik, Irfan Sudahri; Saragih, Ilham Syahputra
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 6, No 1 (2021): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v6i1.284

Abstract

Service becomes one of the important things in the form of business activities engaged in services. Worthiness in providing the best service must be through a good judgment. There are company indicators in assessing the feasibility of service advisor at PT. Sutan Indo Aneka Mobil Pematangsiantar. This requires a method to be able to assist the company in making decisions (MCDM). Weighted Sum Model (WSM) method is the best solution to help companies in determining the feasibility of service with many criteria
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 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 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 Taufiq Hidayat Theresia Siburian Vikki, Zakial Wanayumini Wanto, Anjar Widodo Saputra Winanjaya, Riki Yumni Syabrina Agustina Lubis Zulia Almaida Siregar