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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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Journal : JOMLAI: Journal of Machine Learning and Artificial Intelligence

 1 
Application of Data Mining on Patterns of Sales of Goods in Minimarkets Using the Apriori Algorithm Siti Hadija; Eka Irawan; Irfan Sudahri Damanik; Jaya Tata Hardinata
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 4 (2022): December
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (561.502 KB) | DOI: 10.55123/jomlai.v1i4.1668

Abstract

Minimarket is a shop that sells goods for daily needs. Each minimarket generates a lot of sales data every day. Sales transaction data can only be stored without further analysis. Based on this description, research was conducted to assist minimarket managers in making it easy to solve sales pattern problems at minimarkets using the Apriori algorithm. The Apriori algorithm is an algorithm that searches for item set frequencies using the association rule technique. The final result of using data mining using the Apriori association method is proven to be able to find out the results of the analysis that appear simultaneously based on sales data at the Mawar Simp.Tangsi Balimbingan Minimarket with a minimum amount of support of 30% and 80% confidence resulting in 8 association rules that are formed.
Determining Product Suitability using Rule-Based Model with C4.5 Algorithm Chintya Carolina Situmorang; Dedy Hartama; Irfan Sudahri Damanik; Jaya Tata Hardinata
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 1 (2023): March
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i1.1923

Abstract

A hotel warehouse must have orderly, good, safe, comfortable, and usable procurement of goods. The common issue that occurs in a warehouse is damaged and unusable goods. The fluctuating production demand for goods sometimes leads to neglecting the quality of the goods in the warehouse. To determine usable goods, appropriate recommendations are needed. The C4.5 algorithm with data mining techniques is an appropriate recommendation for analyzing a large amount of data for classification. The data used in this study is the inventory data of Hotel Sapadia Pematangsiantar's warehouse. Implementing the C4.5 algorithm that produces a Decision Tree can assist the warehouse in determining which goods are still usable for hotel activities. This study resulted in the best variable from the rule model used to determine the feasibility of goods being the physical condition of the goods. The accuracy of the rule model generated from the C4.5 Algorithm modeling is 99.02% against the feasibility of goods.
Decision Support System for Giving PDAM Tirtauli Pematangsiantar Employee Bonuses Using the Weighted Product (WP) Method Mira Ariffiani; Irfan Sudahri Damanik; Zulia Almaida Siregar
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 1 (2023): March
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i1.346

Abstract

Employee Bonuses at PDAM Tirtauli Pematangsiantar are given to employees who are selected as employees of the workforce who perform their work in accordance with the profession through the selection process. The process of judgment and decision-making in selection is usually subjective when there are some recipients of employee bonuses who have not much different abilities. Applications created in this research in the form of Decision Support System Employee Bonus Employee PDAM Tirtauli Pematangsiantar Using Weighted Product Method. This application is used to assist the selection in conducting assessments of the competency of the recipients of employee bonus giving and recommendation in decision making. The assessment criteria used include other Attendance, Number of Children, Length of Work, Responsibility, and Loyalty. Weighted Product method is a method of completion by using multiplication to associate attribute values, where the value must be raised first with the attribute weights in question. The system is built using WEB and MySQL programming language for data processing. The result of the research is the application of the recipient of the employee bonus giving to facilitate the process of selecting the recipients of the employee bonus giving according to the need.
Community Temporary Direct Assistance (BLSM) Decision Support System with the Profile Matching Method Mita Ariffiani; Irfan Sudahri Damanik; Ika Okta Kirana; Primatua Sitompul
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 1 (2023): March
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i1.1033

Abstract

Community Temporary Direct Assistance (BLSM) is a Government Program. The process of assessing and making decisions in BLSM is usually subjective, especially if there are prospective BLSM recipients who have criteria that are not much different. The application made in this study is a Decision Support System for Community Temporary Direct Assistance (BLSM) in the Panguluh Nagori Gunung Bayu Office with the Profile Matching method. This application is used to assist in assessing the competence of prospective BLSM recipients and providing recommendations in decision making. The assessment criteria used include aspects of the condition of the house and economic aspects. This Profile Matching method will compare participant profiles with the ideal profile of prospective BLSM recipients. The smaller the gap, the greater the chance to pass the assessment. This system was built using the WEB programming language and MySQL as the database. It is hoped that the decision support system for receiving community temporary direct assistance (BLSM) at the Panguluh Nagori Gunung Bayu Office can assist the Village Head in determining potential beneficiaries who are entitled to be recommended for BLSM with a process of multi-criteria weighting and assessment that is faster, more accurate and more effective.
Co-Authors Abdi Rahim Damanik Achmad Noerkhaerin Putra Agus Perdana Windarto Agustinus Liberty Pasaribu Anjelita, Mawaddah Azi Arisandi Azi Guntur Chairul Fadlan Chintya Carolina Situmorang Cici Astria Dea Dwi Rizki Tampubolon 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 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 Jaya Tata Hardinata Laila Kumalasari M Fauzan M FAUZAN M Fauzan M Fauzan M. Fauzan 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 Safii, M. Sahendra Fahreza Saifullah Saifullah Sandy Putra Siregar Saputra, Widodo Saragih, Ilham Syaputra Saragih, Ria Annisa Sari, Andini Fadila Sari, Hanifah Urbach Sari, Winda Permata Sepridho, Jaka Siahaan, Mian Manimpan Sinaga, Dolli Sari 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 Winanjaya, Riki Yumni Syabrina Agustina Lubis Zulia Almaida Siregar