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All Journal TEKNIK INFORMATIKA Jurnal Sains dan Teknologi Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat JITK (Jurnal Ilmu Pengetahuan dan Komputer) Martabe : Jurnal Pengabdian Kepada Masyarakat KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) JURIKOM (Jurnal Riset Komputer) JURTEKSI Building of Informatics, Technology and Science JATI (Jurnal Mahasiswa Teknik Informatika) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Computer Science and Information Technologies TIN: TERAPAN INFORMATIKA NUSANTARA Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Journal of Applied Data Sciences BEES: Bulletin of Electrical and Electronics Engineering JOMLAI: Journal of Machine Learning and Artificial Intelligence Journal of Informatics, Electrical and Electronics Engineering Dike Jurnal Indonesia : Manajemen Informatika dan Komunikasi Bulletin of Information System Research
Hartama, Dedy
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Analisa Metode Profile Matching Pada Pemilihan Susu Rendah Lemak Berdasarkan Konsumen Sari, Hanifah Urbach; Windarto, Agus Perdana; Winanjaya, Riki; Hartama, Dedy; Damanik, Irfan Sudahri
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 4, No 1 (2020): The Liberty of Thinking and Innovation
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v4i1.2590

Abstract

Milk is a source of nutrition for humans, especially in infants who cannot digest food. Milk has a high calcium content and can strengthen human bones. This study aims to recommend low-fat milk as a recommendation to consumers to determine the right milk product. Data collection methods used were interview techniques and questionnaire random sampling to 60 respondents who used low-fat milk at STIKOM Tunas BangsaPematangsiantar. Based on the results of interviews and questionnaires, the assessment criteria were obtained, namely price (K1), side effects (K2), packaging (K3), and availability of goods (K4). The alternatives used in the study were Ultra Milk Low Fat (S1), Bear Brand Gold (S2), Frisian Flag (S3) and Hilo Teen (S4). The settlement method applied is POFILE MATCHING. The results of the algorithm show that the right alternative is for the highest ranking Hilo Teen (S4) with a final score of 88.95 and followed by Ultra Milk Low Fat (S1) with a final score of 86.325. The results of the study are expected to provide recommendations to consumers to determine the right low-fat milk.Keywords: Milk, Nutrition, Profile Matching, Decision Suport System, Product Selection
Implementasi Jaringan Syaraf Tiruan (JST) Untuk Memprediksi Jumlah Penjualan Gas 3Kg Menggunakan Metode Backpropagation B. Tambunan, Holpan Torang; Hartama, Dedy; Gunawan, Indra
TIN: Terapan Informatika Nusantara Vol 1 No 9 (2021): Februari 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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

Abstract

In a service company, there are customers who become company consumers. Customer satisfaction is formed from the level of performance and service of the company. One level of customer satisfaction can be measured from the level of gas sales of 3 Kg. Therefore, the 3 kg LPG gas pankalan Pematangsiantar needs to overcome the problem of overcoming the amount of 3 kg gas sales at each LPG base in order to improve their performance and service. So research is needed to predict the amount of gas sales of 3 Kg through the Neural Network method with the backpropagation algorithm to find the best results that will be used to solve the problems faced.
REKOMENDASI PENJUALAN AKSESORIS HANDPHONE MENGGUNAKAN METODE ANALITYCAL HIERARCHY PROCESS (AHP) Widyasuti, Meilin; Wanto, Anjar; Hartama, Dedy; Purwanto, Eko
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 1, No 1 (2017): Intelligence of Cognitive Think and Ability in Virtual Reality
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v1i1.468

Abstract

Talk about the lifestyle that is now growing, it also affects the appearance of mobile phones that are owned by everyone that is more complete mobile accessories and create attractive appearance. Along with the time mobile phone accessories business is also experiencing a fairly rapid development, not even just a store product that sells mobile phone accessories but also has sold the counter. Here the researchers want to examine the recommendation of mobile accessories, where the selected accessories are the accessories of the most popular consumers based on store ratings. The rise of accessories business is proving that the mobile phone accessories still deserve to be a good opportunity. Some telemonication experts predict that mobile users are increasing the number of populations. This can be an accessory business that has good prospects in the future. Based on the results of research using AHP method with 6 samples of best selling mobile accessories, where the data obtained based on the results of interviews with mobile shops in the city Pematangsiantar, obtained the calculation of AHP method for handpone accessories recommendation is 1. Led Selfie (34%), 2. Gopro (25%), 3. Phone Ring (20%), 4. Scean Guard (16%), 5. Charge Wireless (14%) and 6. Handset (10%)
PENERAPAN KLASIFIKASI C4.5 DALAM MENINGKATKAN SISTEM PEMBELAJARAN MAHASISWA P, Dini Rizky Sitorus; Windarto, Agus Perdana; Hartama, Dedy; Damanik, Irfan Sudahri
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 3, No 1 (2019): Smart Device, Mobile Computing, and Big Data Analysis
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v3i1.1665

Abstract

The purpose of this research is to classify the improvement of student learning systems using the C4.5 datamining method. The source of the research data was obtained from the education section of STKOM Tunas Bangsa through interviews and questionnaires to semester 5 students (160 students) in the 2019-2020 academic year study program. The attributes used in the classification of student learning systems include: Teaching System (C1), Teaching Aids (C2), Environment (C3), Infrastructure Facilities (C4) and Assignment (C5). The calculation results mention the attribute Assignment (C5) is the attribute that most influences the improvement of student learning systems. The test was also carried out using the help of Rapidminer software and obtained an accuracy of 95%.Keywords: Datamining, Classification, C4.5, Student Learning, STIKOM Tunas Bangsa
Prediksi Perkembangan Jumlah Pelanggan Listrik Menurut Pelanggan Area Menggunakan Algoritma Backpropagation Saragih, Irfan Christian; Hartama, Dedy; Wanto, Anjar
JURIKOM (Jurnal Riset Komputer) Vol 7, No 4 (2020): Agustus 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v7i4.2291

Abstract

Electricity is one of the vital needs of humanity. Without electricity, it is certain that the wheels of the economy will not be able to run properly. So that electricity customers are increasingly increasing, as they increase the needs and population of the community. Therefore this study aims to determine the development of the number of electricity customers using the backpropagation algorithm. The research data used was electricity customer data by area (customer) in North Sumatra in 2013-2017, obtained from the Central Statistics Agency of North Sumatra. This study uses 5 architectural models, namely 4-2-1, 4-3-1, 4-4-1, 4-5-1, and 4-6-1. Of the five architectural models used, one of the best architectural models is obtained 4-4-1 with an accuracy rate of 88%, epoch 716 iterations in a short amount of time, 15 seconds, with MSE Training 0,00099763 and MSE testing 0.00109935. Based on the best architectural model, this will be used to predict the Development of Electricity Customers by Area Customers in North Sumatra from 2018 to 2020
Monitoring Keamanan Toko Menggunakan Sensor Pir dan Pintu Berbasis Arduino dengan Notifikasi SMS Gateway Putra, Jaka; Sumarno, Sumarno; Damanik, Bahrudi Efendi; Hartama, Dedy; Gunawan, Indra
Building of Informatics, Technology and Science (BITS) Vol 1 No 2 (2019): December 2019
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (364.045 KB) | DOI: 10.47065/bits.v1i2.49

Abstract

The author has conducted research at UD Stores. Variant Jl. Kabu-Kabu No. 31 Pematangsiantar and found a problem where the theft was prone to the place and no employees guarded the store during the closing. Then another problem arises how to monitor stores from a distance by using SMS Gateway notifications. So here the author provides a solution so that the store can be monitored remotely with SMS Gateway Notifications. The author implements a Magnetic switch on the front door so that when the door is forced open the buzzer will ring and the owner receives an SMS, then in the front room the writer implements a PIR sensor where when a human passes the sensor the buzzer will turn on and the shop owner will get SMS notification.
Prediksi Perkembangan Jumlah Pelanggan Listrik Menurut Pelanggan Area Menggunakan Algoritma Backpropagation Saragih, Irfan Christian; Hartama, Dedy; Wanto, Anjar
Building of Informatics, Technology and Science (BITS) Vol 2 No 1 (2020): June 2020
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (364.497 KB) | DOI: 10.47065/bits.v2i1.341

Abstract

Electricity is one of the vital needs of humanity. Without electricity, it is certain that the wheels of the economy will not be able to run properly. So that electricity customers are increasingly increasing, as they increase the needs and population of the community. Therefore this study aims to determine the development of the number of electricity customers using the backpropagation algorithm. The research data used was electricity customer data by area (customer) in North Sumatra in 2013-2017, obtained from the Central Statistics Agency of North Sumatra. This study uses 5 architectural models, namely 4-2-1, 4-3-1, 4-4-1, 4-5-1, and 4-6-1. Of the five architectural models used, one of the best architectural models is obtained 4-4-1 with an accuracy rate of 88%, epoch 716 iterations in a short amount of time, 15 seconds, with MSE Training 0,00099763 and MSE testing 0.00109935. Based on the best architectural model, this will be used to predict the Development of Electricity Customers by Area Customers in North Sumatra from 2018 to 2020
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.
Analisa Visualisasi Data Covid – 19 Di Indonesia Menggunakan Tableau Big Data Pangestu, Prayoga; Hartama, Dedy; Suhendro, Dedi; Damanik, Abdi Rahim; Oktaviani, Selli
BEES: Bulletin of Electrical and Electronics Engineering Vol 4 No 2 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bees.v4i2.4634

Abstract

This study explains the benefits of data analysis by visualization of Big data inoptimizing cases of the spread of COVID-19 in Indonesia. The data used is the COVID-19 Indonesia time series data from the Kaggle website. In this study, the author used tableau tools to analyze data based on worksheets of covid-19 distribution maps, COVID-19 statistics, details of active cases per province, death cases per province, active cases, death cases, confirmed cases and produced a dashboard of COVID-19 data. The results of the analysis obtained using visualizations in the form of graphs are very fast and optimize data processing so that they can find out which provinces are affected by active cases and deaths of COVID-19 from the highest to the lowest in Indonesia and can be used in decision and policy making for the Indonesian government.
Decision Support System in Determining the Level of Success of Teaching Teachers Using the AHP Method Abdillah, Mhd Khoiri; Hartama, Dedy; Nasution, Rizki Alfadillah
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 2 (2023): June
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i2.2399

Abstract

This study aims to implement a Decision Support System (SPK) that uses the Analytic Hierarchy Process (AHP) method in assessing and determining the level of success of teachers teaching at SMA Taman Siswa, Bah Jambi Branch. This study uses five assessment criteria, namely the number of attendance, lesson plans, teaching period, learning media, and discipline, as a basis for evaluating teacher performance. In this study, the AHP method was used to calculate the relative weight of each criterion and sub-criteria involved in assessing teacher performance. The data collected from various teachers was evaluated using the AHP method, and the results provide an overview of the level of success of each teacher in carrying out the teaching and learning process. The results showed that among the many existing teachers, Siti Palastri managed to score 0.81002, indicating good performance in the teaching and learning process. The application of this system is expected to assist schools in making decisions regarding teacher performance evaluation in a more objective and structured manner. In addition, this system can provide guidance and recommendations that are more effective in identifying areas for improvement by teachers who have not achieved the expected level of success. Thus, improving the quality of teaching can be achieved through corrective measures that are right on target.
Co-Authors , Rahmad Sembiring Abdillah, Mhd Khoiri Abdullah Ahmad Achmad Noerkhaerin Putra Agus Perdana Windarto Akbari, Imam Amalya, Nanda Audi, Femy Ines Ayunda, Yuli Septya Azhari, Ridhan B. Tambunan, Holpan Torang Damanik, Abdi Rahim Damanik, Bahrudi Efendi Dewi, Rafiqa Eko Purwanto Fania, Fira Fitri Anggraini, Fitri Hamdani Hamdani Herman Mawengkang Indra Gunawan Irfan Sudahri Damanik Jaya Tata Hardinata Katuk, Norliza Lili Tanti, Lili MARIA BINTANG Mhd Furqan Mochamad Wahyudi Mochammad Imron Awalludin Muhammad Raqib Syahkur Muhammad Ridwan Lubis Muhammad Zarlis, Muhammad Nasution, Della Fatricia Nasution, Rizki Alfadillah Oktaviani, Selli P, Dini Rizky Sitorus Pangestu, Prayoga Parlina, Iin Poningsih Poningsih, Poningsih Poningsih, P Putra, Jaka Putri, Adelia Putri, Nurma Wadda Rafai, Muhammad Riski, Ginanti Safii Safii Safii, M. Saragih, Irfan Christian Sari, Hanifah Urbach Siahaan, Nove Viktor Boyke Siregar, Filzah Naura Solikhun Solikhun, Solikhun Suhada, S Suhendro, Dedi Sumarno . Syaputri, Vera Trianda, Dimas Wanayumini Wanto, Anjar Widodo Saputra Widyana, Silva Widyasuti, Meilin Winanjaya, Riki