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All Journal Infotech Journal Sinkron : Jurnal dan Penelitian Teknik Informatika IT JOURNAL RESEARCH AND DEVELOPMENT INTECOMS: Journal of Information Technology and Computer Science KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Teknik dan Informatika Building of Informatics, Technology and Science Jurnal Mantik Jurnal Sains dan Teknologi Community Engagement and Emergence Journal (CEEJ) Jurnal Tekinkom (Teknik Informasi dan Komputer) Jatilima : Jurnal Multimedia Dan Teknologi Informasi Journal of Computer System and Informatics (JoSYC) INFOKUM Jurnal Darma Agung Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) International Journal Of Science, Technology & Management (IJSTM) Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) KLIK: Kajian Ilmiah Informatika dan Komputer Instal : Jurnal Komputer Jurnal Info Sains : Informatika dan Sains Bulletin of Information Technology (BIT) Jurnal Fokus Manajemen Jurnal Minfo Polgan (JMP) Jurnal Nasional Teknologi Komputer Jurnal Pengabdian Masyarakat Gemilang (JPMG) Data Sciences Indonesia (DSI) DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Best Journal of Administration and Management Jurnal INFOTEL Bulletin of Engineering Science, Technology and Industry
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APPLICATION OF K-NEAREST NEIGHBOR METHOD IN CLASSIFICING THE RATE OF PAPAYA MURABILITY BASED ON FRUIT COLOR FORM Danu Wardhana Azhari; Zulham Sitorus; Zulfahmi Zulfahmi
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (263.132 KB)

Abstract

Papaya is a type of nutrient-rich fruit that offers many health benefits. The highest nutritional content in papaya is vitamin A. Papaya is also a climbing fruit that is usually harvested and distributed. In an immature state with different degrees of aging. The high public awareness of the importance of consumption of papaya fruit affects the increase in demand for papaya fruit and therefore supply. The K-NN algorithm produces an accuracy rate of 75% and error 25% with 3 attributes, 3 classes and 18 data for classifying. The results of the model carried out are quite good by looking at the resulting accuracy value, although it is not 100% perfect. The author hopes that further research will apply the same parameters to avoid missing values in pre-processing data. It is hoped that further research will be developed by applying this classification model with other and larger data
BUS TICKET PREDICTION DURING THE COVID PANDEMIC USING BACKPROPOGATION Mhd Arie Akbar; Zulham Sitorus; Zulfahmi Syahputera
INFOKUM Vol. 10 No. 03 (2022): August, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (391.953 KB)

Abstract

Buses are the most popular land transportation during the pandemic by the community, because using buses can save time compared to using sea transportation. Transportation using land routes in modern times is considered to be the most effective means. The bus ticket price itself is quite volatile, sometimes very expensive and sometimes very cheap because it depends on the price indicators that go up and down. The purpose of this research is to design a system that can predict the price of airline tickets early by using pattern recognition technology with Backpropagation by utilizing matlab software. In the prediction system there are only six input variables, so the researcher suggests that further research is expected to have more detailed input variables to be used as test data and target data because there may still be many indicators that cause bus prices to fluctuate. After knowing the indicators of rising and falling ticket prices, the next ticket must be done first. Initially, the indicators will be tested and tested to find out using the backropogation method. The results of flight ticket price predictions using an architectural network show that the proportion of similarity of each difference is able to improve the weighting of the hidden layer with the output of UP ticket prices. the indicators will be tested and tested to find out using the backropogation method. The results of flight ticket price predictions using an architectural network show that the proportion of similarity of each difference is able to improve the weighting of the hidden layer with the output of UP ticket prices. the indicators will be tested and tested to find out using the backropogation method. The results of flight ticket price predictions using an architectural network show that the proportion of similarity of each difference is able to improve the weighting of the hidden layer with the output of UP ticket price
COMPARISONAL ANALYSIS OF EUCLIDEAN, CANBERRA, AND CHEBECHEV DISTANCE MODELS ON KNN METHOD ON STUDENTS' VALUE Ragil Satya Adi W; Eko Hariyanto; Zulham Sitorus
INFOKUM Vol. 10 No. 03 (2022): August, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (161.557 KB)

Abstract

KNN has a significant influence on nonparametric methods in the form of classification, but the level of performance generally depends on the equilibrium point of the variable that is correlated with the far point. The distance between readings from the specified limit of the standard deviation value. KNN method. One of the instance-based learning groups is the K-Nearest Neighbor (KNN) method. Group search performed by KNN on new data objects or k objects in the test that is closest to the test data. KNN helps classify objects based on training data that is close to the object being tested. This study concluded that the Canberra Distance model produced the highest accuracy of 87.50% with an error value of 12.50% on the K-Nearest Neighbor algorithm.
FORECASTING MATERIAL INVENTORY OF PT INALUM (PERSERO) CARBON DEPARTMENT USING SINGLE EXPONENTIAL SMOOTHING METHOD WEB-BASED Aldi Kesuma; Zulham Sitorus; Wirda Fitriani
INFOKUM Vol. 10 No. 03 (2022): August, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (643.009 KB)

Abstract

An error occurred in recording material inventory, resulting in disruption of the aluminum production process at PT Inalum (Persero). In addition, orders that are not on time can also cause losses to PT Inalum (Persero), because the accumulation of too much material inventory will require a lot of working capital, this allows capital investment for other activities to be hampered, while the limited material inventory allows PT. Inalum (Persero) cannot meet the needs of its customers. The purpose of this study is to determine the amount of material inventory that must be provided by the Carbon Department of PT Inalum (Persero) in the next period. The method used in this study is Single Exponential Smoothing (SES) with the calculation of the error size, namely Mean Absolute Deviation (MAD), Mean Square Error (MSE), and Mean Absolute Perentage Error (MAPE. The results of this study indicate that the calculation of each material uses alpha 0.1 because the lowest percentage of MAPE values is at alpha 0.1 Material Petroleum Coke Low Sulfur has a MAPE percentage of 21.08%, Petroleum Coke High Sulfur has a MAPE percentage of 21.37%, and Diesel has a MAPE percentage namely 17.44%. s Department of Carbon (Persero) using the Single Exponential Smoothing method, it is known that the results of these calculations are the same
ANALISA METODE NAÏVE BAYES DENGAN GAIN RATIO PADA DATA IDENTIFIKASI KACA Alvian Alvian; Zulham Sitorus; Arpan Arpan
Jurnal Darma Agung Vol 30 No 1 (2022): APRIL
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Darma Agung (LPPM_UDA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46930/ojsuda.v30i1.2225

Abstract

Pengujian yang telah dilakukan pada semua data menunjukkan bahwa model klasifikasi Gain Ratio dapat memberikan nilai akurasi yang lebih baik karena terdapat perubahan bobot nilai atribut pada dataset yang digunakan. Nilai weighted Gain ratio digunakan untuk menghitung probabilitas pada Nave Bayes, yang merupakan parameter untuk melihat hubungan antar setiap atribut dalam data, dan digunakan sebagai dasar pembobotan setiap atribut dari dataset. Semakin tinggi rasio Gain suatu atribut, semakin besar hubungannya dengan kelas data. Sehingga nilai akurasinya meningkat dibandingkan dengan nilai akurasi yang dihasilkan oleh model klasifikasi Naïve Bayes. Peningkatan akurasi pada model klasifikasi Naïve Bayes disebabkan oleh banyaknya akurasi bobot dari pemilihan atribut pada Gain ratio.
Implementasi Machine Learning Pada Sistem Pemetaan Daerah Rawan Banjir Di Desa Pahlawan Kabupaten Batu Bara Zulham Sitorus; Eko Hariyanto; Fahmi Kurniawan
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 3 No. 3 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v3i3.560

Abstract

One of the areas in Batu Bara Regency, Pahlawan Village, Tanjung Tiram District, has an area of ??173.79 km² and is located in a lowland area with an altitude of 0.-4.5m which is directly adjacent to the Malacca Strait to the east. Where almost half of the area is affected by sea tides, Hero Village has a tropical climate with two seasons namely the rainy season and the dry season. The people who live in Pahlawan Village, Tanjung Tiram District. There are so many obstacles faced by the people of Pahlawan Village, including the problem of flooding which has an impact on the health and the economy of the community. Lack of counseling and knowledge, as well as public awareness of the occurrence of flooding during high tides, and when the rainy season will increase the water discharge at sea level will rise so that it can cause flooding. In this study, the implementation of machine learning was used as a mapping system for flood-prone areas in Pahlawan Village, Batu Bara District, with data analysis used using primary and secondary data, both qualitative and quantitative. Due to the occurrence of floods, and the impact of losses that affect material and non-material, it is very important to map flood-prone areas for regional development planning. Identification of potential flooding involves machine learning using the Random Forest method, taking into account the triggering factors for flooding. The Random Forest method also provides sensitivity parameters using a Receiver Operating Characteristic (ROC) curve which indicates areas prone to flooding, for example, Pahlawan Village, Tanjung Tiram District
Rancang Bangun Pendataan Stok Barang Operasional Dengan Metode Iconix Process Di HRP Foto Copy Berbasis Web Wahyu Agung Pratama; Zulham Sitorus
Bulletin of Information Technology (BIT) Vol 4 No 1: Maret 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i1.518

Abstract

HRP Fotocopy is a business engaged in the sale of stationery and printing goods. However, along with the development of business and the world of technology, the sales and purchasing processes are increasing, while the processes carried out by the HRP are still carried out manually, resulting in a buildup of files and longer services. The development of the times is followed by the role of computer technology which is increasingly rapidly making business competition more stringent, thus HRP Foto Copy builds a stock information system application using the Software Development Life Cycle (SDLC) concept. One of the SDLC frameworks is Use Case Driven Object Modeling with UML or what is commonly called the ICONIX process. Utilization of information technology with the Iconix Process method greatly assists business parties in developing systems according to needs with the Iconix Process concept which completes the stages up to the evaluation stage
IMPLEMENTATION OF TEACHER AND STAFF ABSENCE SYSTEM AT ANDROID-BASED SCHOOLS Fahmi Kurniawan; Zulham Sitorus
INFOKUM Vol. 10 No. 5 (2022): December, Computer and Communication
Publisher : Sean Institute

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Abstract

Attendance is part of an important role in every institution, especially in educational institutions. Where attendance is one of the main supports to support and motivate every activity in it. As is the case with the PAB 5 Kelambir Lima Vocational School, which is currently still using the manual method, namely by handwriting. This method is very vulnerable for an educational institution because the level of discipline cannot be controlled and can be misused by irresponsible people. For this reason, it is necessary to have a digitization-based attendance system that utilizes an Android smartphone. With the existence of a digitization-based attendance system, it can provide performance achievements at the school. The system that will be built later is that every employee and teacher, if they want to be absent, must use a smartphone by sending a photo and being absent 100 meters from the workplace. Then the principal will check the attendance of teachers and employees every month.
Data Mining Menggunakan Algoritma Apriori Dalam Menentukan Tarif Pajak Penghasilan Di Oenity Hafiz Rodhiy; Zulham Sitorus
Bulletin of Information Technology (BIT) Vol 4 No 2: Juni 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i2.673

Abstract

Thel Oelnity tax consulting officel is onel of thel companiels that havel a lot of data on goods, data-data, and transaction data elvelry day. In gelnelral, thel Oelnity tax consulting officel only usels this data for relporting purposels only. Tax transaction data collelcteld and storeld can providel uselful knowleldgel for company managelmelnt in carrying out elfforts rellateld to tax increlasels, for elxamplel in telrms of deltelrmining tax financel stratelgiels and supporting delcisions for thel company. Consumelrs who apply for thel procelss of deltelrmining incomel tax ratels usually havel relasons why thely choosel a tax data calculation systelm from a tax consultant rathelr than managing it thelmsellvels. Belcausel tax consultants can providel what thely want, such as convelnielncel, accuracy, speleld, and nelatnelss of incomel tax calculations. Many consumelrs complain about thel incomel tax ratel calculation systelm, whelrel thel layout, making it difficult for consumelrs to gelt thel final tax relsults thely neleld, will also spelnd quitel a long timel just to find thel total incomel tax ratel. Thel Apriori algorithm is onel of thel most frelquelntly useld typels of data analysis in thel world of data procelssing. This analysis procelss is to analyzel thel numbelr of businelssels and thel amount of consumelr incomel by finding associations beltweleln lists of taxels that must bel paid. Thel Apriori algorithm is useld to arrangel itelm layouts and group itelms. From thel relsults of systelm implelmelntation, it was concludeld that using thel Apriori Algorithm melthod can hellp thel procelss of finding incomel tax ratels for elach consumelr data.
Perancangan Aplikasi Inventaris Barang Milik Daerah Pada Dinas Komunikasi Dan Informatika Kota Medan Berbasis Web Larius Ambasador Parlindungan; Zulham Sitorus; Eko Hariyanto
INTECOMS: Journal of Information Technology and Computer Science Vol 6 No 2 (2023): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/intecoms.v6i2.7268

Abstract

Penelitian ini bertujuan untuk merancang sebuah aplikasi inventaris barang milik daerah berbasis web untuk Dinas Komunikasi dan Informasi Kota Medan. Tujuan utama aplikasi ini adalah meningkatkan efisiensi dalam pengelolaan inventaris barang, memberikan informasi yang akurat dan terkini, serta memudahkan akses dan kontrol terhadap data inventaris. Melalui pendekatan metodologi pengembangan perangkat lunak, seperti SDLC (Sistem Pengembangan Siklus Hidup), langkah-langkah terstruktur dan berurutan diterapkan untuk menghasilkan aplikasi yang terkontrol dan sesuai dengan kebutuhan pengguna. Hasil dari penelitian ini mencakup perancangan basis data yang menggambarkan relasi antara berbagai tabel untuk menyimpan informasi inventaris barang. Arsitektur aplikasi menggunakan web server Apache, dan implementasi tampilan program meliputi halaman-halaman seperti login, dashboard, serta halaman kelola data master dan kelola data master barang. Aplikasi ini memberikan pandangan yang lebih baik tentang inventaris, mempermudah pengelolaan data master, dan memungkinkan pengelolaan inventaris dengan lebih terarah dan efisien
Co-Authors , Arpan , Fery Anugerah A.A. Ketut Agung Cahyawan W Abdul Karim Afrizal, Sandi Akbar Maulana, Taufik Aldi Kesuma Alvian Alvian Ami Abdul Jabar Andi Ernawati Andysah Putera Utama Siahaan Angkat, Chairul Indra Antoni, Robin Ardya, Dwika Arief, Muhammad Arif Rahman Asyahri Hadi Nasyuha Aulia, Ananda Ayu Ofta Bambang Sugito Batubara, Supina Boy Rizki Akbar Br Tarigan, Sella Monika Chelfina Utami Daniel Happy Putra Danu Wardhana Azhari Darmeli Nasution DEWI SARTIKA diansyah, Suhar Eko Hariyanto Eko Hariyanto Eko Hariyanto Fahmi Iskandar Fahmi Kurniawan Farta wijaya, Rian Faza Wardanu Damanik, Dwi Gilang Ramadhan Gultom, Ananda Christianto H. Aly, Moustafa Hafiz Rodhiy Haliza, Siti Nur Hamzah, Iswadi Hartono Sinambela, Sugi Helmy, Ahmad Hendra Harnanda Heni Wulandari Hrp, Abdul Chaidir Ibezato Zalukhu, Anzas Ika Devi Perwitasari Indra Angkat, Chairul IQBAL , MUHAMMAD Irwan Syahputra Irwan Syahputra, Irwan Izhari, Fahmi Khairul Khairul Khairul, Khairul Kiki Artika Kurniawan, Fahmi Laila Maghfirah Larius Ambasador Parlindungan Leni Marlina Leni Marlina Limbong, Yohannes France M Imam Santoso M. Rasyid M.Rizki Khadafi Mardiah, Nia Marzuki Sianturi, Ismail Melva Sari Panjaitan Meri Sri Wahyuni Mhd Arie Akbar Mohammad Yusuf, Mohammad Muhammad Fahriza Muhammad Iqbal Muhammad Iqbal Muhammad Wahyudi Nahampun, Natalia Nainggolan, Andreas Ghanneson Nasution, Darmeli Nazar Saputra, Risfan Nelviony Parhusip Nurwijayanti Ofta Sari, Ayu Parhusip, Nelviony Pranoto, Sugeng Putra, Khairil Ragil Satya Adi W Ramadani, Pebri Ramadhan, Aditya Ramadhan, Deni Ramadhani, Aditya Rian Farta Wijaya Rian Putra, Randi Rika Uli Samosir, Siska Risky, Raihan Rusydi Tanjung , Miftah Sahputra, Fajar Said Oktaviandi Saputra, Maulian Sari Penjaitan, Melva Septiani, Nadya Sianturi, Ismail Sibarani, Dina Marsauli Simamora, Siska Simbolon, Fikri Zuhaili Simorangkir, Elsya Sabrina Asmita Sinambela, Sugi Hartono Sinyo Andika Nasution, Ahmad Sipra Barutu Siregar, Andree Risky Yuliansyah Sitepu, Fernando Sitinur, Siti Nurhaliza Sofyan Sitompul, Jelly Rolley Sofyan, Siti Nurhaliza Solly Ariza Lubis Sri Wahyuni, Meri Suhardiansyah Suhardiansyah Suhardiansyah Suherman Suherman Sukrianto, Sukrianto Sutiono, Sulis Syahputri, Maulisa Syamsiar, Syamsiar T, Siti Isna Syahri Tanjung, Miftah Rusydi Utama, Hendra Vina Arnita Vivin Yulfia Sarah Wahyu Agung Pratama Wahyuni, Meri Sri Wijaya, Rian Farta Winnugroho Wiratman, Manfaluthy Hakim, Tiara Aninditha, Aru W. Sudoyo, Joedo Prihartono Wirda Fitriani Yahya, Susilawati Zalukhu, Anzas Ibezato Zulfahmi Syahputera Zulfahmi Zulfahmi Zulfahmi Zulfahmi