Article Per Year (5 Year)
p-Index From 2021 - 2026
3.018
P-Index
This Author published in this journals
All Journal InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Jurnal Mantik Penusa International Journal of Natural Science and Engineering Jurnal Sistem Informasi Kaputama (JSIK) Jusikom: Jurnal Sistem Informasi Ilmu Komputer Jurnal Sains dan Teknologi Jurnal Tekinkom (Teknik Informasi dan Komputer) INFOKUM
Saut Parsaoran Tamba
Universitas Prima Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics Physics Social Sciences

Published : 25 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 25 Documents
Search

 1   2   3 
ANALISIS METODE TREND MOMENT DALAM FORECASTING UNTUK MEMPREDIKSI JUMLAH PENJUALAN PADA RESTORAN AYAM GEPREK GOKIL Rizky Prayoga; Anita Anita; Josua Silaban; Saut Parsaoran Tamba
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 1 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i1.892

Abstract

Predictions are things that might be done so that actions taken in the future are more effective and efficient. Predictions in sales are absolutely necessary so that companies / institutions can avoid big losses. Gokil Chicken Resto is a company engaged in the culinary field. Even though it is a Resto brand, it must have a business license in the form of a CV so that it can be said to be a company. The Gokil Chicken Resto has a problem, namely in the loss of procuring raw materials to be produced in a culinary menu called Gokil Geprek Chicken. In a condition, sometimes the procurement of these materials will be left quite a lot or even run out. This causes losses in terms of cost and also consumer disappointment as well. For this reason, research is needed in the form of sales predictions so that it can help minimize losses by procuring materials that are more effective and efficient. This study uses the trend moment method in analyzing sales to produce predictive numbers. The method of precise prediction accuracy uses MAPE (Mean Absolute Percentage Error). The accuracy of the prediction accuracy obtained is 99.36%.
PENERAPAN NEURAL NETWORK LSTM DALAM MEMPREDIKSI SENTIMEN PENGGUNA TWITTER TERHADAP BITCOIN Pratama, Duta; Wijaya, Salim; Santosa, Sofian Ali; Tamba, Saut Parsaoran
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.921

Abstract

Abstract This research aims to apply the Long Short-Term Memory (LSTM) Neural Network to predict Twitter users' sentiment towards the price of Bitcoin. Bitcoin, as the leading cryptocurrency in the world, faces high price volatility influenced by external factors and market sentiment. Twitter has become a valuable source of information for market analysis, including sentiment towards Bitcoin. Several algorithms have been studied previously for predicting sentiment towards cryptocurrencies, but LSTM has shown excellent results in text analysis and sequence-based data prediction. This research utilizes LSTM to account for the temporal dependencies in Bitcoin tweet data. During testing, the implementation of Bitcoin sentiment prediction using the LSTM model achieved an accuracy level of 96%, indicating the model's capability to make accurate predictions regarding Bitcoin tweet sentiment. The results of this research can contribute to the development of Bitcoin trading strategies and a better understanding of the cryptocurrency market based on Twitter users' sentiment.
APPLICATION OF DATA MINING TO DETERMINE THE LEVEL OF FISH SALES IN PT. TRANS RETAIL WITH FP-GROWTH METHOD Tamba, Saut Parsaoran; Sitanggang, Mario; Situmorang, Bimo Christhoper; Panjaitan, Gracia Laura; Marlince Nababan
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 (470.934 KB)

Abstract

Trans Retail Indonesia is one of the shopping places in the city of Medan. Trans Retail Indonesia is engaged in providing raw materials such as selling fish. However, at Trans Retail Indonesia, sales data collection still uses a manual system, so this store has not been able to determine which type of fish has the highest level of sales. So this affects the availability of goods and results in a lack of stock in this store. So we need a data mining system with the FP-Grwoth method to analyze fish sales data so that the results of the analysis become a reference for stores in determining the supply of fish stocks. The results of the analysis carried out by researchers from the data obtained are the fish that is most in demand is the Jengka Split with a value of 90%, and if you take a split Jengka fish, you will take anchovy buntiaw with a value of 54%. If you take an anchovy, it will take a large anchovy and will take a white Peda fish with a value of 100%.
PENERAPAN METODE ANT COLONY OPTIMIZATION (ACO) DALAM MENENTUKAN JALUR ALTERNATIF SOLUSI KEMACETAN KOTA MEDAN William William; Rizky Syahputra Sitompul; Adilman Reliance Hia; Roy F. Hasudungan Malau; Saut Parsaoran Tamba; Mohammad Irfan Fahmi
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1221

Abstract

This research aims to analyze and implement the Ant Colony Optimization (ACO) method in determining alternative routes to reduce traffic congestion in Medan City. Against the background of significant congestion problems during rush hours, this research collects traffic data through surveys and observations to serve as input for the ACO algorithm. This method is inspired by the natural behavior of ants in searching for food, where ants collectively find the shortest route based on pheromone trails. Tests were carried out with variations in ACO parameters such as pheromone evaporation rate, number of ants, and iterations to analyze the effectiveness of alternative paths. The research results show that the application of this method can help reduce the burden on the road network and is proven to be able to reduce travel time by 37.5%, where the time needed from 40 minutes can be reduced to 25 minutes. The results of this research can contribute to the development of an intelligent transportation system that is adaptive to changes in traffic conditions and the needs of road users in the city of Medan.
PENERAPAN METODE REGRESI LINEAR MEMPREDIKSI TINGKAT PENJUALAN SEPEDA MOTOR HONDA PADA PT. PLATINA MULIA ABADI Palma Juanta; Saut Parsaoran Tamba; Windania Purba; Yoel Ferdinand Zai; Steven Steven; Elbert Ghozali
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.941

Abstract

This research aims to obtain predictions of Honda motorbike sales based on Honda motorbike sales data at PT. Platina Mulia Abadi is a company engaged in transportation and automotive services, especially sales of Honda motorbikes. The linear regression method is used to predict the number of sales of Honda motorbikes. The uncertainty in the number of sales of Honda motorbikes to this company has slightly hindered the company's development, because the company cannot take a definite policy regarding the sales that occur. Therefore, this company estimates future sales of Honda motorbikes for this company, so that management can estimate future consumer demand. So that the company is able to serve and provide consumer demand. To carry out estimates, the Multiple Linear Regression method is used. The results of this research obtained an estimated sales of manual motorbikes in 2023 in January of 64,003 or 64 units of Honda motorbikes in the manual category. This means that there is an increase in the number of manual Honda motorbikes by 8 motorbikes, while the results until May 2023 are 72,123 motorbikes. Through the application of this method, the estimated sales of Honda motorbikes in the next 5 months at PT. Eternal Precious Platinum can be done easily and quickly.
ANALISIS PREDIKSI PENJUALAN TOKO FURNITUR DENGAN METODE LONG SHORT-TERM MEMORY (LSTM) Gunawan, Ricky; Dimiliu, M Bairaja; Valerine, Karen; Tamba, Saut Parsaoran
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1511

Abstract

This study aims to analyze and predict furniture store sales using the Long Short-Term Memory (LSTM) method, focusing on time series datasets from 2014 to 2017. The LSTM method was chosen because of its ability to handle remote dependencies in time series data, which is relevant in understanding furniture sales patterns and trends for strategic planning. The research stages include literature study, library research, field research, data acquisition, and data preprocessing using Python and Google Colab. Exploratory analysis of the data was carried out to understand the characteristics of the dataset, followed by the development of the LSTM model, data normalization, and model evaluation with RMSE, MAE, and MAPE metrics. The evaluation results show that the LSTM model produces RMSE of 39.27%, MAE of 32.74%, and MAPE of 42.28%. Nonetheless, there is potential to improve accuracy by integrating more variables, exploring different LSTM architectures, and utilizing regularization techniques. This research is expected to contribute to improving the effectiveness of furniture sales management strategies and inspire further development in the application of ESG in business prediction.
Android-Based Learning Media for Vocational High School Students Siregar, Bina Jaya; Ndruru, Liberlina; Tamba, Saut Parsaoran
International Journal of Natural Science and Engineering Vol. 5 No. 2 (2021): July
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (371.073 KB) | DOI: 10.23887/ijnse.v5i2.37080

Abstract

Online learning impacts decreasing student interest and learning outcomes, so students need media that can help the learning process. This research aims to produce an android-based learning application for vocational students. This research is classified as developed using the ADDIE model (analysis, design, development, implementation, and evaluation). The subjects involved in this study were two media experts, one teacher, and vocational students. Data collection in the study was carried out using the interview method and distributing questionnaires with an instrument in a product validity test questionnaire. The research data was analyzed using scores from each validator by adding up each score on each indicator and finally providing a valid assessment using the percentage assessment procedure. The study results indicate that the developed learning application media has a high validity score, so developing and teaching vocational high school students. In addition to having a high validity score, the learning application media has increased students' motivation and learning outcomes.
PENERAPAN DATA MINING UNTUK MENENTUKAN PENJUALAN SPAREPART TOYOTA DENGAN METODE K-MEANS CLUSTERING: data mining;k-means-clustering Tamba, Saut Parsaoran; Kesuma, Felix Toknady; ., Feryanto
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 2 (2019): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (362.434 KB) | DOI: 10.34012/jusikom.v2i2.376

Abstract

Semakin berkembangnya persaingan dalam dunia bisnis khususnya dalam industri penjualan sparepart mobil dan jasa serivice menuntut para pengembang untuk menemukan suatu pola yang dapat meningkatkan penjualan dan pemasaran barang di perusahaan, salah satunya adalah dengan pemanfaatan data transaksi. CV Terang Jaya merupakan perusahaan yang begerak dalam bidang Otomotif yang melayani pembelian, penjualan sparepart mobil serta memberikan service untuk berbagai merek mobil. Namun demikian kurang dalam peninjauan produk-produk apa saja yang dibutuhkan konsumen dan penyimpanan data-data yang kurang efektif. Untuk mengatasi permasalahan tersebut analisis yang digunakan yaitu penerapan Clustering dengan menggunakan Algoritma K-Means. Clustering merupakan salah satu teknik dari salah satu fungsionalitas data mining, algoritma clustering merupakan algoritma pengelompokkan sejumlah data menjadi kelompok–kelompok data tertentu (cluster). Sehingga dengan adanya pengelompokan data ini pihak perusahaan dapat mengetahui barang paling laris, laris dan tidak laris. Sehingga barang yang ada digudang tidak menumpuk. Dari penitian ini output yang dihasilakan yaitu, barang paling laris sebanyak 15, barang yang laris sebanyak 45 dan kurang laris sebanyak 13. Dengan adanya pengolahan data yang dilakukan diharapkan dapat memberikan solusi kepada pihak perusahaan agar dapat mengetahui mana barang yang paling laris, laris dan mana barang yang tidak laris.
PENERAPAN METODE FUZZY MAMDANI UNTUK MENGANALISA PENTINGNYA KEDISIPLINAN DAN KOMUNIKASI UNTUK MENINGKATKAN PRESTASI KERJA KARYAWAN Tamba, Saut Parsaoran; Wibowo, Yonatan Adi; banjarnahor, jepri; Damanik, Ruth Tetra
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 3 No. 2 (2020): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jusikom.v3i2.937

Abstract

Penilaian prestasi kerja karyawan pada suatu perusahaan atau instansi, sangat berguna untuk mengevaluasi kerja dan memotivasi masing-masing karyawan untuk memenuhi standard kinerja yang telah ditentukan. Karyawan yang berprestasi bukan hanya mempunyai kemampuan yang tinggi dalam menyelesaikan pekerjaan tetapi juga bisa berkomunikasi yang baik serta mempunyai kedisiplinan. dengan demikian hasil pekerjaan akan dapat diharapkan menjadi lebih baik. PT. Universal merupakan sebuah perusahaan yang bergerak dalam bidang produksi obat-obatan, yang berada di kota Medan. Sistem yang digunakan untuk pencapaian kinerja karyawan saat ini masih bersifat manual dan belum secara maksimal memanfaatkan teknologi dalam mengembangkan proses bisnis, serta peningkatan efektifitas dalam pekerjaan mereka. Hal ini disebabkan oleh sistem penilaian yang terbangun belum didasarkan pada kompetensi individu. Selain itu proses penilaian membutuhkan waktu lama dan dokumentasi tidak teratur. Dalam pencapaian prestasi karyawan yang maksimal, sangat dibutuhkan peranan dari komunikasi dan kedisiplinan yang tinggi dari karyawan. Fuzzy Mamdani merupakan salah satu metode yang sangat fleksibel dan memiliki toleransi pada data yang ada. Variabel – variabel yang dipakai dalam penilaian prestasi karyawan adalah kedisiplinan dan komunikasi, yang akan dijadikan input. Berdasarkan kedua input yang dimasukkan maka output untuk prestasi kerja karyawan adalah 86.8 yang merupakan keanggotaan dari domain himpunan fuzzy sangat memuaskan [70 100] yang berarti prestasi kerjanya sangat memuaskan.
PENERAPAN DATA MINING MENGGUNAKAN ALGORITMA K-MEANS UNTUK MENENTUKAN JUDUL SKRIPSI DAN JURNAL PENELITIAN (STUDI KASUS FTIK UNPRI) Sembiring, Cornelia Selvi Dinta Br; Hanum, Latifah; Tamba, Saut Parsaoran
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 5 No. 2 (2022): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v5i2.2393

Abstract

Kemajuan teknologi saat ini berpengaruh pesat termasuk dalam bidang pendidikan khususnya dalam perkuliahan untuk menentukan judul skripsi dan jurnal penelitian. Dalam hal ini para pengembang menemukan suatu pola untuk mempermudah dalam pencarian ide judul untuk menyelesaikan syarat kelulusan perkuliahan dalam lingkup jurusan Sistem Informasi di Universitas Prima Indonesia. Untuk mengatasi permasalahan tersebut dengan menerapkan metode Algoritma K-Means. Metode tersebut bertujuan untuk mengelompokkan data mahasiswa seesuai dengan skill dan basic yang didominasi pada mata kuliah yang paling banyak diminati sebagai acuan dalam pengembangannya. Dengan adanya pengolahan data yang dilakukan dapat memberikan solusi kepada mahasiswa dan lingkupnya untuk mengetahui ide judul skripsi dan jurnal penelitian. Maka hasil uji coba mendapatkan perbandingan score dalam pembagian clustering yaitu pada 29% C1, 21% C2, 22% C3, 13% C4, 15% C5
Co-Authors -, Edbert -, Edric Ade Luthfi Ramadhan Perangin-Angin Adilman Reliance Hia Afluqfy Harahap Albert William Tan Alvin Purba Andina Riandra Tryvaldy Andreas Andreas Angga Snidres Girsang Angreyani Oktavia Anita Anita Banjarnahor, Jepri Cristian, Yusticio Damanik, Ruth Tetra Delima Sitanggang, Delima Didik Rifaldi Hia Dimiliu, M Bairaja Donny Prayitna Egi Suranta Bangun Elbert Ghozali Elida Mardiana Manik Feryanto ., Feryanto Intan Susanti Simarmata Josua Silaban Kesuma, Felix Toknady Kisen Kumar Latifah Hanum Malika, Salsa Manalu, Christ Natamaro Anastasius Mang Ayu Santi Vidyastuti Manurung, Onesimus Gust Marcel Hutabarat Mardi Turnip, Mardi Marlince Nababan Matondang, Matius Merry Christina Mohammad Irfan Fahmi Ndruru, Liberlina Palma Juanta Panjaitan, Gracia Laura Pasaribu, Yuni Rumyanti Peni Wulandari Pratama, Duta Puri, Anin Dita Sekar Ricky Gunawan, Ricky Rizky Prayoga Rizky Syahputra Sitompul Rizky, Rahmad Roy F. Hasudungan Malau Santosa, Sofian Ali Sembiring, Cornelia Selvi Dinta Br Siburian, Yosepha Sinambela, Rio Siregar, Bina Jaya Sitanggang, Mario Situmorang, Bimo Christhoper Steven Steven Surya Dharma Valerine, Karen Wibowo, Yonatan Adi Wijaya, Salim William William Windania Purba Yoel Ferdinand Zai Yogga Eka Kusuma Yonata Laia Yudi Gunawan