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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Mantik Penusa JurTI (JURNAL TEKNOLOGI INFORMASI) Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Building of Informatics, Technology and Science JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Jurnal Teknik Informatika (JUTIF) Jutsi: Jurnal Teknologi dan Sistem Informasi Bulletin of Computer Science Research Journal of Social Responsibility Projects by Higher Education Forum J-Com (Journal of Computer) Jurnal Ipteks Terapan : research of applied science and education Aptekmas : Jurnal Pengabdian Kepada Masyarakat Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Zadama: Jurnal Pengabdian Masyarakat Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Yessica Siagian
Sekolah Tinggi Manajemen Informatika Dan Komputer Royal
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APPLICATION OF E-CRM IN MUSHROOM SALES (A CASE STUDY OF BOMBOM BUSINESS) Citra Novianti; Yessica Siagian; Ahmad Muhazir
Jurnal Ipteks Terapan (Research Of Applied Science And Education ) Vol. 17 No. 1 (2023): Jurnal Ipteks Terapan : research of applied science and education
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah X

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (636.948 KB) | DOI: 10.22216/jit.v17i1.1567

Abstract

Bombom business is a business engaged in the sale and cultivation of mushrooms, where there are several types of mushrooms that are cultivated such as oyster mushrooms, ear mushrooms, straw mushrooms, button mushrooms, and toadstools. The location of this business is in Mangkai Baru Village, Lima Puluh District, Batu Bara Regency. Currently the process of selling mushrooms is only done manually, namely by coming directly to the business location and in marketing this business is still doing marketing directly through banners in front of the house and this business does not yet have a sales system that covers a wide area to market its products to a wider area. as outside the province. The method used in this research is to apply Electronic Customer Relationship Management (E-CRM). The results of implementing E-CRM (Electronic Customer Relationship Management) mushroom sales in the bombom business can improve service to customers and can increase mushroom sales in the bombom business. Based on the results of these studies, it can be concluded that E-CRM can help in the sale of mushrooms which can increase sales and can retain customers.
Pemanfaatan Zoom Meeting Sebagai Solusi Pembelajaran Interaktif Di Masa Pandemi Yessica Siagian; Guntur Maha Putra; Arridha Zikra Syah
Educativo: Jurnal Pendidikan Vol 1 No 1 (2022): Zadama: Jurnal Pengabdian Masyarakat
Publisher : PT. Marosk Zada Cemerlang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (928.563 KB) | DOI: 10.56248/zadama.v1i1.22

Abstract

Pandemi  Covid-19  memberikan dampak yang  cukup  besar dalam  berbagai  bidang termasuk bidang  pendidikan. Sebagai  upaya  untuk  mengurangi  persebaran  Covid-19  di  Indonesia,  maka pemerintah Indonesia  menerapkan suatu  kebijakan physical  distancing, yaitu anjuran   menjaga jarak  diantara  masyarakat, mengurangi   jenis aktivitas   yang   melibatkan banyak   orang   secara   langsung,   menghindari   kerumunan, perkumpulan,  dan  mengurangi  berbagai  aktivitas  di  ruang  terbuka. Adanya  penetapan kebijakan physical distancing selanjutnya menjadi  dasar  pelaksanaan pembelajaran  secara online, mulai dari tingkat PAUD hingga jenjang perguruan tinggi. Kebijakan physical distancing tersebut menyebabkan guru dan siswa diwajibkan untuk beradaptasi dengan situasi dan kondisi selama pandemi dengan melakukan proses pembelajaran daring. Untuk itu dibutuhkan aplikasi seperti Zoom Meeting, sebagai  multimedia  interaktif dalam pembelajaran online di  masa  pandemi. Meskipun  demikian,  penggunaan  aplikasi  tersebut  menimbulkan  permasalahan  baru  dikarenakan  tidak  semua siswa bisa mengikuti pembelajaran online dengan baik. Walaupun sebelumnya sekolah telah memberikan sosialisasi terhadap siswa cara penggunaan beberapa aplikasi yang digunakan dalam proses pembelajaran daring, namun masih banyak siswa yang belum familiar dan belum memahami dengan baik. Hal tersebut mengakibatkan menurunnya minat dan hasil belajar siswa. Sehubungan dengan itu, pengabdian kepada masyarakat ini dilakukan untuk memberi pelatihan bagi siswa SMA Panti Budaya mengenai cara menggunakan aplikasi Zoom Meeting di Laptop dan HP Android. Pelatihan ini bertujuan memanfaatkan Zoom Meeting sebagai solusi pembelajaran interaktif, dan menarik untuk memaksimalkan proses pembelajaran dimasa pandemi Covid-19. Peserta pelatihan dalam kegiatan pengabdian kepada masyarakat ini adalah siswa kelas XII pada SMA Panti Budaya. Hasil dari pelatihan ini, siswa SMA Panti Budaya dapat praktik memanfaatkan Zoom Meeting dalam proses pembelajaran daring dengan baik.
Data Mining Klasifikasi Breast Cancer Menerapkan Algoritma Gradient Boosted Trees Kraugusteeliana Kraugusteeliana; Saludin Muis; Fifto Nugroho; Abdul Karim; Yessica Siagian
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 2 (2023): April 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i2.6095

Abstract

Cancer is a deadly disease that is often experienced suddenly. Cancer is suffered not only among adults and the elderly, but even small children who are just born can also suffer from cancer. There are many types of cancer that have almost the same symptoms but different types and there are also levels of seriousness (danger) of these cancers, ranging from common cancers to malignant cancers that have significant changes to the body. There are many types of cancer, one of which is breast cancer, which is more common in women. This type of cancer often occurs in adult women and the elderly. In this study, to facilitate the diagnosis of breast cancer, a classification method was applied. By making an early diagnosis can reduce the mortality rate, previous diagnosis is done by utilizing image media (PET scan and CT scan) which takes a long time so it is considered less efficient. The classification algorithm used is gradient boosted trees. The test was carried out using the rapidminer application as a tester to determine the accuracy of the algorithm and also the AUC size obtained using information gain. The final result after applying the gradient boosted method produces an accuracy rate of 58.52%, this is considered less effective to use so this algorithm is not suitable to be used as a prediction of breast cancer. Precision of 64.25% and recall of only 69.44%.
SISTEM PENDUKUNG KEPUTUSAN PENILAIAN ADMINISTRASI DESA DI KECAMATAN AIR JOMAN DENGAN MENGGUNAKAN METODE TOPSIS Yulia Safitri; Yessica Siagian; Afdhal Syafnur
JUTSI: Jurnal Teknologi dan Sistem Informasi Vol 2, No 1 (2022): February 2022
Publisher : LPPM STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jutsi.v2i1.1530

Abstract

Abstract: This research aims to apply the TOPSIS method in the support system of village administration assessment decisions in Air Joman subdistrict office based on predetermined criteria. Assessment of village administration is a routine program organized by the government every year, especially in Joman Water Subdistrict. Calculation and evaluation of village administration have been done using Microsoft Excel applications that certainly have not been integrated with the database. For this reason, an application is needed to assist the village administration assessment process against the criteria that have been set for each field by using the TOPSIS method. This research uses qualitative methods with data collection techniques through observation, interviews, and documentation. The results of this study facilitate and accelerate in carrying out the administrative assessment process by the village government, based on the ranking of preference values from the highest to the lowest, where the fertile village is the village that has the best administration with the highest score of 0.753. Keywords: decision support system; village administration assessment; air joman; topsis.  Abstrak: Penelitian ini bertujuan untuk menerapkan metode TOPSIS dalam sistem pendukung keputusan penilaian administrasi desa di kantor kecamatan Joman Air berdasarkan kriteria yang telah ditentukan. Penilaian administrasi desa merupakan program rutin yang diselenggarakan oleh pemerintah setiap tahun khususnya di Kecamatan Air Joman. Perhitungan dan evaluasi administrasi desa selama ini dilakukan dengan menggunakan aplikasi Microsoft Excel yang tentunya belum terintegrasi dengan database. Untuk itu diperlukan sebuah aplikasi untuk membantu proses penilaian administrasi desa terhadap kriteria yang telah ditetapkan untuk masing-masing bidang dengan menggunakan metode TOPSIS. Penelitian ini menggunakan metode kualitatif dengan teknik pengumpulan data melalui observasi, wawancara dan dokumentasi. Hasil dari penelitian ini memudahkan dan mempercepat dalam melakukan proses penilaian administrasi oleh pemerintah desa, berdasarkan pemeringkatan nilai preferensi dari yang tertinggi sampai yang terendah, dimana desa yang subur merupakan desa yang memiliki administrasi terbaik dengan skor tertinggi 0,753. Kata kunci: sistem pendukung keputusan; penilaian administrasi desa; air joman; topsis.
PENERAPAN ALGORITMA NAIVE BAYES UNTUK PREDIKSI WAKTU TUNGGU ALUMNI MENDAPATKAN PEKERJAAN PADA LEMBAGA PUSAT LAYANAN KARIR STMIK ROYAL Tasyia Dita Aulia; Yessica Siagian; Pristiyanilicia Putri
J-Com (Journal of Computer) Vol 3, No 2 (2023): Juli 2023
Publisher : LPPM STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/j-com.v3i2.2504

Abstract

Abstract: Getting a job is a goal by graduates after completing their studies. But in this process, getting a job inevitably requires waiting time. If one measure of success in the field of education of a tertiary institution is the number of graduates entering the workforce. So to implement this goal, alumni data is needed that can be used in decision making. Existing tracer study data at the STMIK Royal Career Service Center (LPLK) have not been utilized optimally by the campus. If we dig deeper, we will get some knowledge from this data by applying data mining techniques. Therefore, it is clear that using data mining to predict alumni waiting time is important for a university to determine its strategy. The purpose of this study is to predict the waiting time for alumni to get a job using data mining by applying the Naive Bayes algorithm. Training and testing data were taken from 193 data tracer study alumni of STMIK Royal in 2021 who had graduated and were working. The criteria used to predict alumni waiting time are gender, major, year of entry, year of graduation, GPA, and length of time getting a job. The results of modeling using the Naive Bayes algorithm produce an accuracy of 94%. Keyword: data mining; naive bayes; waiting time  Abstrak: Mendapatkan pekerjaan merupakan tujuan oleh lulusan setelah menyelesaikan studi mereka. Tetapi dalam proses ini, mendapatkan pekerjaan pasti membutuhkan waktu tunggu. Jika salah satu ukuran keberhasilan di bidang pendidikan suatu perguruan tinggi adalah banyaknya lulusan yang masuk ke dunia kerja. Maka untuk menerapkan tujuan itu, maka diperlukan data alumni yang dapat digunakan dalam pengambilan keputusan. Data tracer study yang ada di Lembaga Pusat Layanan Karir (LPLK) STMIK Royal belum dimanfaatkan secara optimal oleh kampus. Jika kita gali lebih dalam, kita akan mendapatkan suatu pengetahuan dari data ini dengan menerapkan teknik data mining. Oleh karena itu, jelas bahwa menggunakan data mining untuk memprediksi waktu tunggu alumni penting bagi suatu perguruan tinggi untuk menentukan strateginya. Tujuan dari penelitian ini adalah untuk memprediksi waktu tunggu alumni mendapatkan pekerjaan  menggunakan data mining dengan menerapkan algoritma naive bayes. Data training dan testing diambil dari 193 data tracer study alumni STMIK Royal tahun 2021 yang sudah lulus dan bekerja. Kriteria yang digunakan untuk memprediksi waktu tunggu kerja alumni yaitu jenis kelamin, jurusan, tahun masuk, tahun lulus, IPK, dan lama mendapatkan pekerjaan. Hasil pemodelan dengan menggunakan algoritma naive bayes menghasilkan akurasi sebesar 94%. Kata Kunci: data mining; naive bayes; waktu tunggu
Implementasi Metode Weighted Product Untuk Seleksi Calon Instruktur Pada LKP Mandiri Computer Neny Mulyani; Yessica Siagian
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 2, No 1 (2021): Edisi Januari
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v2i1.60

Abstract

LKP Mandiri in selecting prospective instructors still uses the assessment system manually so that all data selection of new instructor candidates does not have a fixed weight, is still subjective and often occurs errors in the calculation process and takes a relatively long time in calculating the value of the alternative. For that in this research applied weighted product (WP) method in determining new instructor candidates because the weighted product (WP) method is a method of completion by using multiplication to connect the attribute rating, where the rating must be raised first with the weight of the attribute in question, this process is the same as the normalization process. With the WP (Weighted Product) method implemented into the decision support system in LKP Mandiri facilitates calculation in making decisions to get prospective instructors.
PELATIHAN PEMANFAATAN TEKNOLOGI INFORMASI DI ERA DIGITAL BAGI SISWA/I SMK BM YAPIM SIMPANG KAWAT Arridha Zikra Syah; Yessica Siagian; Novica Irawati
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol 3, No 2 (2023): Desember 2023
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v3i2.1532

Abstract

Abstract: SMK Yapim has an Accounting study program that produces practitioners in financial reporting. Students have good abilities in accounting. To be able to keep pace with competition in the industrial era 4.0, they must also master information technology such as Accounting Information Systems, operating computer systems quickly and precisely. This service aims to equip students with basic information technology skills as supporters of office technology. The method used in this training is the provision of material or counseling and training. With this training, it is expected that these students will be able to utilize Information Technology to support their abilities in an appropriate, effective and efficient manner.Keyword: Hot Key; Office applications,Utilization of Information Technology; Training.Abstrak: SMK Yapim memiliki program study Akuntansi yang menghasilkan praktisi dalam pelaporan keuangan. Siswa memiliki kemampuan yang baik di bidang akuntansi. Untuk dapat mngimbangi persaiingan di era industri 4.0, merekapun harus menguasai teknologi informasi seperti halnya Sistem Informasi Akuntansi, pengoperansian sistem komputer secara cepat dan tepat. Pengabdian ini bertujuan untuk membekali siswa dengan kemampuan dasar teknologi informasi sebagai pendukung teknologi perkantoran. Metode yang digunakan dalam pelatihan ini adalah pemberian materi atau penyuluhan dan pelatihan. Dengan adanya pelatihan ini, diharapkan siswa-siswa tersebut mampu untuk memanfaatkan Teknologi Informasi untuk menunjang kemampuan mereka secara tepat guna, efektif dan efisien.Kata kunci: aplikasi perkantoran; Hot Key; Pemanfaatan Teknologi Informasi; Pelatihan.
Penentuan Bibit Kelapa Sawit Unggul dengan Metode ARAS dan TOPSIS Yessica Siagian; Mulyani, Neni
Bulletin of Computer Science Research Vol. 4 No. 6 (2024): Oktober 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v4i6.367

Abstract

The Industrial Era 4.0 opens up great opportunities to increase production, efficiency and sustainability of the palm oil industry. The problem faced by farmers is that farmers are often hampered by limited knowledge and lack of guidance in choosing plant seeds. Because seeds are an important factor in supporting satisfactory results. This research was carried out to help farmers who have difficulty in choosing oil palm seeds which could become a problem for farmers in the future. day. This research uses the ARAS and TOPSIS methods to evaluate seeds based on criteria that have been identified and analyzed, to assess 10 types of superior seeds based on 5 criteria: oil potential, pest resistance, seed price, productive planting period, and maintenance costs. It is hoped that this research can help oil palm farmers increase their productivity and profits, as well as support the sustainability of the palm oil industry in the Industry 4.0 era. The ARAS and TOPSIS methods have proven to be effective in helping farmers choose superior oil palm seeds. From the results of research conducted using the ARAS and TOPSIS methods, VIM 1 seeds were recommended as the best choice based on the points obtained
Comparison Of Machine Learning Algorithms For Rice Production Prediction In Sumatra Abdul Karim; Yuwaldi Away; Syahrial; Roslidar; Jeperson Hutahaean; William Ramdhan; Yessica Siagian
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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

Abstract

Rice production prediction is a crucial aspect in agricultural planning and food security. This study compares the performance of four regression algorithms in predicting rice production based on agronomic and climatological variables. The algorithms used are Random Forest Regression, XGBoost Regression, Support Vector Regression (SVR), and Artificial Neural Network (ANN). The evaluation results showed that Random Forest performed best with an R² of 0.963, followed by XGBoost with an R² of 0.959, indicating that these two models were able to explain more than 95% of the data variation. In contrast, SVR performed poorly with an R² of -0.064, while ANN had the worst result with an R² of -2.417, indicating the model's unsuitability for the dataset used. Thus, it can be concluded that Random Forest and XGBoost are the best options for rice production prediction, while SVR and ANN require further optimization to be used effectively in this context.
Co-Authors Abdul Karim Abdul Karim Abdul Karim Syahputra Afdhal Syafnur Arridha Zikra Syah Citra Novianti Desma Erica Maryati Manik Dwi Agus Wita Edi Kurniawan Emi Okta Purwita Sari Fifto Nugroho Guntur Maha Putra Hommy Dorthy Ellyany Sinaga Jeperson Hutahaean Kifti, Wan Mariatul Kraugusteeliana Kraugusteeliana Mhd. Ihsan Muhammad Amin Muhammad Ardiansyah Sembiring Muhazir, Ahmad Neny Mulyani Norenta sitohang Novica Irawati Novita Sari Sitorus Nurul Azura Pristiyanilicia Putri Putri Eka Wardani Putri Masliana Rika Nofitri Rizaldi Rizaldi Rohminatin Rohminatin Romy Aulia Roslidar safrian aswati Sahren Saludin Muis Sri Rezki Maulina Azmi Syahrial Tasyia Dita Aulia Widia Lestari William Ramdhan Yulia Safitri Yunita Yuwaldi Away Zuhairoh Zuhairoh Zulfi Azhar