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All Journal Jurnal Mantik Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer)
Sethu Ramen
STMIK Pelita Nusantara
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Languange, Linguistic, Communication & Media Social Sciences

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Pelatihan Peningkatan Kemampuan Pengunaan Microsoft Office Bagi Mahasiswa Sekolah Tinggi Teologi Baptis Medan Jonson Manurung; Bosker Sinaga; Paska Marto Hasugian; Logaraj Logaraj; Sethu Ramen
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 2 No. 2 (2022): Jurnal Pengabdian kepada Masyarakat Nusantara (JPkMN)
Publisher : Cv. Utility Project Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (363.033 KB) | DOI: 10.55338/jpkmn.v2i2.252

Abstract

Students at almost all levels of education are required to be technology literate, especially information technology. In addition to supporting educational activities, it also supports students in solving administrative problems. One of the software that can be used to support education and administrative issues is Microsoft Office. The application has many features that are still not familiar to some users, especially students. This was experienced by STT Baptist Medan who was not familiar with the many tools provided in Microsoft Word, Microsoft Excel, and Microsoft PowerPoint software. Some of the obstacles that are often encountered are the less than optimal use of the merge function in Word, the function of conditional formulas in Excel and animation, and multimedia in PowerPoint. During the implementation of service activities, it was concluded that the importance of direct Microsoft office training to students, especially study programs outside of computers. In the implementation of the training, students are able to use Microsoft Excel to manage numerical data. Microsoft word in managing data. Also the use of Microsoft PowerPoint in making presentations.
Student Graduation Value Analysis Based On External Factors With C4.5 Algorithm Fristi Riandari; Hengki Tamando Sihotang; Rohit Gautama; Sethu Ramen
Jurnal Mantik Vol. 6 No. 2 (2022): August: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v6i2.2784

Abstract

Data mining is the process of extracting data into information that has not previously been conveyed, with the right techniques the data mining process will provide optimal results. Data Mining is divided into several methods. Data classification is a process of finding the same properties in a set of objects in a database and classifying them into different classes according to the defined classification model. The purpose of classification is to find a model from the training set that distinguishes attributes into the appropriate category or class, the model is then used to classify attributes whose class has not been previously known. The classification technique is divided into several techniques, one of which is the Decision Tree. One of the existing approaches in the classification technique is the C4.5 algorithm. The C4.5 algorithm is an approach in data mining classification techniques that can predict students' final grades. The variables used in analyzing the passing grades will be classified based on their attributes. The C4.5 algorithm with the decision tree method can provide predictive rule information to describe the process associated with analyzing student passing grades. The characteristics of the classified data can be obtained clearly, both in the form of a decision tree structure and rules so that in the testing phase the RapidMiner software can help predict student passing grades. With the formation of rules that can become new information that can be used as a tool in analyzing student passing grades.
Prediksi Keberhasilan Penanganan Stunting Menggunakan Seleksi Fitur PSO Dengan SaaS Cloud Computing Anita Sindar Sinaga; Sethu Ramen; Sri Mulyani
Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Vol 23 No 1 (2024): Februari 2024
Publisher : PRPM STMIK TRIGUNA DHARMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jis.v23i1.9561

Abstract

Permasalahan stunting merupakan tugas pokok setiap pemerintahan dari perkotaan sampai desa-desa. Deep Learning dapat mengenal pola rumit yan ada pada gambar, dokumen, video, dan data lain untuk menghasilkan prediksi yang akurat. Pengolahan data tidak terstruktur seperti kata, kalimat dapat diekstrak menerapkan Particle Swarm Optimization (PSO). Pengolahan data tidak terstruktur pada kata dan kalimat bersumber dari media online diekstrak menerapkan Particle Swarm Optimization (PSO) mencakup swarm, partikel, Pbest, Gbest, dan Velocity. Melalui empat tahapan algoritma PSO dimulai dari Inisialisasi, Evaluation fungsi fitness, update dan Termination. Prediksi capaian penanganan program stunting berdasarkan dampak, pencegahan, dan penyebab stunting yang diekstrak dari berbagai media online menggunakan Neural Network Particle Swarm Optimization (PSO) yang dibangun pada layanan perangkat lunak SaaS Cloud menghasilkan persentase baik akurasi Seleksi Fitur PSO sebesar 85.36%. Aplikasi SaaS dapat menginformasikan tingkat keberhasilan penanganan program stunting dari pencarian kalimat tidak terstruktur yang terhubung dengan internet
Co-Authors Bosker Sinaga Fristi Riandari Hasugian , Paska Marto Hengki Tamando Sihotang Logaraj Logaraj Rohit Gautama Sinaga, Anita Sindar R M Sri Mulyani