Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal SISFOTENIKA Jurnal Sisfokom (Sistem Informasi dan Komputer)
Yuyi Andrika
Department Of Information Systems, Faculty Of Information Technology, ISB Atma Luhur
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
RANCANGAN SISTEM INFORMASI PENELUSURAN PENGGUNA ALUMNI BERBASIS WEB PADA STMIK ATMA LUHUR PANGKALPINANG Yuyi Andrika; Melati Suci Mayasari; Harrizki Arie Pradana
SISFOTENIKA Vol 9, No 1 (2019): SISFOTENIKA
Publisher : STMIK PONTIANAK

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (538.103 KB) | DOI: 10.30700/jst.v9i1.453

Abstract

Data pengguna alumni di suatu perguruan tinggi sangatlah dibutuhkan untuk kepentingan akreditasi program studi. Kebutuhan untuk data pengguna alumni perguruan tinggi itu sendiri meliputi kepuasan pengguna terhadap alumni dan banyak lagi kegiatan-kegiatan di perguruan tinggi yang berhubungan dengan pengguna alumni perguruan tinggi itu sendiri. Dalam mengelola data pengguna alumni itu sendiri banyak perguruan tinggi yang merasa kesulitan tidak terkecuali dengan STMIK Atma Luhur itu sendiri. Di STMIK Atma Luhur pengelolaan pengguna alumni masih dilakukan secara manual dengan membagikan kuesioner kepada alumni selanjutnya meneruskannya ke atasan mereka untuk diisi. Hasilnya nanti baru diarsip dan direkap oleh Bagian Kemahasiswaan. Metode yang dilakukan dalam penelitian ini dengan menggunakan metode terstruktur dengan menggunakan model Waterfall.  Oleh sebab itu dibutuhkan sebuah sistem informasi untuk menyimpan data-data pengguna alumni agar dapat tersimpan secara efektif dan efesien serta apabila dibutuhkan dapat dicari dengan cepat dan mudah.. Hasil yang didapatkan dari penelitian ini dalam melakukan pendataan pengguna alumni, menghasilkan sistem informasi yang efektif dan efesien dalam mengumpulkan data tentang pengguna alumni. Dalam melakukan pendataan alumni tidak perlu mendatangi satu persatu alumni di tempat mereka bekerja tetapi cukup menginformasikan kepada mereka melalui email untuk mengisi kuesioner. Selanjutnya alumni akan menginformasikan kepada atasannya untuk mengisi kuesioner tersebut.Kata Kunci : Pengguna Alumni, Sistem Informasi Web, Metode Terstruktur
Teacher Selection Analysis at Pangkalpinang Baptist School Using SAW Method Fitriyani Fitriyani; Devi Irawan; Ari Amir Alkodri; Yuyi Andrika; Melati Suci Mayasari; Chandra Kirana
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 15 No. 1 (2026): JANUARY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v15i01.2574

Abstract

Selecting competent teachers plays a vital role in enhancing the quality of education at Pangkalpinang Baptist School. However, the use of subjective judgment in the recruitment process often leads to less effective decision-making. Therefore, this research aims to examine the teacher selection mechanism by applying the Simple Additive Weighting (SAW) method to strengthen the objectivity and precision of the selection decisions. The SAW approach assesses applicants using three main criteria: interview performance (30%), academic test results (35%), and micro teaching skills (35%).Each criterion receives specific weights according to importance levels, followed by calculations to determine candidates with the highest scores. Research results demonstrate that SAW method implementation provides more systematic and transparent decisions in teacher selection. The study evaluated 10 teacher candidates with Eka Sitompul achieving the highest score of 0.85, followed by Fandi Saputra and Vitta Natalia with 0.825 each. This method enables schools to conduct data-based selection, reducing subjectivity in recruitment processes and ensuring selected teaching staff possess competencies aligned with school requirements.
CRISP-DM Based Sentiment Analysis on MSME Loan Opinions in Bangka Belitung Using Naïve Bayes Ari Amir Alkodri; Fitriyani Fitriyani; Melati Suci Mayasari; Yuyi Andrika; Sarwindah Sarwindah; Agus Dendi
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 15 No. 3 (2026): JULY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v15i3.2711

Abstract

The development of the MSMEs sector plays a crucial role in national economic growth. It not only supports the regional economy but also significantly impacts and contributes to job creation and equitable income distribution. However, one of the primary obstacles faced by MSMEs is limited access to financing or loans. To address this issue, many government and private institutions provide financing and mentoring programs. This study focuses on the analysis of sentiment opinions regarding assisted MSMEs loans in the Bangka Belitung Islands Province using the Cross-Industry Standard Process for Data Mining approach and the Multinomial Naïve Bayes algorithm, was utilized for opinion sentiment analysis on assisted MSME loans, with a total of 1,112 reviews collected through surveys and data from assisted MSMEs, such as Witel. This study successfully implemented the CRISP-DM framework and the Multinomial Naïve Bayes algorithm to analyze public opinion sentiment toward assisted MSME loan programs in the Bangka Belitung Islands Province. Achieving an accuracy of 96.02%, this model proves to be highly effective and efficient in extracting and classifying survey-based opinion data. The primary scientific contribution of this research is the successful integration of a structured data mining approach with local economic policy analysis. However, a trade-off was identified in the Negative Recall of 0.79, indicating that 21% of negative opinions were missed due to a class imbalance where positive opinion data significantly outnumbered negative opinions in the survey. Overall, this approach yielded exceptionally high evaluation metrics, achieving a Positive Recall of 1.00 and a Negative Precision of 1.00.
Co-Authors Agus Dendi Ari Amir Alkodri Ari Amir Alkodri Chandra Kirana Devi Irawan Fitriyani Fitriyani Fitriyani Fitriyani Harrizki Arie Pradana Melati Suci Mayasari Melati Suci Mayasari Melati Suci Mayasari, Melati Suci Sarwindah Sarwindah