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All Journal Jurnal Ilmiah Edunomika (JIE) Jurnal Pengabdian kepada Masyarakat Nusantara JURNAL REKAYASA INFORMASI SWADHARMA (JRIS) Jurnal Media Computer Science
Wawan Laksito Yuly Saptomo
Universitas Tiga Serangkai
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Social Sciences

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KLASIFIKASI PRESTASI AKADEMIK MAHASISWA MENGGUNAKAN METODE RANDOM FOREST Serly Sustiana Saputri; Dwi Remawati; Teguh Susyanto; Wawan Laksito Yuly Saptomo
JRIS : Jurnal Rekayasa Informasi Swadharma Vol 6, No 2 (2026): JURNAL JRIS EDISI JULI 2026
Publisher : Institut Teknologi dan Bisnis (ITB) Swadharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56486/jris.vol6no2.1179

Abstract

This study aims to classify student academic achievement using the Random forest algorithm, utilizing the Student Performance dataset from Kaggle. The main attributes used as predictors include attendance rate, weekly study duration, and class engagement. The research methodology included data preprocessing with label encoding, an 80:20 split between training and test sets, and standardized model evaluation using accuracy, precision, recall, and F1-score. The results showed an accuracy of 31.03%. This low accuracy is due to the complexity of multi-class classification and imbalanced data distribution. This research contributes to mapping student learning behavior patterns and serves as a reference for developing more optimal academic prediction models.Penelitian ini bertujuan untuk mengklasifikasikan prestasi akademik mahasiswa menggunakan algoritma Random forest dengan memanfaatkan dataset Students Performance dari Kaggle. Atribut utama yang digunakan sebagai prediktor meliputi tingkat kehadiran, durasi belajar mingguan, dan keterlibatan di kelas. Metodologi penelitian mencakup pra-pemrosesan data dengan label encoding, pembagian data latih dan uji (80:20), serta evaluasi model yang diseragamkan menggunakan metrik akurasi, precision, recall, dan F1-score. Hasil penelitian menunjukkan nilai akurasi sebesar 31,03%. Rendahnya akurasi tersebut merupakan dampak dari kompleksitas klasifikasi multi-kelas dan distribusi data yang tidak seimbang (imbalanced data). Penelitian ini memberikan kontribusi dalam memetakan pola perilaku belajar mahasiswa serta menjadi referensi bagi pengembangan model prediksi akademik yang lebih optimal.
Usability Evaluation And User Acceptance Testing (Uat) On Website-Based Digital Psychology Testing Application: A Case Study Of Psikotestyuk.Id Adi Putra Dwi Nugraha; Wawan Laksito Yuly Saptomo
Jurnal Media Computer Science Vol 5 No 3 (2026): Juli
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v5i3.11666

Abstract

Digital transformation in the recruitment process through digital psychological testing applications such as psikotestyuk.id aims to increase the efficiency and objectivity of candidate selection. However, the effectiveness of this system is highly dependent on the ease of use and functional acceptance by end users, both prospective employees and HR. This study aims to evaluate the level of usability and user acceptance of the psikotestyuk.id application to identify operational obstacles and areas for system architecture improvement. The method used is Mixed Methods, integrating quantitative data from Usability Testing on 30 prospective employee respondents, and qualitative data from User Acceptance Testing (UAT) with in-depth interviews with three HR staff. The results showed an average usability score in the "Very Good" category with a value range of 4.21 to 4.40. Although functionally the system was very well received, UAT testing revealed the need for server infrastructure optimization to handle high traffic and the addition of a bulk data import feature to improve the efficiency of mass recruitment administration. In conclusion, the psikotestyuk.id application is very suitable for continued use with several development notes on the data scalability side.
Otomasi Nutrisi Hidroponik Berbasis IoT untuk Greenhouse Mitra Soloraya melalui PjBL-OJT Ahmad Muhariya; Dziky Ridhwanullah; Yenny Rahmawati; Wawan Laksito Yuly Saptomo; Sapto Nugroho; Teguh Susyanto; Muhammad Hasbi; Saly Kurnia Octaviani; Ilham Fannani
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 7 No. 2 (2026): Edisi Mei - Agustus
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jpkmn.v7i2.9243

Abstract

Kesenjangan antara penguasaan teori Internet of Things (IoT) dan implementasi perangkat keras di lapangan menjadi tantangan pendidikan tinggi dalam mencetak talenta pertanian modern. Merespons hal ini, Program Studi S1 Informatika Universitas Tiga Serangkai (UTS) menyelenggarakan Pelatihan dan On-the-Job Training (OJT) "Smart Farming Project Based Learning" berkolaborasi dengan Edutic dan Balai Pelatihan Vokasi dan Produktivitas (BPVP) Surakarta. Kegiatan ini bertujuan menyelesaikan kendala pencampuran nutrisi hidroponik manual yang rentan tidak presisi pada unit usaha mitra. Melalui pendekatan Project Based Learning (PjBL), 16 mahasiswa lintas program studi dilibatkan mulai dari perancangan hingga implementasi purwarupa Smart Nutrition System pada empat greenhouse mitra. Hasil kegiatan menunjukkan 100% peserta dinyatakan kompeten pada Uji Kompetensi (UJK) skema otomasi nutrisi, dan tiga dari empat purwarupa sistem berhasil diimplementasikan secara berkelanjutan di lokasi mitra. Kolaborasi antara kampus, industri, dan lembaga vokasi terbukti efektif mencetak talenta digital sekaligus mengakselerasi digitalisasi sistem hidroponik pada level UMKM/BUMDes.
PENGARUH LITERASI DIGITAL DAN KECERDASAN EMOSIONAL TERHADAP KESIAPAN KERJA MAHASISWA: MOTIVASI KERJA SEBAGAI AGEN PENDORONG Elistya Rimawati; Ari Wibowo; Wawan Laksito Yuly Saptomo; Cinthia Annisa Vinahapsari
JURNAL ILMIAH EDUNOMIKA Vol. 10 No. 3 (2026): EDUNOMIKA
Publisher : ITB AAS Indonesia Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/jie.v10i3.20285

Abstract

The rapid advancement of digital technology has increased the demand for graduates who possess not only technical competencies but also strong psychological readiness for work. This study aims to examine the effects of digital literacy and emotional intelligence on students’ work readiness, with work motivation serving as a mediating variable. A quantitative approach was employed. Data were collected through an online questionnaire distributed to Information Systems and Informatics students who had completed Digital Transformation courses and were preparing for career entry. The data were analyzed using Partial Least Squares Structural Equation Modeling. The findings reveal that digital literacy and emotional intelligence have positive and significant effects on both work motivation and work readiness. Work motivation also significantly influences work readiness. Furthermore, work motivation partially mediates the relationships between digital literacy and work readiness, as well as between emotional intelligence and work readiness. The structural model demonstrates substantial explanatory power. These results suggest that digital literacy and emotional intelligence function as essential capabilities that can be transformed into actual work readiness when supported by strong work motivation. Therefore, higher education institutions should integrate technological competence development, emotional skill enhancement, and motivational interventions to better prepare students for the evolving labor market.
Co-Authors Adi Putra Dwi Nugraha Ahmad Muhariya Ari Wibowo Cinthia Annisa Vinahapsari Dwi Remawati Dziky Ridhwanullah Elistya Rimawati Ilham Fannani Muhammad Hasbi Saly Kurnia Octaviani Sapto Nugroho Serly Sustiana Saputri Teguh Susyanto Yenny Rahmawati