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Analisis Penggunaan M-Attendance Student dengan Pendekatan TAM dan UTAUT Bayu Nugraha; Nurhaeni Nurhaeni; M Rizki Ikhsan
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 12 No 01 (2022): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v12i01.657

Abstract

M-Attendance is an online attendance system that can simplify the method of recording student attendance so as to reduce errors and speed up verification. This study aims to determine the success rate of implementing the M-Attendance Student system as student attendance at Sari Mulia University (UNISM) using the TAM (Technology Acceptance Model) and UTAUT (Unified Theory of Acceptance and Use of Technology) methods. The TAM method can be used to explain the factors of user behavior towards technology acceptance, user acceptance behavior towards technology, while through UTAUT it can be understood that the user's reaction and perception of technology can affect his attitude in accepting technology use. This study uses all the variables of the two methods. Measurement of the data analyzed in this study using a questionnaire distributed to 100 respondents, namely students at Sari Mulia University.Based on the results of the analysis of the TAM method, it was found that the intention to use the actual effect on the use of the system was 77%, the intention to use was influenced by the attitude towards the use of 41.7% and the perception of the usefulness of 43%, the attitude towards the use was influenced by the perception of the usefulness of 41. 5% and the perception of the ease of use of 49.7%, the perception of the ease of use affects the perception of the usefulness of 87.9%. Meanwhile, based on the results of the analysis of the UTAUT method, it was found that the intention to use and the facilitating conditions affected user behavior by 68% and 31%, usage behavior was only influenced by business expectations by 56% and social influence by 44.6%. Expectations on performance have no effect because they only get a score of 0.13%.
Metode Simple Additive Weighting Untuk Pemilihan Sosial Media Pada Pemasaran Digital UMKM Kuliner Kota Banjarmasin Rusidah Rusidah; Nurhaeni Nurhaeni; Ahmad Hidayat; Mambang Mambang
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 15 No 01 (2025): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v15i01.1461

Abstract

Digital marketing has become very important because the world of marketing has changed through advances in information technology. Interactive and integrated marketing that allows market intermediaries, potential consumers and producers to interact with each other. Instagram, WhatsApp, Twitter, Facebook, Telegram, TikTok, YouTube, and Shopee are social media that are often used in digital marketing. In this research, the data used is Banjarmasin City Culinary UMKM data obtained through a questionnaire totaling 174 respondent data which was distributed to the Banjarmasin City Culinary UMKM group. Data obtained from decision support system calculations using the Simple Additive Weighting method shows that many social media that are popular in society may not be suitable for use as digital media for culinary marketing. The results of the Simple Additive Weighting research show that it can be used to help culinary MSMEs in Banjarmasin City in making decisions about the use of social media through social media ranking results. This decision is reviewed based on several criteria such as length of business, length of use of social media, income and age. The length of business is because the longer the business lasts, the more people will know it. The length of use of social media is because the longer people use social media, the more they understand how to use the features and benefits of the features on social media. The greater the income in the business, the faster the business will develop. If you are at a more ideal age for running a business, your business will develop quickly because you have creative ideas and broad insight into business. The results of the Simple Additive Weighting method research show that WhatsApp has an accuracy value of 0.92, while Telegram has an accuracy value of 0.715. The concrete impact of the results of this research is that social media can help increase sales and the Simple Additive Weighting method can be used as a decision maker in selecting social media as a marketing medium so that Culinary MSMEs do not make the wrong choice in using social media.
ANALISIS PENGARUH METODE PEMBELAJARAN HYBRID TERHADAP TINGKAT KEPUASAN MAHASISWA MENGGUNAKAN ALGORITMA DECISION TREE Nur Helma; Nurhaeni; Ahmad Hidayat; Muhammad Riko Anshori Prasetya
Jurnal Ilmiah Informatika Vol. 10 No. 2 (2025): Jurnal Ilmiah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v10i2.134-144

Abstract

Peralihan dari model pembelajaran konvensional ke digital telah meningkatkan kebutuhan akan metode yang mampu menjaga kualitas pendidikan sekaligus memberikan fleksibilitas. Pembelajaran hybrid, yang menggabungkan pembelajaran tatap muka dan daring, menjadi solusi atas kebutuhan tersebut, namun memerlukan evaluasi berkelanjutan untuk memastikan kepuasan mahasiswa. Penelitian ini bertujuan untuk menganalisis pengaruh metode pembelajaran hybrid terhadap kepuasan mahasiswa di Universitas Sari Mulia serta mengidentifikasi faktor kualitas layanan yang paling berpengaruh. Pendekatan kuantitatif digunakan dengan kuesioner berbasis SERVQUAL yang mencakup lima dimensi, yaitu Tangibles, Reliability, Responsiveness, Assurance, dan Empathy. Data dari 325 responden dianalisis menggunakan algoritma Decision Tree untuk mengklasifikasikan tingkat kepuasan dan mengungkap pola utama. Hasil penelitian menunjukkan bahwa sebagian besar mahasiswa merasa puas, dengan dimensi Assurance dan Reliability sebagai faktor dominan yang memengaruhi kepuasan. Model Decision Tree mencapai tingkat akurasi sebesar 82%, memberikan wawasan yang jelas dan mudah diinterpretasikan mengenai hubungan antara kualitas layanan dan kepuasan mahasiswa. Temuan ini menegaskan bahwa interaksi dosen dan mahasiswa, konsistensi penyampaian materi, serta ketanggapan menjadi aspek penting dalam keberhasilan pembelajaran hybrid. Penelitian ini memberikan kontribusi berupa kerangka berbasis data yang dapat meningkatkan pemahaman institusi terhadap kualitas pembelajaran di era digital. Berbeda dari metode evaluasi tradisional, model yang diusulkan menggabungkan aspek teknologi dan human-centered untuk pendekatan yang lebih komprehensif dalam meningkatkan efektivitas pembelajaran hybrid.