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All Journal Pendas : Jurnah Ilmiah Pendidikan Dasar METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Teknik Informatika UNIKA Santo Thomas Jurnal ULTIMA InfoSys METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Journal of Applied Science, Engineering, Technology, and Education Didaktik : Jurnal Ilmiah PGSD STKIP Subang MEANS (Media Informasi Analisa dan Sistem) Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Pengabdian Pada Masyarakat METHABDI Majalah Ilmiah METHODA Jurnal Pengabdian Masyarakat Bangsa Jurnal Rekayasa Sistem Informasi dan Teknologi Jurnal Ilmiah Ekonomi dan Manajemen JURNAL RUMPUN MANAJEMEN DAN EKONOMI Escalate : Economics and Business Journal JURNAL AKADEMIK EKONOMI DAN MANAJEMEN Manajemen : Jurnal Ekonomi Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Ekonomi, Manajemen Pariwisata dan Perhotelan Eduvista: Journal of Education and Innovation Societa: Journal of Society and Change
Darwis Robinson Manalu
Universitas Methodist Indonesia
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Beyond assignment deadlines: Explaining academic stress through deadline behavior among university students Susi Juniarti Pardosi; Darwis Robinson Manalu
Eduvista: Journal of Education and Innovation Vol. 1 No. 1 (2026): Eduvista: Journal of Education and Innovation
Publisher : PT Bina Perfidia Akademia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67964/h029d512

Abstract

Deadline behavior, defined as the habit of completing academic assignments close to submission deadlines, is presumed to contribute to higher levels of academic stress among university students; however, empirical evidence specifically examining this relationship remains limited. This study aimed to analyze the effect of deadline behavior on academic stress among students at Universitas Methodist Indonesia. A quantitative associative design was employed involving 100 undergraduate students who completed a five-point Likert-scale questionnaire. The data were analyzed using simple linear regression with IBM SPSS Statistics 22. The findings revealed that deadline behavior had a positive and significant effect on academic stress (B = 0.278; t = 4.082; p < 0.001). The coefficient of determination (R² = 0.145) indicates that deadline behavior explained 14.5% of the variance in academic stress, while the remaining variance was influenced by factors outside the proposed model. These findings highlight the importance of effective time management as a preventive strategy for reducing academic stress and contribute to the growing literature on academic behavior in higher education. Abstrak Kebiasaan mengerjakan tugas mendekati batas waktu (deadline behavior) diduga menjadi salah satu penyebab meningkatnya stres akademik mahasiswa, namun penelitian yang secara khusus menguji pengaruh perilaku tersebut terhadap tingkat stres masih relatif terbatas. Penelitian ini bertujuan menganalisis pengaruh deadline behavior terhadap tingkat stres mahasiswa di Universitas Methodist Indonesia. Penelitian menggunakan pendekatan kuantitatif dengan desain asosiatif yang melibatkan 100 mahasiswa melalui penyebaran kuesioner skala Likert lima poin. Data dianalisis menggunakan regresi linear sederhana dengan bantuan IBM SPSS Statistics 22. Hasil penelitian menunjukkan bahwa deadline behavior berpengaruh positif dan signifikan terhadap tingkat stres akademik (B = 0,278; t = 4,082; p < 0,001). Nilai koefisien determinasi (R² = 0,145) menunjukkan bahwa deadline behavior menjelaskan 14,5% variasi tingkat stres akademik, sedangkan sisanya dipengaruhi oleh faktor lain di luar model penelitian. Temuan ini menegaskan pentingnya pengelolaan waktu sebagai strategi preventif dalam menekan stres akademik mahasiswa sekaligus memperkaya kajian mengenai perilaku akademik di pendidikan tinggi.
Hubungan Intensitas Penggunaan Gadget dengan Produktivitas Belajar Mahasiswa Anastasya Silaban, Erfina; Robinson Manalu, Darwis
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 11 No. 03 (2026): Volume 11 Nomor 03, September 2026 Public
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i03.60473

Abstract

Advancements in digital technology have made devices crucial tools for university students' learning activities. However, how an individual utilizes these devices can influence learning outcomes—either enhancing or diminishing quality—depending on the purpose and method of use. This study aims to assess how students at the Indonesian Methodist University utilize devices to boost their learning productivity. The research employs a quantitative method and a correlational approach, surveying 102 active students selected via convenience sampling. Data were collected using a questionnaire based on a five-point Likert scale and subsequently analyzed using IBM SPSS software. The analysis included validity and reliability testing, descriptive statistics, normality testing, simple linear regression, the coefficient of determination, and t-tests. The results indicate a positive and significant relationship between the frequency of device usage and student learning productivity, with a significance value of 0.001.
Mapping digital song popularity characteristics as a foundation for popular song identification in society Viona Anjani Greit Lumban Toruan; Darwis Robinson Manalu
Societa: Journal of Society and Change Vol. 1 No. 1 (2026): Societa: Journal of Society and Change
Publisher : PT Bina Perfidia Akademia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67964/0q2w1e65

Abstract

Song popularity on digital platforms has increasingly influenced public music preferences. However, differences in popularity metrics across Spotify, YouTube, and TikTok have resulted in fragmented approaches to identifying popular songs, preventing a comprehensive representation of song popularity. This study aims to identify song popularity characteristics by integrating cross-platform popularity metrics using the K-Means clustering algorithm. A quantitative approach was employed using primary data collected from questionnaires administered to 71 respondents and secondary data consisting of 500 songs selected from the Most Streamed Spotify Songs 2024 dataset. The data were analyzed using Z-transformation normalization and the K-Means clustering algorithm. The findings identified three principal popularity characteristics—Low Popular, Viral Popular, and Stable Popular—demonstrating that TikTok virality does not necessarily reflect overall song popularity across digital platforms. This study contributes by proposing a conceptual framework for Popular Song Identification based on the integration of cross-platform popularity metrics, offering a more comprehensive approach to identifying popular songs for society, the digital music industry, and the development of music recommendation systems. Abstrak Popularitas lagu pada platform digital semakin memengaruhi preferensi musik masyarakat. Namun, perbedaan metrik popularitas pada Spotify, YouTube, dan TikTok menyebabkan identifikasi lagu populer masih dilakukan secara parsial sehingga belum mampu merepresentasikan popularitas lagu secara menyeluruh. Penelitian ini bertujuan mengidentifikasi karakteristik popularitas lagu melalui integrasi metrik lintas platform menggunakan algoritma K-Means Clustering. Penelitian menggunakan pendekatan kuantitatif dengan data primer berupa kuesioner yang melibatkan 71 responden dan data sekunder berupa 500 lagu yang dipilih dari dataset Most Streamed Spotify Songs 2024. Data dianalisis menggunakan normalisasi Z-Transformation dan algoritma K-Means Clustering. Hasil penelitian mengidentifikasi tiga karakteristik utama popularitas, yaitu Low Popular, Viral Popular, dan Stable Popular, serta membuktikan bahwa viralitas TikTok tidak selalu merepresentasikan popularitas lagu secara menyeluruh. Penelitian ini berkontribusi melalui pengembangan kerangka konseptual Popular Song Identification berbasis integrasi metrik popularitas lintas platform sehingga menawarkan pendekatan yang lebih komprehensif dalam mengidentifikasi lagu populer bagi masyarakat, industri musik digital, dan pengembangan sistem rekomendasi musik.
Building user trust in the digital society: The influence of perceived data security on the DANA digital wallet application Jenny Karunia Putri Zai; Darwis Robinson Manalu
Societa: Journal of Society and Change Vol. 1 No. 1 (2026): Societa: Journal of Society and Change
Publisher : PT Bina Perfidia Akademia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67964/xekh4n76

Abstract

The rapid adoption of digital wallets within society has intensified concerns regarding data security. However, previous studies examining the influence of perceived data security on user trust have primarily focused on statistical relationships without explaining the conceptual mechanism underlying trust formation. This study aims to examine the influence of perceived data security on user trust in the DANA digital wallet application. A quantitative approach employing simple linear regression was conducted using questionnaire data collected from 75 DANA users at Methodist University of Indonesia through a five-point Likert scale. The findings reveal that perceived data security has a positive and statistically significant effect on user trust (R² = 0.738; t = 14.343; p < 0.001), indicating that stronger perceptions of data security lead to higher levels of user trust in digital financial services. This study contributes by proposing a conceptual framework that explains the trust formation process while providing practical recommendations for digital wallet providers to strengthen security systems and enhance public trust in digital transactions. Abstrak Pesatnya penggunaan dompet digital di masyarakat meningkatkan kebutuhan akan keamanan data, namun penelitian mengenai pengaruh persepsi keamanan data terhadap kepercayaan pengguna masih terbatas pada hubungan statistik dan belum menjelaskan mekanisme konseptual pembentukan kepercayaan. Penelitian ini bertujuan menganalisis pengaruh persepsi keamanan data terhadap kepercayaan pengguna aplikasi DANA. Penelitian ini menggunakan pendekatan kuantitatif dengan analisis regresi linear sederhana terhadap 75 mahasiswa pengguna DANA di Universitas Methodist Indonesia melalui kuesioner berbasis skala Likert. Hasil penelitian menunjukkan bahwa persepsi keamanan data berpengaruh positif dan signifikan terhadap kepercayaan pengguna (R² = 0,738; t = 14,343; p < 0,001), yang mengindikasikan bahwa semakin tinggi persepsi keamanan, semakin tinggi pula tingkat kepercayaan pengguna dalam memanfaatkan layanan keuangan digital. Penelitian ini berkontribusi dengan menawarkan kerangka konseptual yang menjelaskan proses pembentukan kepercayaan pengguna serta memberikan rekomendasi bagi penyedia layanan untuk memperkuat keamanan sistem dan meningkatkan kepercayaan masyarakat terhadap transaksi digital.
Toward a secure digital society: The influence of digital security awareness on students' personal data protection behavior Lucia Apria; Darwis Robinson Manalu
Societa: Journal of Society and Change Vol. 1 No. 1 (2026): Societa: Journal of Society and Change
Publisher : PT Bina Perfidia Akademia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67964/j4qnz139

Abstract

The growth of the digital society has increased technology use while simultaneously amplifying the risk of personal data breaches, yet the relationship between digital security awareness and personal data protection behavior among university students remains underexplored. This study aimed to examine the influence of digital security awareness on the personal data protection behavior of students at Universitas Methodist Indonesia. A quantitative causal-associative approach was employed involving 102 respondents selected through convenience sampling, with data collected using questionnaires and analyzed through simple linear regression. The findings revealed that digital security awareness had a positive and significant effect on personal data protection behavior (B = 0.621; t = 9.876; p < 0.001) and explained 49.4% of the behavioral variance (R² = 0.494). These findings highlight that strengthening digital security awareness is fundamental to fostering personal data protection behavior and provides empirical support for enhancing cybersecurity literacy initiatives within the digital society. Abstrak Perkembangan masyarakat digital meningkatkan intensitas penggunaan teknologi sekaligus memperbesar risiko kebocoran data pribadi. Namun, hubungan antara kesadaran keamanan digital dan perilaku perlindungan data pribadi mahasiswa masih belum banyak dikaji secara empiris. Penelitian ini bertujuan untuk menganalisis pengaruh kesadaran keamanan digital terhadap perilaku perlindungan data pribadi mahasiswa Universitas Methodist Indonesia. Penelitian ini menggunakan pendekatan kuantitatif dengan desain asosiatif kausal terhadap 102 responden yang dipilih melalui teknik convenience sampling. Data dikumpulkan menggunakan kuesioner dan dianalisis menggunakan regresi linear sederhana. Hasil penelitian menunjukkan bahwa kesadaran keamanan digital berpengaruh positif dan signifikan terhadap perilaku perlindungan data pribadi (B = 0,621; t = 9,876; p < 0,001), dengan kemampuan menjelaskan 49,4% variasi perilaku (R² = 0,494). Temuan ini menegaskan bahwa peningkatan kesadaran keamanan digital merupakan fondasi penting dalam membentuk perilaku perlindungan data pribadi serta memperkuat upaya pengembangan literasi keamanan siber di era masyarakat digital.
Analisis Pola Pembelian Menu Coffee Shop Menggunakan Algoritma FP-Growth sebagai Dasar Rekomendasi Menu pada Sistem Kasir Martianova Lusia Sihombing; Marchel Hamonangan Ritonga; Darwis Robinson Manalu
Jurnal Ilmu Komputer dan Teknologi Informasi Vol. 3 No. 2 (2026): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jikti.v3i2.1960

Abstract

Transaction data in cash register systems has the potential to serve not only as sales records but also to identify customer purchasing patterns that can support business decision-making. Unfortunately, the utilization of transaction data in coffee shops is often limited to sales reports, resulting in suboptimal use of the relationships between menu items. This study aims to analyze menu purchasing patterns using the Frequent Pattern Growth (FP-Growth) algorithm and to interpret the resulting association rules as a basis for menu recommendations in the cash register system. Employing a quantitative approach and descriptive methods, this research analyzes the public dataset The Bread Basket, which contains over 9,000 transactions. Data preprocessing was conducted using RapidMiner Studio through attribute selection and transformation stages. The FP-Growth algorithm was applied with a minimum support parameter of 5% and a minimum confidence of 20%, yielding two association rules: Bread → Coffee and Cake → Coffee. The Cake → Coffee rule demonstrates a positive relationship with a support value of 0.055 and confidence of 0.527, while Bread → Coffee does not indicate a positive association despite having a higher support value. These findings suggest that the FP-Growth algorithm is effective in identifying purchasing patterns that support menu recommendation logic.
Implementasi Sistem Pendukung Keputusan untuk Penentuan Pola Belajar Mahasiswa Berbasis Web Menggunakan Metode Simple Additive Weighting (SAW) Elvi Dewi Purnama Sari Simanjuntak; Darwis Robinson Manalu
Jurnal Rekayasa Sistem Informasi dan Teknologi Vol. 4 No. 1 (2026): Agustus
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70248/jrsit.v4i1.4082

Abstract

Sistem Pendukung Keputusan (SPK) merupakan solusi berbasis komputer yang membantu pengambilan keputusan pada permasalahan semi-terstruktur, termasuk penentuan pola belajar mahasiswa yang selama ini masih dilakukan secara subjektif. Penelitian ini mengimplementasikan metode Simple Additive Weighting (SAW) ke dalam sistem berbasis web untuk menentukan pola belajar 98 mahasiswa aktif Program Studi Sistem Informasi Universitas Methodist Indonesia (Semester 2, 4, dan 6) berdasarkan tiga kriteria: Tingkat Konsentrasi (C1, bobot 40%, benefit), Waktu Luang Belajar (C2, bobot 35%, benefit), dan Tingkat Kelelahan (C3, bobot 25%, cost). Data kuesioner Skala Likert (1–5) diuji validitasnya menggunakan korelasi item-total dan reliabilitasnya menggunakan Cronbach’s Alpha, menunjukkan seluruh butir valid (r hitung > r tabel = 0,199) dengan reliabilitas baik pada kriteria Waktu Luang (α = 0,822) dan Kelelahan (α = 0,800), serta cukup pada Konsentrasi (α = 0,502). Tahapan SAW meliputi pembentukan matriks keputusan, normalisasi, dan perhitungan nilai preferensi (Vi); sistem diverifikasi melalui Black-Box Testing (Equivalence Partitioning) dan dilengkapi instrumen System Usability Scale (SUS) untuk pengujian lanjutan. Hasil menunjukkan 55 mahasiswa (56,12%) berkategori Baik dan 43 mahasiswa (43,88%) berkategori Cukup, dengan nilai SAW tertinggi diraih Cory Debora (Vi = 0,8708) dari Semester 4. Kontribusi utama penelitian ini adalah SPK berbasis web yang mengintegrasikan tiga kriteria perilaku belajar secara real-time dengan instrumen teruji validitas dan reliabilitasnya, sehingga rekomendasi pola belajar yang dihasilkan lebih objektif, transparan, cepat, dan dapat dipertanggungjawabkan secara kuantitatif.
Pengaruh Kepuasan Kerja terhadap Produktivitas Kerja Karyawan Chindy Salim; Darwis Robinson Manalu
Jurnal Ekonomi, Manajemen Pariwisata dan Perhotelan Vol. 5 No. 3 (2026): Jurnal Ekonomi, Manajemen Pariwisata dan Perhotelan
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jempper.v5i3.8084

Abstract

This study aims to analyze the influence of job satisfaction on employee productivity through the literature review method. A total of 15 articles obtained from Google Scholar were analyzed based on relevance to the research topic. The results of the study showed that 13 studies found a significant influence of job satisfaction on productivity, while 2 studies stated that there was no significant influence. In general, job satisfaction is closely related to employee productivity, although the relationship is not singular and is influenced by other factors such as motivation, work environment, compensation, workload, and work-life balance. This finding confirms that job satisfaction is one of the important determinants in increasing productivity, but its effectiveness depends on synergy with other supporting variables. Thus, organizations need to pay attention to the aspect of job satisfaction comprehensively through human resource management policies that are oriented towards employee welfare, increased motivation, and the creation of a conducive work environment. This research makes a theoretical contribution in strengthening the understanding of the relationship between job satisfaction and productivity, as well as providing practical implications for the development of sustainable employee management strategies.
ANALISIS SENTIMEN PUBLIK TERHADAP KABINET MERAH PUTIH PADA APLIKASI X DENGAN METODE BIDIRECTIONAL ENCODER REPRESENTATION FROM TRANSFORMER Darwis Robinson Manalu; Jusup Sihotang; Edward Rajagukguk
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 12 No. 2 (2026): Volume 12 Nomor 2 Tahun 2026
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v12i2.5580

Abstract

The X application has become a platform for Indonesians to express their opinions, including those related to the Kabinet Merah Putih. This study aims to analyze public sentiment on the X application regarding the Kabinet Merah Putih using the IndoBERT method. A total of 1944 tweets were collected from the X platform using the keyword “Kabinet Merah Putih”, then processed through preprocessing stages including cleaning, normalization, case folding, and stopword removal, automatic labeling with TextBlob, and data division for model training and testing. The finetuned IndoBERT model was used to classify sentiment into positive, negative, and neutral. The results of the study show that public sentiment is dominated by positive and neutral sentiments, while IndoBERT's performance shows good accuracy in sentiment classification, with a model accuracy value of 85.96%, precision of 75%, recall of 74%, and F1-Score of 74%. This study provides an objective picture of public perception of the Kabinet Merah Putih on the X application and is expected to serve as evaluation material for the government.
Co-Authors Adam Jordie Sinulingga Agus Syahputra Alfonso Pareandos Sitorus Anastasya Silaban, Erfina Apriandi, Virgiawan Bayu Aprodegreselia Tarigan Ari Kartanto Sinuhaji Asokhiwa Zega Ayler Beniah Ndraha Azelia Sarah Dwi Artha Chindy Salim Cosmas Tambunan Cristina Adelia Putri Silaban DEWI SARTIKA Dian Eka Matra Putra Bangun Doli Hasibuan Dwiyanto . Dyah Faramida Octaviani Lubis Edward Rajagukguk Eka Samuel P. Hutasoit Elisati Kurniawan Telaumbanua ELIYUNUS WARUWU Eliza, Agnes Lasmaria Elsya Secilia Margaretha Elvi Dewi Purnama Sari Simanjuntak Ester Agnesya Nainggolan Eva Julia Gunawati Harianja Fati Gratianus Nafiri Larosa Feruche, Melani Gea, Asaziduhu Gortap Lumbantoruan Grasella Prescillia Pangaribuan Gresa Simarmata Guellica Agnesia Claudia Thanos Harianja, Eva Julia G. Harlen Gilbert Manullang Hasibuan, Doli Henri Yosua Pangihutan Humuntal Rumapea Hutapea, Marlyna I. Hutasoit, Eka Samuel P Hutasoit, Elfhian Goklas Pangihutan Ijonris, Yusuf Indra Kelana Jaya Indra M. Sarkis S. Intan Nurrachmi Jamaluddin Jamaluddin Jamaluddin Jenny Karunia Putri Zai Jeremia Sebayang Jhon Kristopel Manalu Jhoni Maslan Jhoni Maslan, Jhoni Jimmy F. Naibaho Junika Napitupulu Jusup Sihotang Larosa, Fati G. N. Lase, Delipiter Lestari Natalia Br Sianipar Lucia Apria Lumbanraja, Posma Manalu, Jhon Kristopel Marchel Hamonangan Ritonga Margaretha Yohanna Marihot Gultom Mario Christofell L. Tobing Marlyna I Hutapea Martianova Lusia Sihombing Marzuki, Sinambela Melani Feruche Melisa Aulina Sihite Mendarissan Aritonang Merry Anna Napitupulu Mufria J. Purba Nabila Amanda Nainggolan, Rena Ndruru, Yufita Friska Nehemia Christian Boy Nettina Samosir Octania Togatorop Ofelius Laia Paska Marto Hasugian Perangin-angin , Resianta Posma Lumbanraja Prawita Simarmata Purba, Eviyanti N. Purba, Eviyanti Novita Putra Palipi Rajagukguk, Edward Rajagukguk, Yosia Suhendri Remus Silalahi Rena Nainggolan Resianta Perangin-Angin Rijois I. E Saragih Rijois I. E. Saragih Rikshintia Panjaitan Rimbun Siringoringo Rio J P Saragih Robbi Rahim Rumahorbo, Benget Rumapea, Anastasia Erika Rumapea, Yolanda Y. P. rumapea, yolanda yulianti pratiwi Rumapea, Yolanda Yuliati Pratiwi Samosir, Nettina Samosir, Refani Abednego Samosir, Yosafat Renovaldo Samuel Van Basten Halomoan Manurung Samuel VB Manurung Sarkis, Indra M. Silaban, Cristina Adelia Putri Silalahi, Arina Prima Silitonga, Arino Fanther Simanullang, Febri Yanti Simanullang, Harlen Gilbert Simanullang, Sanco Simatupang, Wilson Simbolon, Mangantar Sitorus, Betti Elvi Deliana Sri Agustina Rumapea Sunardi Sunardi Surianto Sitepu Susi Juniarti Pardosi Syamsu Rijal Telaumbanua, Elisati Kurniawan Toong Hai Sam Viona Anjani Greit Lumban Toruan Yksan Naibaho Yohanna, Margaretha Yolanda Y. P. Rumapea Yolanda Y.P Rumapea yolanda yulianti pratiwi rumapea Yuaniko Paramitra