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All Journal Techno.Com: Jurnal Teknologi Informasi CESS (Journal of Computer Engineering, System and Science) CogITo Smart Journal JURNAL REKAYASA TEKNOLOGI INFORMASI Simtek : Jurnal Sistem Informasi dan Teknik Komputer CSRID (Computer Science Research and Its Development Journal) SENSITEK Jurnal Informasi dan Teknologi Idealis : Indonesia Journal Information System KLIK: Kajian Ilmiah Informatika dan Komputer JUSTIN (Jurnal Sistem dan Teknologi Informasi) Servitium Smart Journal CSRID
Stenly Ibrahim Adam
Fakultas Ilmu Komputer, Universitas Klabat
Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering

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Analysis of User Satisfaction Level of Google Application Classroom Using the ECUS Method Putra, Edson Yahuda; Lahamendu, Irene Gloria; Ngangk, Stivia Yuliefri Lulij; Adam, Stenly Ibrahim; Tangka, George Morris William
CSRID (Computer Science Research and Its Development Journal) Vol. 17 No. 2 (2025): Juni 2025
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.17.2.2025.217-228

Abstract

Despite wide adoption during the COVID‑19 pandemic, Google Classroom’s long‑term acceptance in Indonesian higher education remains under‑examined. This study measures end‑user satisfaction using the five‑factor End‑User Computing Satisfaction (EUCS) framework. A cross‑sectional survey captured 247 valid responses from undergraduate students at Universitas Klabat who had used Google Classroom for at least one semester. Twenty Likert‑scaled items (4 per EUCS dimension) were adapted from Doll & Torkzadeh (1988) and checked for reliability (Cronbach’s α) and validity. Multiple‑linear regression assessed the partial effect of each EUCS factor on overall satisfaction, while descriptive statistics profiled satisfaction levels. Four dimensions—Content (β = 0.299, p < 0.001), Ease of Use (β = 0.268), Format (β = 0.182), and Timeliness (β = 0.222)—significantly predict satisfaction (Adj. R² = 0.682). Accuracy (β = 0.009, p = 0.841) is non‑significant, likely due to low internal consistency (α = 0.429). Overall, 69.6 % of respondents report being satisfied or very satisfied with Google Classroom. Content richness, intuitive interface, presentation quality, and timely feedback drive student satisfaction, whereas perceived accuracy warrants instrument refinement. Findings inform LMS developers and university decision‑makers on prioritised enhancement areas.
Model Random Forest Data Historis Multivariat Untuk Prediksi Pendapatan Asuransi Mokodaser, Wilsen Grivin; Koapaha, Hartiny; Adam, Stenly Ibrahim
IDEALIS : InDonEsiA journaL Information System Vol. 8 No. 2 (2025): Jurnal IDEALIS Juli 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v8i2.3512

Abstract

Perusahaan asuransi adalah perusahaan keuangan non-bank yang melindungi nasabah dari risiko dan mengumpulkan uang dari premi nasabah selama periode tertentu, sesuai dengan ketentuan polis. Karena perusahaan asuransi telah lama terlibat dalam perekonomian negara, masyarakat tidak begitu ragu akan layanan yang mereka tawarkan. Disebabkan oleh ketidakpastian yang terkait dengan hal-hal seperti kesehatan, pendidikan, harta-benda, dan kematian, kesadaran masyarakat tentang pentingnya asuransi terus meningkat. Asuransi menjadi alat penting bagi masyarakat untuk mengantisipasi risiko atau kerugian di masa depan. model Random Forest diterapkan untuk memprediksi pendapatan asuransi bulan berikutnya berdasarkan data historis multivariat dari bulan Januari hingga Juli/Agustus. Hasil evaluasi menunjukkan bahwa model memiliki performa yang cukup baik dalam menangkap pola pendapatan, dengan skor evaluasi Mean Absolute Error (MAE) sebesar ±25.139.426 menunjukkan bahwa rata-rata kesalahan prediksi hanya sekitar 25 juta rupiah, angka yang masih tergolong wajar jika dibandingkan dengan skala pendapatan keseluruhan. Mean Squared Error (MSE) sebesar 2.9815 × 10¹⁵ mencerminkan adanya beberapa error besar, meskipun hal ini wajar mengingat skala data dan keberadaan outlier yang sulit dihindari. R² Score sebesar 0.85 menandakan bahwa 85% variabilitas pendapatan dapat dijelaskan oleh model dari data historis, yang menunjukkan performa prediksi yang sangat baik. Kontribusi ilmiah dari penelitian ini adalah penerapan pendekatan regresi non-linear berbasis Random Forest untuk melakukan peramalan pendapatan asuransi menggunakan data multivariat historis bulanan, yang jarang dibahas secara mendalam dalam konteks industri asuransi. Pendekatan ini tidak hanya menyoroti efektivitas Random Forest dalam menangkap pola musiman dan hubungan non-linier antar variabel waktu, tetapi memberikan landasan eksplorasi metode machine learning lanjutan dalam analisis data asuransi.
IMPLEMENTASI SISTEM REKOMENDASI PRODUK E-COMMERCE MENGGUNAKAN CONTENT-BASED FILTERING BERBASIS COSINE SIMILARITY Adam, Stenly Ibrahim; Mokodaser, Wilsen Grivin
Simtek : jurnal sistem informasi dan teknik komputer Vol. 10 No. 2 (2025): Oktober 2025
Publisher : STMIK Catur Sakti Kendari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51876/simtek.v10i2.1665

Abstract

Pesatnya perkembangan e-commerce menghadirkan tantangan berupa banyaknya pilihan produk yang dapat menimbulkan information overload bagi konsumen. Untuk mengatasi permasalahan tersebut, penelitian ini mengembangkan sistem rekomendasi produk berbasis Content-Based Filtering dengan Cosine Similarity. Metode ini memanfaatkan kombinasi fitur teks (judul dan deskripsi produk) yang direpresentasikan dengan TF-IDF, serta fitur numerik (harga, rating, dan jumlah rating) yang dinormalisasi menggunakan StandardScaler. Selanjutnya, seluruh fitur digabungkan dan dihitung tingkat kesamaannya dengan cosine similarity untuk menghasilkan rekomendasi produk yang relevan. Hasil penelitian menunjukkan bahwa pendekatan ini mampu memberikan rekomendasi yang logis, di mana produk dengan spesifikasi serupa ditampilkan secara berurutan berdasarkan tingkat kesamaan. Analisis tambahan juga memperlihatkan bahwa mayoritas produk memiliki rating tinggi meskipun harga bervariasi, menunjukkan harga bukan satu-satunya indikator kualitas. Dengan demikian, sistem ini terbukti efektif membantu konsumen dalam menemukan produk sesuai preferensi sekaligus memberikan insight bagi pelaku e-commerce.
Analisa Tata Kelola Teknologi Informasi Menggunakan Framework COBIT 2019 Pada Dinas Kominfo Provinsi Sulawesi Utara Mambu, Joe Yuan; Kaligis, Jofan Erlich; Willar, Antares Mario; Adam, Stenly
CESS (Journal of Computer Engineering, System and Science) Vol. 9 No. 2 (2024): July 2024
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v9i2.60904

Abstract

Teknologi Informasi (TI) menjadi esensial dalam operasi bisnis modern, mempengaruhi daya saing, efektivitas, dan efisiensi organisasi. Keberhasilan tata kelola TI terletak pada kesesuaian dengan tujuan organisasi dan adaptasi terhadap perubahan teknologi. COBIT 2019, sebuah framework yang membantu manajemen bisnis dalam mengelola TI, menjadi kunci dalam memandu strategi pengembangan. Penelitian di Dinas Kominfo Sulawesi Utara menemukan tiga proses prioritas: APO12 - Managed Risk, DSS01 - Managed Operations, dan DSS05 - Managed Security Services. Hasil penelitian menunjukkan tingkat kapabilitas dan keefektifan masing-masing proses, dengan APO12 berada pada kapabilitas level 2 dan rating 66%, DSS01 pada level 4 dengan rating 83%, dan DSS05 pada level 2 dengan rating 84%. Evaluasi ini memberikan wawasan yang berharga untuk meningkatkan kinerja dan keamanan TI di institusi tersebut, serta memastikan kontribusi TI yang optimal terhadap tujuan organisasi. Dengan demikian, pemahaman yang mendalam tentang aspek TI yang spesifik dan perannya dalam konteks bisnis lokal menjadi kunci dalam mengambil langkah-langkah yang relevan dan efektif dalam pengelolaan TI.
Pengenalan Teknologi Informasi Untuk Siswa Kelas 1 - 3 di SD Madison School Mobuya Mandias, Green Ferry; Moedjahedy, Jimmy Herawan; Adam, Stenly Ibrahim; Putra, Edson Yahuda; Tombeng, Marchel Timothy
Servitium Smart Journal Vol 4 No 1 (2025): Servitium Smart Journal
Publisher : Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/servitium.v4i1.42

Abstract

This community service activity aims to introduce information technology to students in grades 1 to 3 at SD Madison School Mobuya. Through an interactive workshop approach, students were introduced to information technology tools and basic computer components. A total of 28 students participated in this activity, starting with a pretest to assess their initial understanding of technology. The pretest results showed that 80% of students were not familiar with technological tools and 90% were not familiar with the parts of a computer. After participating in the educational sessions, the posttest results revealed that all students had gained a solid understanding of information technology tools and basic computer components. This activity proves that early introduction to information technology can improve students' understanding of technology and equip them with basic skills needed to face the challenges of the digital world. It is hoped that this activity can be replicated in other schools to broaden the positive impact on the development of technology literacy among students.
Association Pattern Analysis of Global Company Market Capitalization Using the FP-Growth Algorithm with Load Balancing Constraint Adam, Stenly Ibrahim; Pungus, Stenly Richard; Mokodaser, Wilsen Grivin
Techno.Com Vol. 24 No. 4 (2025): November 2025
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v24i4.14885

Abstract

This research focuses on analyzing the global company market capitalization dataset using the FP-Growth algorithm combined with a load-balancing constraint approach. The main objective is to identify association patterns among different market capitalization categories Small, Medium, Large, Mega, and Ultra to understand their distribution and interrelationships. The study begins with data preprocessing, cleaning, and categorization of companies based on their market values. The FP-Growth algorithm is applied with a minimum support threshold of 0.02, and a load balancing constraint is introduced by filtering rules with support ≥ 0.05 and lift > 1, ensuring balanced and significant association patterns. The analysis results show that the most dominant categories are Medium and Small, representing the majority of companies worldwide, while Large, Mega, and Ultra categories are relatively rare. The strongest rule indicates that countries with “Large” companies are very likely to also have “Small” and “Medium” companies. Evaluation metrics show an average lift of 1.171 and an average confidence of 1.000, confirming strong and reliable associations. Overall, this study provides insights into global market capitalization patterns and demonstrates the effectiveness of FP-Growth with constraints in revealing meaningful, balanced relationships within large-scale business data.   Keywords – FP-Growth, Load Balancing Constraint, Market Capitalization, Association.
GreenPoin: Mobile Application with Reward Point System at Klabat University Adam, Stenly Ibrahim; Mokodaser, Wilsen Grivin; Wagiu, Wayne Gilbert
Jurnal Rekayasa Teknologi Informasi (JURTI) Vol 9, No 3 (2025): Jurnal Rekayasa Teknologi Informasi (JURTI)
Publisher : Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/jurti.v9i3.22163

Abstract

At Klabat University, the conventional method of deducting Sabbath points poses challenges for students and supervisors due to its inefficiency. To address this, the GREENPOIN smartphone application was developed as an innovative solution for managing Sabbath points. The application enables administrators to approve point redemptions, add supervisors, manage tasks, and monitor students' total Sabbath points. Students earn points by completing environmental cleaning tasks assigned by supervisors. The system was designed using prototype models and use case diagrams to evaluate user requirements. Key features include Mission Management and Validation for supervisors; Supervisor Management, Point Management, and Point Redemption Approval for administrators; and Login, Registration, Point Viewing, Mission Viewing, Task Submission, Point Redemption, History, and Point Reset for students. GREENPOIN has proven to enhance the efficiency of Sabbath point management, accelerate task validation, and streamline mission oversight. The application increases process transparency and encourages student participation in campus cleanliness initiatives. Future enhancements will include push notifications, an iOS version, mission-specific comments, and API integrations, such as Google Maps, to further improve functionality.
Co-Authors Andrew Lengkong Andrew Tanny Liem Belinda Begre Edson Yahuda Putra Enjelia Tani Ernest Matindas George Morris William Tangka Gerald Varon Alexius Poluan Glainhard Damping Green Ferry Mandias, Green Ferry Inri Pratika Febrili Watung Jimmy H Moedjahedy Jimmy Herawan Moedjahedy Joe Yuan Mambu Kaligis, Jofan Erlich Koapaha, Hartiny Kolibonso, Shyalenn Cerolin Lahamendu, Irene Gloria Mambu, Joe Yuan Yulian Marchel Thimoty Tombeng Mark Jibril Mononutu Marwa , Julius Alfin Melisa Palar Ngangk, Stivia Yuliefri Lulij Oktoverano Lengkong Reymon Rotikan Rinny Cherill Rantung Rolly Junius Lontaan Semmy Wellem Taju Sondakh, Debby Erce Stenly Richard Pungus Supit, Vincent Vian Tenda, Edwin Toetik Wulyatiningsih Tombeng, Marchel Timothy Virgil Steven Weol Wagiu, Wayne Gilbert Willar, Antares Mario Wilsen Grivin Mokodaser