cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Mustakim
Contact Email
officialmalcom.irpi@gmail.com
Phone
+6285275359942
Journal Mail Official
malcom@irpi.or.id
Editorial Address
INSTITUT RISET DAN PUBLIKASI INDONESIA Jl. Tuah Karya Ujung C7. Kel. Tuah Madani Kec. Tampan Kota Pekanbaru - Riau
Location
Kota pekanbaru,
Riau
INDONESIA
Malcom: Indonesian Journal of Machine Learning and Computer Science
Published by Institut Riset dan Publikasi Indonesia
ISSN : 27972313     EISSN : 27758575     DOI : -
Core Subject : Science,
Computer Science & IT
MALCOM: Indonesian Journal of Machine Learning and Computer Science is a scientific journal published by the Institut Riset dan Publikasi Indonesia (IRPI) in collaboration with several Universities throughout Riau and Indonesia. MALCOM will be published 2 (two) times a year, April and October, each edition containing 10 (Ten) articles. Articles may be written in Indonesian or English. articles are original research results with a maximum plagiarism of 15%. Articles submitted to MALCOM will be reviewed by at least 2 (two) reviewers. The submitted article must meet the assessment criteria and in accordance with the instructions and templates provided by MALCOM. The author should upload the Statement of Intellectual/ Copyright Rights when submitting the manuscript. Papers must be submitted via the Open Journal System (OJS) in .doc or .docx format. The entire process until MALCOM is published will be free of charge. MALCOM is registered in National Library with Number International Standard Serial Number (ISSN) Printed: 2797-2313 and Online 2775-8575. Focus and scope of MALCOM includes Data Mining, Data Science, Artificial Intelligence, Computational Intelligence, Natural Language Processing, Big Data Analytic, Computer Vision, Expert System, Text and Web Mining, Parallel Processing, Intelligence System, Decision Support System and Software Engineering
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 418 Documents
 14   15   16   17   18 
Analisis Faktor-faktor Penentu Adopsi E-Wallet di Papua Barat: Extended UTAUT 2 dan Perceived Risk: Analysis of Factors Determining E-Wallet Adoption in West Papua: Extended UTAUT 2 and Perceived Risk Oktavia, Agnes Dwi; Inan, Dedi I.; Wurarah, Rully Novie; Fenetiruma, Obadja A.
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 2 (2024): MALCOM April 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i2.1277

Abstract

E-Wallet merupakan layanan elektronik yang digunakan sebagai tempat penyimpanan data instrumen pembayaran. LinkAja sebagai studi kasus dalam penelitian ini. Tujuan dari penelitian ini adalah mengetahui serta memahami faktor – faktor yang mempengaruhi seseorang untuk mengadopsi penggunaan E-Wallet LinkAja di Provinsi Papua Barat menggunakan model UTAUT 2, persepsi risiko dan control variable yang diukur melalui SEM-PLS. Kuesioner disebar secara online kepada masyarakat Papua Barat. Sebanyak 310 responden yang pernah menggunakan dan pengguna pasti dari aplikasi E-Wallet LinkAja diperoleh dalam penyebaran kuesioner selama satu bulan. Dari hasil penelitian, hubungan antara persepsi risiko dan niat perilaku ditolak, maka persepsi risiko tidak menjadi faktor yang mempengaruhi niat adopsi E-Wallet LinkAja di Papua Barat. Adanya hubungan antara keuntungan , kemudahan, dan pengaruh sosial terhadap niat perilaku serta hubungan antara kondisi yang memfasilitasi, persepsi risiko, dan niat perilaku terhadap niat penggunaan diterima. Maka hubungan variabel tersebut menjadi faktor yang mempengaruhi pengguna memiliki niat untuk menggunakan aplikasi E-Wallet LinkAja di Papua Barat.
Outpacing Competitive Challenges in the Online Market: An Effective Digital Entrepreneurship Approach Diawati, Prety
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 2 (2024): MALCOM April 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i2.1278

Abstract

The online market has become one of the primary battlegrounds for businesses in this digital era. With the increasing use of the internet and the adoption of digital technology, society at large has shifted to online platforms for various activities, including shopping. This research aims to analyze the strategies and factors influencing success in facing the fiercely competitive online market challenges through a digital entrepreneurship approach. The research method employed in this study is a qualitative literature review using Google Scholar as the data source. This study focuses on scholarly articles published between 2013 and 2024. The results of the study indicate that in confronting the fierce and dynamic challenges of the online market, a digital entrepreneurship approach is key to business success. Intense competition and complex consumer dynamics demand business operators to have a deep understanding of the market, as well as the ability to leverage technology and effective marketing strategies. Through in-depth market analysis, personalization, the use of cutting-edge technology, collaboration, consumer engagement, and sustainable innovation, business operators can build resilient and sustainable businesses in this digital era.
The Impact of Digital Transformation on Human Resource Development in the Online Business Paradigm Raharjo, Itot Bian
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 2 (2024): MALCOM April 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i2.1281

Abstract

As digital technology continues to evolve, there is a significant shift from conventional business models towards online business models. This change encompasses various aspects, ranging from how products and services are marketed to interactions with customers. This research aims to understand the influence of digital transformation on Human Resource Development (HRD) in the context of online businesses. The research method employed in this study is a qualitative literature review, drawing data from Google Scholar from 2019 to 2023. The results indicate that in the continuously evolving digital era, digital transformation has become a necessity for every business seeking to survive and thrive, particularly in the realm of online business. HRD is a highly impacted aspect of this transformation. The paradigm shift in HRD development is not only related to technical skills but also to adaptability, continuous learning, and holistic understanding of the online business ecosystem. The urgency of this research is crucial because a deep understanding of how digital transformation affects HRD development can assist organizations and stakeholders in designing effective strategies to address challenges and capitalize on opportunities in this dynamic era of online business.
Analysis of the Interconnection between Digital Skills of Human Resources in SMEs and the Success of Digital Business Strategy Implementation Sutrisno, Sutrisno; Kraugusteeliana, Kraugusteeliana; Syamsuri, Syamsuri
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 2 (2024): MALCOM April 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i2.1282

Abstract

The advancement of information technology has transformed the way SMEs operate, from marketing aspects to inventory management. Digital business opens up new opportunities for SMEs but also demands new skills from human resources to keep up with these developments. The objective of this research is to analyze the interconnection between the digital skills of human resources in SMEs and the success of implementing digital business strategies. This research method focuses on qualitative literature review using Google Scholar as the data source, especially for articles published between 2021 and 2024. The study results indicate that the role of human resources in an increasingly digital business world is crucial. The digital skills possessed by human resources not only affect the effectiveness of implementing digital business strategies but also impact the competitiveness and sustainability of SMEs in the constantly changing market. A deep understanding of the market, creativity in innovation, and adaptability are important factors in ensuring business success in this digital era.
Pengembangan Aplikasi Bunda Care untuk Pemantau Tumbuh Kembang Anak Sebagai Inovasi Antisipatif Penanggulangan Stunting dengan Pendekatan Agile Development: Development of Bunda Care Application for Growth Monitoring Child Growth and Development as an Anticipatory Innovation to Combat Stunting with Agile Development Approach Terttiaavini, Terttiaavini
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 2 (2024): MALCOM April 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i2.1288

Abstract

Sampai saat ini, stunting masih menjadi masalah kesehatan masyarakat yang signifikan, terutama di lingkungan dengan akses terbatas terhadap nutrisi dan perawatan kesehatan. Penelitian ini dilatarbelakangi oleh kebutuhan untuk meningkatkan pemantauan pertumbuhan anak secara efektif. Pusat Kesehatan Masyarakat (Puskesmas) mengalami kesulitan dalam pendataan anak akibat kunjungan untuk pemeriksaan yang tidak teratur, menyebabkan ketidakpastian data dan kesulitan dalam pencegahan stunting. Tujuan penelitian ini adalah untuk mengembangkan aplikasi Bunda Care berbasis Android sebagai alat inovatif untuk memudahkan pemantauan pertumbuhan anak, memberikan informasi edukatif, dan mendorong partisipasi orang tua. Pengembangan aplikasi dilakukan menggunakan metode Agile Development dengan melibatkan pemangku kepentingan dan pengguna akhir untuk memastikan solusi sesuai dengan harapan. Aplikasi Bunda Care berhasil dikembangkan dengan antarmuka pengguna yang ramah, fitur pemantauan pertumbuhan, informasi edukatif, dan notifikasi peringatan. Hasil pengujian black box menunjukkan kinerja positif, sesuai dengan harapan pengguna, dan dapat menjadi solusi inovatif dalam pencegahan stunting.
Analisis Faktor-faktor Pendukung dan Penghambat Beralih Mengadopsi Mobile Banking di Papua Barat Memanfaatkan PLS-SEM dan Perspektif Status Quo Bias: Analysis of Supporting and Inhibiting Factors in Switching to Adopting Mobile Banking in West Papua Utilizing PLS-SEM and Status Quo Bias Perspective Risdiyanto, Cintiya Febiyanti; Inan, Dedi I.; Wurarah, Rully Novie; Fenetiruma, Obadja A.
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 2 (2024): MALCOM April 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i2.1289

Abstract

Mobile banking (m-banking) adalah inovasi teknologi yang bertujuan untuk memfasilitasi transaksi keuangan melalui perangkat mobile, seperti smartphone. Penelitian ini bertujuan untuk menganalisis faktor-faktor pendukung dan penghambat m-banking di Papua Barat memanfaatkan   pendekatan Status Quo Bias. Dua variabel kontrol usia dan gender digunakan untuk memotret demografi responden secara lebih detail. Analisis kuantitatif dilakukan dengan memanfaatkan Partial Least Square – Structural Equation Modelling (PLS-SEM). Sebanyak 303 data responden diperoleh melalui kuesioner online yang disebar kepada masyarakat Papua Barat pengguna aplikasi m-banking selama 1 bulan. Hasil penelitian menunjukan bahwa faktor-faktor perceived value dan sunk cost menunjukan pengaruh yang signifikan terhadap keinginan untuk beralih mengadopsi m-banking. Namun hasil analisis data juga memperlihatkan bahwa faktor-faktor switching benefits dan user resistance menjadi penghambat keinginan untuk mengadopsi m-banking di Papua Barat. Hal ini menggambarkan pengguna merasa membutuhkan banyak usaha untuk membiasakan diri dengan fitur dari layanan m-banking serta kekhawatiran bahwa m-banking menawarkan harapan yang tidak sesuai dengan ekspetasi. Diskusi dan implikasi teoritas dan praktis dari hasil ini juga didiskusikan dalam makalah ini. 
Peningkatan Peningkatan Cakupan Sinyal Wi-Fi dengan Penempatan Access Point Menggunakan Metode Probabilitas Bayesian: Increasing Wi-Fi Signal Coverage with Access Point Placement Using Bayesian Probability Method Linda, Nurhas; Ali, Irsan Taufik
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 2 (2024): MALCOM April 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i2.1291

Abstract

Saat pemasangan jaringan Wi-Fi, posisi Access point merupakan salah satu pengaruh besar terhadap kualitas sinyal  Wi-Fi. Maka, dalam pemasangan alat jaringan diperlukan penempatan Access point yang tepat. Laboraturium Teknik Elektro Universitas Riau merupakan salah satu lokasi yang memanfaatkan jaringan Wi-Fi untuk aktivitas akademik jurusan Teknik Elektro. Namun, penempatan posisi Access point di Laboraturium Teknik Elektor Universitas Riau tidak melalui tahap perencanaan penempatan Access point yang matang dan terdapat penumpukan Access point sehingga cakupan sinyal Wi-Fi di Laboraturium Teknik Elektro Universitas Riau belum optimal. Untuk menyelesaikan permasalahan tersebut, penelitian ini menggunakan metode probabilitas bayesian untuk mengatasi ketidakpastian data dan memerlukan pengetahuan awal untuk mengambil suatu keputusan. Tujuan penelitian ini untuk meningkatkan cakupan sinyal Wi-Fi di Laboraturium Teknik Elektro universitas Riau. Hasil penelitian sebelumnya memiliki luas cakupan sinyal W-Fi sebesar 2,031,04 M2, jika dipersentasekan menjadi 53% dari luas area Laboraturium Teknik Elektro. Setelah dilakukan penelitian terjadi peningkat luas cakupan sinyal Wi-Fi menjadi 3,308,8 M2
Analisa Kepuasan Google Classroom Sebagai Media Pembelajaran Daring Menggunakan Framework PIECES (Kelas RPL): Satisfaction Analysis Google Classroom as an Online Learning Media Using the PIECES Framework (RPL Class) Junaedi, Nanang; Azzahra, Noor Fitria
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 2 (2024): MALCOM April 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i2.1300

Abstract

Kepuasan pengguna sistem informasi adalah tolak ukur baik tidaknya sebuah sistem informasi. Proses pengukuran SI dapat dilakukan dengan banyak cara. Adapun penelitian ini akan menggunakan pengukuran Kepuasan Aplikasi Classroom dengan PIECES Framework, Wabah COVID-19 saat ini memang sudah dinyatakan berakhir oleh pemerintah, tetapi pembelajaran tetap tidak bisa langung dialihkan ke pembelajaran Luring dikarenan jika sewaktu-waktu wabah COVID dengan mutasi baru menyerang maka otomatis pembelajaran akan berhenti lagi, oleh karena itu pembelajaran sekarang menggunakan metode hybrid, dimana melaksanakan secara daring dan luring. Dunia pendidikan pun mengalami imbas yang signifikan sehingga tatap muka dibantu dengan media virtual dan Classrom berperan sebagai sebagai media daring disamping tatap muka di kelas sebagai luringnya. Adapun alasan kami memilih metode ini karena metode ini adalah metode yang paling spesifik dalam mengukur kinerja sebuah sistem informasi. Metode analisa PIECES Framework, yang memiliki beberapa domain atau poin analisa, yakni: Performance, Informations and Data, Economics, Control and Security, Efficiency, and Service, setiap domain analisa adalah referensi yang relevan untuk mengevaluasi dan menganalisa Aplikasi Google Classroom. Hasil dari penelitian ini menunjukkan bahwa Google Classroom adalah media daring yang baik untuk mendukung pembelajaran luring.
Comparative Analysis of Machine Learning Models for Intrusion Detection in Internet of Things Networks Using the RT-IoT2022 Dataset Airlangga, Gregorius
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 2 (2024): MALCOM April 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i2.1304

Abstract

This research investigates the performance of various machine learning models in developing an Intrusion Detection System (IDS) for the complex and evolving security landscape of Internet of Things (IoT) networks. Employing the RT-IoT2022 dataset, which captures a diverse array of IoT devices and attack methodologies, we meticulously evaluated four prominent models: Gradient Boosting, Random Forest, Logistic Regression, and Multi-Layer Perceptron (MLP). Our results indicate that both Gradient Boosting and Random Forest achieved perfect scores with an accuracy, precision, recall, and F1 score of 1.00, suggesting their superior ability to classify and predict security incidents within the dataset. Logistic Regression demonstrated commendable consistency with scores of 0.96 across all metrics, proposing a balance between model complexity and performance. The MLP model closely followed, with an accuracy, precision, recall, and F1 score of 0.99, highlighting its potential in capturing complex, nonlinear data relationships. These findings underscore the critical role of machine learning in fortifying IoT networks against cyber threats and the need for continuous model evaluation against real-world data. The study provides a pathway for future research to refine these IDS models for operational efficiency and sustainability in the dynamic IoT security domain. 
File Encryption and Decryption Using Algorithm Aes-128 Bit Based Website Irwanto, Dola
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 2 (2024): MALCOM April 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i2.1305

Abstract

Digital data security has become very important in the current information era. One way to maintain data security is to use encryption and decryption techniques. The Advanced Encryption Standard (AES) algorithm has been proven effective in protecting data with a high level of security. This research aims to implement the AES-128 bit algorithm for online file encryption and decryption via a website. The method used in this research includes developing a website that provides a user interface for uploading and encrypting files, as well as for decrypting files that have been previously encrypted. The AES-128 bit algorithm is used to carry out the file encryption and decryption process. Users can choose their own encryption key or use a random key generated by the system. The result of this research is a website that can be used to efficiently secure sensitive files using the AES-128 bit algorithm. By using this website, users can easily encrypt the files they want to protect and also decrypt files that have been encrypted previously. The security of user data is guaranteed through the use of strong encryption algorithms and well-managed keys.

Page 16 of 42 | Total Record : 418

 14   15   16   17   18 

Filter by Year

2021 2025


Reset
Filter By Issues
All Issue Vol. 5 No. 4 (2025): MALCOM October 2025 Vol. 5 No. 3 (2025): MALCOM July 2025 Vol. 5 No. 2 (2025): MALCOM April 2025 Vol. 5 No. 1 (2025): MALCOM January 2025 Vol. 4 No. 4 (2024): MALCOM October 2024 Vol. 4 No. 3 (2024): MALCOM July 2024 Vol. 4 No. 2 (2024): MALCOM April 2024 Vol. 4 No. 1 (2024): MALCOM January 2024 Vol. 3 No. 2 (2023): MALCOM October 2023 Vol. 3 No. 1 (2023): MALCOM April 2023 Vol. 2 No. 2 (2022): MALCOM October 2022 Vol. 2 No. 1 (2022): MALCOM April 2022 Vol. 1 No. 2 (2021): MALCOM October 2021 Vol. 1 No. 1 (2021): MALCOM April 2021 More Issue