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INSTITUT RISET DAN PUBLIKASI INDONESIA Jl. Tuah Karya Ujung C7. Kel. Tuah Madani Kec. Tampan Kota Pekanbaru - Riau
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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
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Analisis Sentimen Opini Publik pada Twitter Terhadap Bank BSI Menggunakan Algoritma Machine Learning: Sentiment Analysis of Public Opinion on Twitter Toward BSI Bank Using Machine Learning Algorithms Ratna Andini Husen; Rizki Astuti; Lili Marlia; Rahmaddeni Rahmaddeni; Lusiana Efrizoni
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 3 No. 2 (2023): MALCOM October 2023
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v3i2.901

Abstract

Opini publik yang terekspresikan melalui media sosial, khususnya Twitter, telah menjadi sumber informasi yang penting bagi perusahaan dan lembaga keuangan, termasuk Bank BSI. Analisis sentimen opini publik dapat membantu Bank BSI dalam memahami pandangan dan persepsi masyarakat terhadap layanan mereka. Penelitian ini bertujuan untuk mengembangkan dan mengimplementasikan algoritma machine learning yaitu algoritma SVM, naïve bayes dan logistic regression untuk menganalisis sentimen opini publik terhadap Bank BSI yang terdapat dalam tweet di Twitter. Data tweet yang digunakan dalam penelitian ini diambil situs dari kaggle dengan jumlah data 24.401, berisi tentang ulasan komentar pengguna terkait ransomware pada Bank BSI. Hasil dari percobaan yang telah dilakukan diperoleh bahwa SVM menghasilkan akurasi 0,88%, naive bayes menghasilkan akurasi 0,76%, dan logistic regression menghasilkan akurasi 0,86%. Berdasarkan dari hasil percobaan bahwa SVM mendapatkan performa kinerja yang lebih unggul dari pada algoritma naive bayes dan logistic regression . Dalam konteks ini, SVM dapat menjadi pilihan yang baik untuk analisis sentimen secara umum. Penelitian ini mengungkapkan bahwa persentase sentimen negatif terhadap Bank BSI lebih tinggi daripada sentimen positif. Temuan ini menunjukkan adanya keprihatinan dan ketidakpuasan yang signifikan di antara masyarakat terhadap layanan perusahaan. Meskipun ada beberapa sentimen positif yang teridentifikasi.
Determining the Final Project Topic Based on the Courses Taken by Using Machine Learning Techniques Vicky Salsadilla; Inggih Permana; Muhammad Jazman; M. Afdal
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 3 No. 2 (2023): MALCOM October 2023
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v3i2.904

Abstract

A thesis (TA) is a scientific paper based on a problem. TA must be completed by students who wish to complete their studies. During this time, students often experience difficulties in determining the TA topic they want to research. To fix it, this research tries to determine TA topics using Machine Learning (ML) techniques based on the elective courses that students have taken. Elective courses are one form of academic data that can be used to consider TA topics. The ML algorithms used are KNN, NBC, ANN, SVM, C4.5, Random Forest, and Logistic Regression. The dataset used in this research is imbalanced data. This research balances the data using the Random Oversampling method and the Random Undersampling method. The results of experiments show that datasets balanced using ROS produce much higher ML performance, but tend to over-fit due to data duplication in the dataset. If the dataset is not balanced at all then the ML performance will be very low. Therefore, for unbalanced data, it is recommended to use the RUS method as data balance. The highest accuracy results for algorithms balanced using ROS are ANN=69.7%, RF=66.7%, SVM=57.6%, LR=57.6%, NBC=42.4%, C4.5=42.4%, and KNN=33.3%
Rancang Bangun Sistem Monitoring Bandwidth Server pada PT. Industri Kreatif Digital: Design and Build of Server Bandwidth Monitoring System at PT. Industri Kreatif Digital Linna Oktaviana Sari; Hazline Atika Suri; Ery Safrianti; Feranita Jalil
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 3 No. 2 (2023): MALCOM October 2023
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v3i2.914

Abstract

Bandwidth merupakan salah satu hal yang sangat penting dan harus diperhatikan serta dijaga kestabilan operasionalnya. Untuk menjaga jaringan yang stabil, diperlukan pengalokasian bandwidth. Pengalokasian bandwidth memerlukan informasi terkait kapan saja jam sibuk yang terjadi di PT. Industri Kreatif Digital (PT. IKADA), maka dibutuhkan monitoring pada bandwidth server. Proses pemantauan bandwidth server yang dilakukan PT. IKADA belum optimal menyebabkan jaringan yang tidak stabil dikarenakan pembagian bandwidth yang tidak merata. Pengunduhan aplikasi atau file dalam kapasitas yang besar juga dapat menyebabkan gangguan pada pengguna lain yang sedang melakukan pekerjaannya. Maka diperlukan sistem monitoring bandwidth server untuk dapat memonitor dan mengontrol kapasitas penggunaan bandwidth dari server, apabila penelitian ini tidak selesai, maka PT. IKADA tetap dapat memonitor bandwidth seperti sebelumnya. Berdasarkan permasalahan yang telah diuraikan, diperlukan suatu sistem yang memonitoring kapasitas bandwidth guna mempermudah divisi Network Operation Center untuk mengetahui kapastitas bandwidth yang digunakan apakah sesuai atau tidak, maka dalam penelitian ini, akan dibangun Sistem Monitoring Bandwidth Server. Sistem ini akan dibangun dengan menggunakan PHP sebagai bahasa pemrograman dan MySQL sebagai database manajemen. Berdasarkan pengujian yang telah dilakukan dengan menggunakan metode Blackbox Testing dan Whitebox Testing. Dapat disimpulkan bahwa sistem monitoring ini telah berhasil dibuat dan telah sesuai dengan kebutuhan dari PT. IKADA.
Analysis of The Influence of Brand Image, Digital Marketing and Product Knowledge on Customers Purchase Intention of Banking Products Febri Sari Siahaan; Irma M. Nawangwulan; Hari Setia Putra; Samuel PD Anantadjaya; Sukma Irdiana
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 3 No. 2 (2023): MALCOM October 2023
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v3i2.917

Abstract

The purpose of this study is to determine whether there is a simultaneous relationship between digital marketing, brand image, and product understanding on the decision to become a customer. In this study, the population consists of all Sharia bank customers. With a total of 100 respondents, this study used a non-probability sampling strategy. This study employs a quantitative methodology and a causal research design, gathering information with a questionnaire. The decision to become a customer was found to be significantly influenced in a good way by digital marketing, according to the research findings. This indicates that the decision to become a customer can be influenced by digital marketing. The more effectively digital marketing is implemented, the more it will persuade consumers to become clients. The decision to become a customer is positively and significantly influenced by brand image. This implies that the decision to become a customer may be influenced by brand image. Making the choice to become a customer will be simpler the more positively the brand is portrayed. The decision to become a customer is positively and significantly impacted by product knowledge. This implies that product expertise can affect a potential customer's choice to buy.
Analysis of The Influence of Financial Literacy Digitalization, Digital Word of Mouth, Digital Marketing and Brand Image on Z's Generation Saving Intention in Sharia Banking Rini Hadiyati; Budi Harto; Dhiana Ekowati; Jefriyanto Jefriyanto; Sonny Santosa
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 3 No. 2 (2023): MALCOM October 2023
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v3i2.918

Abstract

This study aims to ascertain the ways in which Generation Z's interest in Sharia banking is influenced by digital marketing, word-of-mouth, brand image, and financial literacy. Students were the research population used in this study. Purposive sampling and non-probability sampling, totaling 400, were the methods used in this study's sample strategy. By distributing questionnaires, this study employed a quantitative methodology. Using SPSS version 23.0, the acquired data was examined for data quality. Next, statistical data will be analyzed using the Partial Least Square (PLS) variance-based structural equation model. The findings of this study indicate that The interest of Generation Z in Sharia banking is influenced by financial literacy. The findings of this study indicate that interest in Sharia banking among Generation Z is influenced by digital marketing. According to the study's findings, Generation Z's interest in Sharia banking is influenced by brand perception. Based on the research findings, Generation Z's interest in Sharia banking is influenced by word of mouth.
Analysis of The Influence of E-Commerce Use and Digital Literacy Toward Society Intention in Digital Entrepreneurship Nur Augus Fahmi; Zulkifli Zulkifli; Tito Irwanto; Apit Fathurohman; I Wayan Adi Pratama
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 3 No. 2 (2023): MALCOM October 2023
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v3i2.919

Abstract

The purpose of this study is to examine the relationship between students' interest in digital entrepreneurship and their use of digital literacy and e-commerce. Quantitative research is the method used in this study. This study uses correlational data collection methods. In this study, questionnaires are used to collect the data. In the questionnaire method, the validity and reliability of the questionnaire will be examined in advance. Data processing will be done using statistical methods after data collecting is finished. To use multiple regression analysis to examine the impact of each variable. Students make up the study's population. With a sample size of 200 participants, the researchers used a basic random sampling procedure. According to the study's findings, students' interest in digital entrepreneurship was positively impacted by their level of digital literacy. Students' interest in digital entrepreneurship is positively impacted by the use of e-commerce. The use of e-commerce and digital literacy both increase students' interest in digital entrepreneurship.
Analisis Pemodelan Data Flow Diagram pada Sistem Basis Data Wisata Kuliner di Kota Balikpapan: Analysis of Data Flow Diagram on Culinary Tourism Database System in Balikpapan City Luh Made Wisnu Satyaninggrat; Prasis Damai Nursyam Hamijaya; Khairunnisa Rahmah
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 3 No. 2 (2023): MALCOM October 2023
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v3i2.920

Abstract

Kuliner merupakan suatu hal yang tak terpisahkan bagi wisatawan yang mengunjungi suatu daerah dan dapat menjadi sarana strategi pemasaran keunikan suatu daerah. Namun pada proses perolehan informasi kuliner yang ada di wilayah Balikpapan masih cukup sukar untuk ditemukan. Terdapat beberapa kesulitan yang mungkin ditemui oleh wisatawan, yaitu terbatasnya informasi kuliner Balikpapan secara online, perbedaan bahasa yang digunakan seperti penggunaan bahasa daerah, lokasi kuliner yang sulit dijangkau, serta sulitnya mengetahui menu-menu yang paling populer dan tempat-tempat kuliner terkenal. Dalam mengatasi permasalahan tersebut, biasanya wisatawan mencari informasi berdasarkan sumber-sumber secara online. Namun hal tersebut dinilai kurang efektif dan membutuhkan waktu yang lebih banyak. Sehingga tim peneliti mengusungkan agar dapat dilakukan pembuatan database Wisata Kuliner agar dapat memudahkan para wisatawan. Penelitian ini dilakukan dengan menganalisis dan mengidentifikasi basis data wisata kuliner yang kemudian ditinjau berdasarkan kebutuhan wisatawan dan pelaku usaha. Hasil yang diperoleh berdasarkan penelitian ini yaitu berupa pemodelan Data Flow Diagram (DFD) sistem basis data wisata kuliner yang terbagi atas beberapa level yaitu 0, 1, 2, dan 3. Selain itu setiap fitur yang ada akan diidentifikasi berdasarkan 2 aktor yaitu pelaku usaha dan juga penikmat kuliner.
ChatGPT's Role in Transforming Employee Recruitment and Selection Processes Itot Bian Raharjo
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 3 No. 2 (2023): MALCOM October 2023
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v3i2.921

Abstract

Employee recruitment and selection is a key process in human resource management that plays an important role in the success of an organisation. This process involves the search, evaluation and selection of individuals who have the qualifications and potential that match the needs of the organisation. One of the significant changes that has transformed the employee recruitment and selection paradigm is the advent of advanced technologies such as ChatGPT. This research aims to analyse the role of ChatGPT in the transformation of the employee recruitment and selection process. The method used is a qualitative literature review that focuses on an in-depth understanding of the topic in the time span from 2018 to 2023. The main objective of this method is to identify, analyse, and synthesise relevant scientific literature that has been published in various journals, conference papers, and other academic sources accessible through Google Scholar. The study results show that the use of ChatGPT in the transformation of employee recruitment and selection processes is a significant step towards higher efficiency and effectiveness in human resource management. However, we must remain cautious in the face of emerging impacts and challenges. 
Alat Kontrol dan Pengaman Sepeda Motor Menggunakan ESP 32 Cam Berbasis Telegram untuk Meminimalisasi Pencurian: Motorbike Control and Safety Devices Using Telegram-Based ESP 32 Cam to Minimize Theft Guyub Rahman Auwali; Akhmad Ahfas; Shazana Dhiya Ayuni
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 3 No. 2 (2023): MALCOM October 2023
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v3i2.923

Abstract

Sepeda motor merupakan kendaraan yang penting untuk mayoritas warga Indonesia yang mempunyai harga beli yang terjangkau untuk masyarakat dengan penghasilan menengah kebawah. Sepeda motor  merupakan alternatif terbaik untuk orang banyak sebab bisa berkelit dari kemacetan serta padatnya jalan raya. Alasan lain mengapa sepeda motor menjadi transportasi yang paling banyak digunakan orang karena memudahkan perjalanan dalam kegiatan sehari hari terutama bekerja. Akan tetapi seiring dengan pesatnya penggunaan sepeda motor semakin banyak pula tindakan kejahatan yang ramai  saat  ini salah satunya yaitu pencurian  sepeda  motor. Tujuan penelitian ini adalah untuk merancang alat yang dapat mengontrol tanpa harus melakukan kontak fisik serta pengiriman data ke smartphone yang lebih cepat. ketika wajah yang terdeteksi oleh sistem adalah wajah yang sudah terdaftar di ESP 32 Cam (pemilik motor) maka kelistrikan akan menyala dan motor dapat digunakan tetapi apabila wajah sipengguna tidak terkenali oleh ESP 32 Cam (bukan pemilik motor) maka kelistrikan akan mati dan akan memberikan notifikasi serta data tersebut akan diproses kedalam Telegram, kemudian buzzer akan berbunyi. Hasil pengujian alat meliputi telegram yang telah diprogram melalui aplikasi Arduino sudah berfungsi sesuai tujuan, sedangkan pengujian keakuratan ESP 32 Cam dalam peroses pengenalan wajah tergantung pada intensitas cahaya sekitar.
The Role of E-Commerce Use, Capital Availability and Business Training on Performance of Small Medium Enterprise (SMEs) in Indonesia Fahrina Mustafa; Tri Febrina Melinda; Tri Yusnanto; Arief Yanto Rukmana; Jamaluddin Majid
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 3 No. 2 (2023): MALCOM October 2023
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v3i2.924

Abstract

This study aims to determine whether the simultaneous use of finance, business training, and e-commerce has a favorable and significant impact on microbusiness revenue. Multiple linear regression is being used in this quantitative research approach. The people who participate in microbusinesses and have received business training make up the population of this study. Purposive sampling, a non-probability sample technique, and a total of 100 respondents make up the approach employed in this study. The questions for this study were made available and directly completed by respondents using Google Forms. The Likert scale was employed by the author as a measurement in this study. The usage of e-commerce has a good and considerable impact on microbusiness income, according to the research findings. Microbusiness income is significantly and favorably impacted by capital. Microbusiness income is significantly and favorably affected by enterprise training. Microbusiness revenue benefits significantly and positively from the usage of e-commerce, financing, and business training all at once. 52% of microbusiness income is impacted by the usage of e-commerce, financing, and enterprise training. The other 48%, meanwhile, was affected by things unrelated to this study.

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