Pub Date : 2023-10-16DOI: 10.57152/malcom.v3i2.920
Luh Made Wisnu Satyaninggrat, Prasis Damai Nursyam Hamijaya, Khairunnisa Rahmah
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.
{"title":"Analisis Pemodelan Data Flow Diagram pada Sistem Basis Data Wisata Kuliner di Kota Balikpapan","authors":"Luh Made Wisnu Satyaninggrat, Prasis Damai Nursyam Hamijaya, Khairunnisa Rahmah","doi":"10.57152/malcom.v3i2.920","DOIUrl":"https://doi.org/10.57152/malcom.v3i2.920","url":null,"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.","PeriodicalId":499353,"journal":{"name":"MALCOM Indonesian Journal of Machine Learning and Computer Science","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136183596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-16DOI: 10.57152/malcom.v3i2.924
Fahrina Mustafa, Tri Febrina Melinda, Tri Yusnanto, Arief Yanto Rukmana, Jamaluddin Majid
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.
{"title":"The Role of E-Commerce Use, Capital Availability and Business Training on Performance of Small Medium Enterprise (SMEs) in Indonesia","authors":"Fahrina Mustafa, Tri Febrina Melinda, Tri Yusnanto, Arief Yanto Rukmana, Jamaluddin Majid","doi":"10.57152/malcom.v3i2.924","DOIUrl":"https://doi.org/10.57152/malcom.v3i2.924","url":null,"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.","PeriodicalId":499353,"journal":{"name":"MALCOM Indonesian Journal of Machine Learning and Computer Science","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136183745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Alat Kontrol dan Pengaman Sepeda Motor Menggunakan ESP 32 Cam Berbasis Telegram untuk Meminimalisasi Pencurian","authors":"Guyub Rahman Auwali, Akhmad Ahfas, Shazana Dhiya Ayuni","doi":"10.57152/malcom.v3i2.923","DOIUrl":"https://doi.org/10.57152/malcom.v3i2.923","url":null,"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.","PeriodicalId":499353,"journal":{"name":"MALCOM Indonesian Journal of Machine Learning and Computer Science","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135923080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-12DOI: 10.57152/malcom.v3i2.921
Itot Bian Raharjo
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.
{"title":"ChatGPT's Role in Transforming Employee Recruitment and Selection Processes","authors":"Itot Bian Raharjo","doi":"10.57152/malcom.v3i2.921","DOIUrl":"https://doi.org/10.57152/malcom.v3i2.921","url":null,"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.","PeriodicalId":499353,"journal":{"name":"MALCOM Indonesian Journal of Machine Learning and Computer Science","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136058529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-12DOI: 10.57152/malcom.v3i2.904
Vicky Salsadilla, Inggih Permana, Muhammad Jazman, M. Afdal
Tugas Akhir (TA) merupakan karya tulis ilmiah yang disusun berdasarkan suatu permasalahan. TA harus diselesaikan oleh seluruh mahasiswa yang ingin menyelesaikan studinya. Selama ini, mahasiswa sering mengalami kesulitan dalam menentukan topik TA yang ingin diteliti. Untuk mengatasi permasalahan tersebut, penelitian ini mencoba melakukan penentuan topik TA menggunakan teknik Machine Learning (ML) berdasarkan matakuliah-matakuliah pilihan yang pernah diambil oleh seorang mahasiswa. Matakuliah pilihan merupakan salah satu data akademik yang bisa digunakan untuk mempertimbangkan topik TA. Algoritma-algoritma ML yang digunakan adalah KNN, NBC, ANN, SVM, C4.5, Random Forest, dan Logistic Regression. Dataset yang digunakan pada penelitian ini adalah data imbalance. Untuk hal tersebut, penelitian ini melakukan balancing data menggunakan metode Random Oversampling dan metode Random Undersampling. Hasil percobaan-percobaan menunjukkan bahwa dataset yang di-balancing menggunakan ROS menghasilkan performa ML yang jauh lebih tinggi, akan tetapi memiliki kecenderungan over-fitting dikarenakan terjadi duplikasi data pada dataset. Jika dataset tidak di-balancing sama sekali maka performa ML akan sangat rendah. Oleh sebab itu, untuk data yang imbalance disarankan untuk menggunaka metode RUS sebagai balancing data. Hasil akurasi tertinggi untuk Algoritma yang dibalancing menggunakan ROS yakni ANN=69.7%, RF=66.7%, SVM=57.6%, LR=57.6%, NBC=42.4%, C4.5=42.4%, dan KNN=33.3%
期末论文是一份基于问题的科学论文。助教应该由所有想完成学业的学生来完成。在这段时间里，学生们经常在选择他们想要研究的助教方面遇到困难。为了解决这个问题，本研究试图根据学生所选择的数学学习技术(ML)来确定一个主题。可供参考的学术数据是研究TA主题的学术数据之一。使用的ML算法是KNN, NBC, ANN, SVM, C4.5，随机森林和逻辑回归。用于这项研究的数据采用反扫描数据。为此，本研究采用随机抽样法和随机抽样方法进行数据平衡。实验结果表明，使用ROS的压缩数据产生了更强的ML性能，但由于数据复制发生而产生了过度匹配的趋势。如果数据集根本不平衡，那么ML的性能将非常低。因此，建议使用RUS的方法作为数据平衡。使用ROS on (ANN)的算法以69.7%为单位，r.f. 7%， SVM=57.6%， LR=57.6%， NBC= 44.4%， C4.5= 43.4%， KNN=33.3%，得分最高
{"title":"Penentuan Topik Tugas Akhir Berdasarkan Matakuliah Yang Pernah Diambil Menggunakan Teknik Machine Learning","authors":"Vicky Salsadilla, Inggih Permana, Muhammad Jazman, M. Afdal","doi":"10.57152/malcom.v3i2.904","DOIUrl":"https://doi.org/10.57152/malcom.v3i2.904","url":null,"abstract":"Tugas Akhir (TA) merupakan karya tulis ilmiah yang disusun berdasarkan suatu permasalahan. TA harus diselesaikan oleh seluruh mahasiswa yang ingin menyelesaikan studinya. Selama ini, mahasiswa sering mengalami kesulitan dalam menentukan topik TA yang ingin diteliti. Untuk mengatasi permasalahan tersebut, penelitian ini mencoba melakukan penentuan topik TA menggunakan teknik Machine Learning (ML) berdasarkan matakuliah-matakuliah pilihan yang pernah diambil oleh seorang mahasiswa. Matakuliah pilihan merupakan salah satu data akademik yang bisa digunakan untuk mempertimbangkan topik TA. Algoritma-algoritma ML yang digunakan adalah KNN, NBC, ANN, SVM, C4.5, Random Forest, dan Logistic Regression. Dataset yang digunakan pada penelitian ini adalah data imbalance. Untuk hal tersebut, penelitian ini melakukan balancing data menggunakan metode Random Oversampling dan metode Random Undersampling. Hasil percobaan-percobaan menunjukkan bahwa dataset yang di-balancing menggunakan ROS menghasilkan performa ML yang jauh lebih tinggi, akan tetapi memiliki kecenderungan over-fitting dikarenakan terjadi duplikasi data pada dataset. Jika dataset tidak di-balancing sama sekali maka performa ML akan sangat rendah. Oleh sebab itu, untuk data yang imbalance disarankan untuk menggunaka metode RUS sebagai balancing data. Hasil akurasi tertinggi untuk Algoritma yang dibalancing menggunakan ROS yakni ANN=69.7%, RF=66.7%, SVM=57.6%, LR=57.6%, NBC=42.4%, C4.5=42.4%, dan KNN=33.3%","PeriodicalId":499353,"journal":{"name":"MALCOM Indonesian Journal of Machine Learning and Computer Science","volume":"129 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136058368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Analisis Sentimen Opini Publik pada Twitter Terhadap Bank BSI Menggunakan Algoritma Machine Learning","authors":"Ratna Andini Husen, Rizki Astuti, Lili Marlia, Rahmaddeni Rahmaddeni, Lusiana Efrizoni","doi":"10.57152/malcom.v3i2.901","DOIUrl":"https://doi.org/10.57152/malcom.v3i2.901","url":null,"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.","PeriodicalId":499353,"journal":{"name":"MALCOM Indonesian Journal of Machine Learning and Computer Science","volume":"11 suppl_1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136058359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"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","authors":"Rini Hadiyati, Budi Harto, Dhiana Ekowati, Jefriyanto Jefriyanto, Sonny Santosa","doi":"10.57152/malcom.v3i2.918","DOIUrl":"https://doi.org/10.57152/malcom.v3i2.918","url":null,"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.","PeriodicalId":499353,"journal":{"name":"MALCOM Indonesian Journal of Machine Learning and Computer Science","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135196401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-09DOI: 10.57152/malcom.v3i2.917
Febri Sari Siahaan, Irma M. Nawangwulan, Hari Setia Putra, Samuel PD Anantadjaya, Sukma Irdiana
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.
{"title":"Analysis of The Influence of Brand Image, Digital Marketing and Product Knowledge on Customers Purchase Intention of Banking Products","authors":"Febri Sari Siahaan, Irma M. Nawangwulan, Hari Setia Putra, Samuel PD Anantadjaya, Sukma Irdiana","doi":"10.57152/malcom.v3i2.917","DOIUrl":"https://doi.org/10.57152/malcom.v3i2.917","url":null,"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.","PeriodicalId":499353,"journal":{"name":"MALCOM Indonesian Journal of Machine Learning and Computer Science","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135196881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-09DOI: 10.57152/malcom.v3i2.919
Nur Augus Fahmi, Zulkifli Zulkifli, Tito Irwanto, Apit Fathurohman, I Wayan Adi Pratama
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.
{"title":"Analysis of The Influence of E-Commerce Use and Digital Literacy Toward Society Intention in Digital Entrepreneurship","authors":"Nur Augus Fahmi, Zulkifli Zulkifli, Tito Irwanto, Apit Fathurohman, I Wayan Adi Pratama","doi":"10.57152/malcom.v3i2.919","DOIUrl":"https://doi.org/10.57152/malcom.v3i2.919","url":null,"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.","PeriodicalId":499353,"journal":{"name":"MALCOM Indonesian Journal of Machine Learning and Computer Science","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135196664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-09DOI: 10.57152/malcom.v3i2.914
Linna Oktaviana Sari, Hazline Atika Suri, Ery Safrianti, Feranita Jalil
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.
{"title":"Rancang Bangun Sistem Monitoring Bandwidth Server pada PT. Industri Kreatif Digital","authors":"Linna Oktaviana Sari, Hazline Atika Suri, Ery Safrianti, Feranita Jalil","doi":"10.57152/malcom.v3i2.914","DOIUrl":"https://doi.org/10.57152/malcom.v3i2.914","url":null,"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.","PeriodicalId":499353,"journal":{"name":"MALCOM Indonesian Journal of Machine Learning and Computer Science","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135196637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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