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All Journal ILKOM Jurnal Ilmiah Minda Baharu Jurnal Teknik Informatika (JUTIF) International Journal of Economics, Management, Business, and Social Science International Journal Software Engineering and Computer Science (IJSECS) INTERNATIONAL JOURNAL OF EDUCATION, INFORMATION TECHNOLOGY, AND OTHERS Global Advances in Business Studies
Dhieka Avrilia Lantana
Bogor Agricultural University
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences Other

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SISTEM PAKAR UNTUK MENDIAGNOSA PENYAKIT KULIT PADA KUCING MENGGUNAKAN CERTAINTY FACTOR Kurniati, Nia; Yanitasari, Yessy; Lantana, Dhieka Avrilia; Karima, Inna Sabily; Susanto, Erliyan Redy
ILKOM Jurnal Ilmiah Vol 9, No 1 (2017)
Publisher : Program Studi Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1027.985 KB)

Abstract

Kucing merupakan hewan yang mudah beradaptasi dan dapat menjadi teman baik bagi manusia. Kecerobohan pemilik dalam menjaga dan merawat kucing dapat mengakibatkan kematian bagi kucing. Salah satu penyakit yang sering dijumpai adalah penyakit kulit pada kucing. Pemahaman masyarakat akan penyakit kulit pada kucing masih rendah. Sehingga masih banyak masyarakat yang masih mengandalkan keahlian dari pakar secara manual. Selain itu, biaya untuk pengobatan ke dokter hewan sangatlah mahal dan keberadaan dokter hewan masih sangat sedikit. Kesalahan pemberian obat dapat memperparah kondisi kucing. Solusi dari permasalahan tersebut dapat di bangun melalui sistem pakar Sistem pakar merupakan sistem penalaran yang dapat menentukan jenis penyakit seperti halnya dokter. Penelitian ini menggunakan pendekatan Certainty Factor yaitu pendekatan ketidakpastian. Hasil penelitian menunjukkan tingkat kebenaran, keakuratan dari kemungkinan penyakit kulit pada kucing.
Classification of Potential Tsunami Disaster Due to Earthquakes in Indonesia Based on Machine Learning Mardiani, Eri; Rahmansyah, Nur; Ningsih, Sari; Lantana, Dhieka Avrilia; Wulandana, Nabila Puspita; Lombu, Azzaleya Agashi; Budyarti, Sisca
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 1 (2024): APRIL 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i1.2084

Abstract

Earthquakes and tsunamis pose significant threats to Indonesia due to its unique geological positioning at the convergence of four tectonic plates. This study focuses on classifying the potential occurrence of tsunami disasters following earthquakes using various data mining methods, including k-Nearest Neighbor (kNN), Naïve Bayes, Decision Tree and Ensemble Method, and Linear Regression. The research employs a qualitative approach to systematically understand and describe the context of natural disasters, utilizing both primary and secondary data collection techniques. Performance evaluation metrics such as Area Under the Curve (AUC), Classification Accuracy (CA), F1 Score, Precision, and Recall are utilized to assess the effectiveness of each method in predicting potential tsunami events. The findings reveal that the kNN method exhibits the highest performance, with an AUC of 94.4% and a precision of 82.8%, indicating robust predictive capabilities. However, misclassifications were observed, emphasizing the need for further refinement. Naïve Bayes also shows promising results with an AUC of 84.5% and precision of 78.6%. Decision Tree and Ensemble Method models, such as Random Forest and AdaBoost, demonstrate reasonable performance, with Random Forest achieving the highest AUC of 71.9%. Linear Regression is employed to explore the correlation between earthquake attributes and tsunami occurrence, revealing a weak relationship. Further research integrating advanced modeling approaches and additional earthquake attributes is recommended to enhance the predictive capabilities of tsunami risk assessment models. The study underscores the importance of employing diverse machine learning techniques and evaluating their performance metrics to refine the accuracy of tsunami prediction models, ultimately contributing to practical disaster preparedness and mitigation strategies.
The Determinants of Startup Business Growth in Indonesia: A Bibliometrical Analysis Lantana, Dhieka Avrilia; Digdowiseiso , Kumba
INTERNATIONAL JOURNAL OF ECONOMICS, MANAGEMENT, BUSINESS, AND SOCIAL SCIENCE (IJEMBIS) Vol. 3 No. 3 (2023): September 2023
Publisher : CV ODIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59889/ijembis.v3i3.225

Abstract

Startups are companies that have had a major influence on the Indonesian economy especially in the past COVID-19 when with the presence of startups the circulation of money in the country is still awake. However, in its growth, the start-up company is currently experiencing constraints that have to dismiss many of its employees. Given how important startups are for the Indonesian economy, it is important to look for any determinants that could potentially influence the growth of startups in Indonesia. The researchers used quantitative methods using bibliometric analysis. The data used in the study were journals collected using Harzing’s Publish or Perish which were then curated by the researchers and analyzed using the VOSviewer application. The researchers found that out of the 29 journals obtained, only 20 corresponded to the study. The journal used was from 2018-2023 to keep the information on the study up to date. Based on the results of the analysis, the researchers found that the most powerful determinants to influence the growth of startup business in Indonesia are employee, Indonesia, startup growth, technology and the economy
The Implementation of Machine Learning on MSMEs Product Sales in Indonesia: A Systematic Literature Review Lantana, Dhieka Avrilia; Digdowiseiso , Kumba
INTERNATIONAL JOURNAL OF ECONOMICS, MANAGEMENT, BUSINESS, AND SOCIAL SCIENCE (IJEMBIS) Vol. 3 No. 3 (2023): September 2023
Publisher : CV ODIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59889/ijembis.v3i3.232

Abstract

Micro, Small, and Medium Enterprises (MSMEs) are crucial in Indonesia. They contribute significantly to employment absorption and can be initiated with minimal capital. However, this does not imply that MSMEs are without potential challenges. They often face difficulties in capturing markets and implementing professional management practices. This is why technological assistance is needed within this sector. One anticipated technical aid is the application of Machine Learning as a marketing tool. This aligns with the characteristics of Machine Learning, which has long been instrumental in various businesses. This research employs the systematic literature review method to explore how Machine Learning can help MSMEs. Findings based on the SLR demonstrate that Machine Learning not only aids in marketing but also enhances operational efficiency.
PENINGKATAN PENJUALAN UMKM ALBY KEY DENGAN PEMASARAN DIGITAL Mardiani, Eri; Rahmansyah, Nur; Ningsih, Sari; Handayani, Endah Tri Esti; Hidayatullah, Deny; Desmana, Satriawan; Lantana, Dhieka Avrilia; Fachry, Fachry; Suhatmojo, Guing Tri; Nurfaiz, Kelfin; Perdana, Muhammad Rizky; Putro, Prayogo Dwi Cahyo; Dhema, Salestinus Petrus; Prasetyo, Yoga Dwi
MINDA BAHARU Vol 7, No 1 (2023): Minda Baharu
Publisher : Universitas Riau Kepulauan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33373/jmb.v7i1.5330

Abstract

Pandemi covid-19 sangat berdampak sekali terhadap UMKM serta bagi yang baru membuat wirausaha, dengan kondisi peralihan dari masa pandemi ke endemi, penjualan dengan secara konvensional sangat tidak efektif, agar penjualan dapat berjalan dengan baik, maka pelaku usaha harus dapat mengembangkan usahanya. Untuk bangkit kembali mengembangkan usahanya maka pelaku usaha harus mampu meningkatkan potensi diri menyesuaikan kondisi saat ini sehingga pelaku melakukan wirausaha dengan efisien, salah satu untuk meningkatkan penjualan, pelaku usaha harus mengoptimalkan pemasaran penjualan dengan sistem digital, dengan menggunakan potensi diri dan keinginan pelaku usaha untuk mengembangkan pemasaran maka peningkatan penjualan menggunakan sistem digital jauh lebih mudah untuk mengembangkan usaha. Dengan menggunakan Social Customer Relationship Management (SCRM) untuk membantu end-user memanfaatkan jejaring sosial, data internal dan eksternal, umpan berita, serta konten penjualan dan pemasaran yang ada dengan lebih baik. Contohnya dengan menggunakan e-commerce dan media sosial untuk mempermudah promosi. Karena era digital saat ini, pemasaran produk UMKM menggunakan situs web yang tepat, memiliki manfaat yang sangat besar karena promosi penjualan atau pemasaran dapat menjangkau target konsumen dengan jangkauan yang lebih luas dan dengan jaminan layanan yang optimal dengan biaya yang relatif murah dan lebih efisien. Untuk sukses di era digital, UMKM juga perlu mengelola strategi pemasarannya dengan memanfaatkan teknologi digital.
Exploring the influence of digital marketing strategies on private university selection Tuna, Syifa Azzahra; Cahyani, Diah Hanung; Lantana, Dhieka Avrilia; Lestari, Rahayu
Global Advances in Business Studies Vol. 3 No. 2 (2024): Global Advances in Business Studies (GABS)
Publisher : Ifma Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55584/Gabs003.02.3

Abstract

Understanding the factors influencing students' decisions to attend private universities can provide valuable insights for educational institutions in South Jakarta. This study aims to determine the effects of aspects of digital marketing, such as social media, marketing, paid ads, and website quality, on students’ decision to select private universities in South Jakarta. If universities know which factors have the most significant impact, they can effectively allocate their resources. Data were collected through questionnaires distributed via Google Forms to first-year students across private universities in South Jakarta. This study used a purposive sampling technique to collect data from 101 respondents, and quantitative methods were used for analysis. The results show a positive correlation between the decision to attend a private university and social media marketing, influencer marketing, and paid ads.
Product Diversification and Implementation of Public Relations Strategy at Setu Babakan Kusumaningrum, Anisa Putri; Waluyo, Tri; Pradini, Gagih; Saleh, Muhammad Surya; Lantana, Dhieka Avrilia
International Journal of Education, Information Technology, and Others Vol 8 No 1 (2025): International Journal of Education, information technology   and others
Publisher : Peneliti.net

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study discusses product diversification and the implementation of Public Relations (PR) strategies in the Betawi Setu Babakan Cultural Village, as one of the cultural tourism destinations in Jakarta. By utilizing SWOT analysis, this study explores the potential for product diversification in various zones, such as Zone A and Embryo which highlights Betawi culture through museums and traditional houses, as well as Zone B which offers typical culinary and children's play rides. The PR strategy implemented includes the use of social media for promotion, collaboration with various parties, and market research to understand visitor preferences. The results of the study show that product diversification and effective PR strategies can increase the competitiveness and sustainability of tourist destinations. However, challenges such as competition from other destinations and the impact of negative reviews on social media need to be addressed. In conclusion, by taking advantage of internal advantages and existing opportunities, Setu Babakan can strengthen its image as an attractive and sustainable cultural tourism destination.
OPTIMIZATION ISO 25010 WITH THE VORD METHOD AND C4.5 ALGORITHM IN SAVING LOAN COOPERATIVE Subkhi, Akhmad Yunus; Andrianingsih, Andrianingsih; Lantana, Dhieka Avrilia
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 4 (2023): JUTIF Volume 4, Number 4, August 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.4.900

Abstract

Advances in technology have made many companies and agencies, especially cooperatives, use information technology for their operational activities. Not infrequently in the operation of its business cooperatives have several obstacles caused by data processing and loan decision making still using conventional models. Cooperatives need a computerized information system in achieving organizational goals. To overcome this problem, a system is created that is integrated in one database which will be implemented by the Cooperative to facilitate its business operations. This study uses the Viewpoint Oriented Requirement Definition (VORD) method to analyze system requirements based on the user's point of view. In addition, the C4.5 Algorithm and the Naïve Bayes Algorithm as decision making for loan approval which will be compared in recommending and classifying loans using the confusion matrix, the results of testing the two algorithms with an accuracy value of the C4.5 Algorithm of 88.00% and an accuracy rate of the Naïve Bayes Algorithm of 76.00%. It can be concluded that the accuracy value of the C4.5 Algorithm is feasible to be implemented into the Koperasi Jasa Pratama system. The application that is made is then tested using the ISO 25010 standard to produce an optimal application. After conducting a needs analysis using the VORD method for ISO optimization, an application test is carried out using the ISO 25010 standard. From the test results, the characteristics of the Functional Suitability test are: Appropriate; Usability : 90.08; Performance Efficiency : Grade "B"; Portability : no errors. The test results show that the system is appropriate and feasible to use.
Co-Authors A.A. Ketut Agung Cahyawan W Andrianingsih Budyarti, Sisca Cahyani, Diah Hanung Deny Hidayatullah Desmana, Satriawan Dhema, Salestinus Petrus Digdowiseiso , Kumba Endah Tri Esti Handayani Fachry, Fachry Karima, Inna Sabily Kusumaningrum, Anisa Putri Lombu, Azzaleya Agashi Mardiani, Eri Nurfaiz, Kelfin Perdana, Muhammad Rizky Pradini, Gagih Prasetyo, Yoga Dwi Putro, Prayogo Dwi Cahyo Rahayu Lestari Rahmansyah, Nur Saleh, Muhammad Surya Sari Ningsih Subkhi, Akhmad Yunus Suhatmojo, Guing Tri Susanto, Erliyan Redy Tri Waluyo Tuna, Syifa Azzahra Wulandana, Nabila Puspita Yessy Yanitasari