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All Journal SITEKIN: Jurnal Sains, Teknologi dan Industri Jurnal Ilmiah Giga Jurnal EMT KITA Informatik : Jurnal Ilmu Komputer Edumaspul: Jurnal Pendidikan Minda Baharu Jurnal Ilmiah Edunomika (JIE) Jurnal Informasi dan Teknologi Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Journal Sensi: Strategic of Education in Information System Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Community Development Journal: Jurnal Pengabdian Masyarakat Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Kompleksitas: Jurnal Ilmiah Manajemen, Organisasi, dan Bisnis International Journal Software Engineering and Computer Science (IJSECS) Digital Transformation Technology (Digitech) Innovative: Journal Of Social Science Research West Science Journal Economic and Entrepreneurship West Science Interdisciplinary Studies The Eastasouth Journal of Learning and Educations West Science Interdisciplinary Studies The Eastasouth Journal of Social Science and Humanities
Mardiani, Eri
Unknown Affiliation
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Public Health Social Sciences Other

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Implementasi Metode Penalaran CBR dalam Mengidentifikasi Gejala Awal Penyakit Jantung menggunakan Algoritma Sorensen Coeffient Arundy, Vicky Agnes; Fitri, Iskandar; Mardiani, Eri
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 5, No 3 (2021): JTIK
Publisher : KITA Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v5i3.220

Abstract

Heart disease is a condition when the heart is experiencing a disorder. The forms of disturbance that are experienced are usually various. Usually there is a disturbance in the blood vessels of the heart, heart rate, heart cover, or congenital problems. The heart itself is a muscle consisting of four chambers. That is, the first two rooms are located at the top, the atrium (foyer) to the left and right. Then the other two rooms are at the bottom, namely the right and left ventricles. To provide information on how to diagnose the type of disease and how to control heart disease, an application of an expert system that can represent someone who is an expert in their field is needed to provide solutions to this disease problem using the Case-Based Reasoning method with the Sorensen Coeffient approach. The result of this research is the creation of an expert system for diagnosing heart disease using the Case-Based Reasoning method with the Sorensen Coeffient approach which is able to provide solutions to heart disease.Keywords:CBR, Expert system, Heart Disease, Method Sorensen Coeffient.
Penerapan Face Recognition pada Aplikasi Akademik Online Utomo, Budi Tri; Fitri, Iskandar; Mardiani, Eri
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 5, No 4 (2021): JTIK
Publisher : KITA Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v5i4.244

Abstract

In the era of big data, the biometric identification process is growing very fast and is increasingly being implemented in many applications. Face recognition technology utilizes artificial intelligence (AI) to recognize faces that are already stored in the database. In this research, it is proposed to design an online academic login system at the National University using real time face recognition used OpenCV with the Local Binary Pattern Histogram algorithm and the Haar Cassade Classification method. The system will detect, recognize and compare faces with the stored face database. The image used is 480 x 680 pixels with a .jpg extension in the form of an RGB image which will be converted into a Grayscale image., to make it easier to calculate the histogram value of each face that will be recognized. With a modeling system like this it is hope to make it easy for user to log into online academics.Keywords:Face Recognition, Haar Cascade Clasifier, Local Binary Pattern Histogram, Online Akademic, OpenCV. 
Analisis Sentimen Tweet KRI Nanggala 402 di Twitter menggunakan Metode Naïve Bayes Classifier Djamaludin, Muhammad Ariel; Triayudi, Agung; Mardiani, Eri
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 6, No 2 (2022): April-June
Publisher : KITA Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v6i2.398

Abstract

Social media is one of the technological developments that has contributed greatly in making it easy for us to communicate and socialize, one of which is using Twitter social media. Twitter in this study is used as a data source to analyze tweets discussing KRI Nanggala 402. Analysis of KRI Nanggala 402 twitter sentiment is used to see the tendency of public responses to the sinking of the KRI Nanggala 402 submarine whether to give positive or negative opinions. This Sentiment analysis uses the Naïve Bayes Classifier method, which is a classification method. The first research stage is crawling, processing, classification, and evaluation. The classification stage is carried out after the processing phase, where the classification results tend to be positive or negative, using the Naïve Bayes Classifier method. The accuracy of the system in the Sentiment analysis of the KRI Nanggala 402 tweet is 73.00%.
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.
Optimalisasi Aplikasi Pengendalian Skripsi Menggunakan Algoritma Dynamic Priority Scheduling dan Sequential Search Arief, Arya; Sari, Ratih Titi Komala; Mardiani, Eri
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 8 No 3 (2024): JULY-SEPTEMBER 2024
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v8i3.2219

Abstract

Thesis registration in the academic environment often faces priority and time management problems, therefore an effective and responsive approach is needed. This study suggests optimizing the Dynamic Priority Scheduling and Sequential Search algorithms to improve the performance of thesis control applications. Dynamic characteristics of students and service requests regulate submission priorities and a sequential search algorithm improves the search for thesis-related information in the database. This research discusses the ideas of both algorithms and how they can improve system efficiency by integrating them.
Evaluasi Efektivitas Iklan Aero Street di Media Sosial dengan Consumer Decision Model (CDM) Mardiani, Eri; Rasyad, Rizky Zakariyya; Hasian, Irene
Jurnal EMT KITA Vol 8 No 1 (2024): JANUARY 2024
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/emt.v8i1.2165

Abstract

Social media advertising plays a crucial role in marketing. This research evaluates the influence of advertising messages and Brand recognition on consumer Attitudes on social media, using the Consumer Decision Model (CDM) on Aero Street advertising. A total of 100 respondents were selected through purposive sampling. Data was collected through questionnaires and analyzed using multiple linear regression. The results show that the advertising message variables (I, Information) and Brand recognition (B, Brand recognition) have a positive effect on consumer Attitudes (A, Attitude), such as A = 2.172 + 0.229F + 0.258B. The calculated F statistical test is 19.005, exceeding the F table of 3.090, indicating a significant joint influence. The advertising message and Brand recognition variables simultaneously and partially have a significant effect on consumer Attitudes, showing the effectiveness of Aero Street advertising on social media with CDM.
Analisis Segmen Pelanggan Dalam Merespon Produk Menggunakan Metode KNN, Naive Bayes, Decision Tree, Ensemble, Linear Regression Mardiani, Eri
Jurnal Ilmiah Giga Vol. 26 No. 2 (2023): Volume 26 Edisi 2 Tahun 2023
Publisher : Universitas Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47313/jig.v26i2.2942

Abstract

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B2B Digital Marketing and ROI Measurement: Challenges and Opportunities in the Business-to-Business Industry for MSMEs in Indonesia Mardiani, Eri; Utami, Eva Yuniarti; Farooq Mujahid, Muhammad Umer
West Science Interdisciplinary Studies Vol. 1 No. 09 (2023): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v1i09.249

Abstract

In order to maintain growth and competitiveness in the modern business environment, digital marketing must be strategically integrated, especially for Micro, Small, and Medium-Sized Enterprises (MSMEs) that conduct business-to-business (B2B) transactions. This study looks into the potential and difficulties that come with B2B digital marketing as well as how to measure return on investment (ROI) for MSMEs in Indonesia. Surveys and in-depth interviews were used in a mixed-methods approach to collect both quantitative and qualitative data. The results show that MSMEs have widely adopted digital marketing tactics, with social media and content marketing being the most popular. There are still issues like tight budgets, hard ROI calculations, and fierce market competition. The report makes actionable suggestions, such as group marketing campaigns, the creation of uniform ROI measurements, and a focus on innovation via emerging technologies and niche targeting. The insights provide practitioners, policymakers, and industry stakeholders with practical advice for improving the knowledge of the dynamics in B2B digital marketing for MSMEs in Indonesia.
Improving Trust and Accountability in AI Systems through Technological Era Advancement for Decision Support in Indonesian Manufacturing Companies Mardiani, Eri; Judijanto, Loso; Rukmana, Arief Yanto
West Science Interdisciplinary Studies Vol. 1 No. 10 (2023): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v1i10.301

Abstract

This study explores how technological developments in Artificial Intelligence (AI) decision support systems within Indonesian manufacturing organizations interact with the intricate dynamics of trust, accountability, and technology. The study employed a cross-sectional quantitative research approach to gather responses from a representative sample of professionals spanning different organizational levels, age groups, and functions. The results show that there is a high degree of trust in AI systems, which is largely impacted by dependability and transparency. Strong perceived accountability frameworks encourage prudent decision-making. Technological developments have a big impact on trust and responsibility, especially in Explainable AI and bias prevention. A nuanced interpretation is ensured by the study's demographic analysis, which provides practitioners and policymakers with practical insights to support ethical AI integration in Indonesia's industrial sector.
Business Intelligence Dashboard Visualization on Information Systems for Online Verification of Invoice Documents and Requests for Goods or Services Hadiwinata, Daad; Fauziah, F; Mardiani, Eri
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 1 (2024): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i1.748

Abstract

In the daily running of their business, business companies are usually faced with the problem of adapting to changing trends related to the business world. To make a decision that is precise, fast, and accurate based on data and analysis, the company must apply Business Intelligence (BI) based technology. In this research, the study was conducted at PT ADHI KARYA (Persero) Tbk, which has a problem with the document verification system which is still done manually. To help the above problems, a solution is offered by utilizing Business Intelligence (BI) based technology to create a dashboard of information systems for verification of invoice documents and requests for goods and services online. For evaluating the performance of employees or verifier officers can use the collaboration between BI and the K-Means Algorithm by classifying incoming data based on the duration of the data input until the e-Verification sheet is sent by the system.   The system development method in this study uses the RAD (Rapid Application Development) method of rapid application development. Which is expected to produce a solution in the form of a visualization dashboard for online verification information systems for invoice documents and requests for goods and services based on Business Intelligence technology.
Co-Authors . Syamsulbahri Agung Triayudi Ahmad Salabi Aisha, Amelia Ayu Nur Akbar Ramadhan, Ferdan Al Rizky, Farid Arief Setiawan Arief, Arya Arundy, Vicky Agnes Aziza, Failasufa Budyarti, Sisca Cahyani, Lidya D.Iwan Riswandi Damau, Unika Oktaviani Darusallam, Ucuk Deny Hidayatullah Deny Hidayatullah Desmana, Satriawan Dewi, A.Ratna Sari Dhema, Salestinus Petrus Dhieka Avrilia Lantana Dhieka Avrilia Lantana Djafri, Novi Djamaludin, Muhammad Ariel Djoko Setyadi Endah Tri Esthi Handayani Endah Tri Esti Handayani Fachry, Fachry Farooq Mujahid, Muhammad Umer Fauziah, F Fitri, Annisa Amalia Hadiwinata, Daad Halim Mudia Haryaka, Usfandi Hasian, Irene Hendriyani, Mungky Hia, Era Era Ilhamiwati, Mega Ilwandri, Ilwandri Irma Rahmawati Irwansyah Irwansyah Iskandar Fitri, Iskandar Judijanto, Loso Khamaludin, Khamaludin Kurniati, Ira Leonita Sibarani, Magdalena Linda Limbalo, Syifa Sumayyah Azzahrah Lombu, Azzaleya Agashi Mamonto, Jessyka Maqfirah, Poetri AL-Viany Matiala, Tiara Fathulmila Matondang, Nurhafifah Mohammad Edy Nurtamam, Mohammad Edy Mokodenseho, Sabil Mokodompit, Nesa Yuliska Mustafa, Rayhan Nur Hayati Nurfaiz, Kelfin Occe Luciana, Occe Panjaitan, Feliks Anggia Binsar Kristian Perdana, Muhammad Rizky Podomi, Adelia Pramesti, Komang Mustika Prasetya, Vithalia Rizki Prasetyo, Yoga Dwi Purnata, Alan Putri, Lusiana Putro, Prayogo Dwi Cahyo Raden Mohamad Herdian Bhakti Rahmansyah, Nur Ramadhan, Ferdan Akbar Rasyad, Rizky Zakariyya Ratih Titi Komalasari Rini Fatmawati Riniati, Wa Ode Rizki, Muhammad Romadhoni Romzy , Inayah Rukmana, Arief Yanto Sabalius Uhai Santosa, Tomi Apra Sari Ningsih Sari Ningsih Septya, Sharmila Setiawan Wibowo, Teguh Sugiyarto, Arman Prasojo Sugiyono Sugiyono Suharto Suharto Suhatmojo, Guing Tri Supriyanti, Dedeh Surahmi, Mila Syarifah Hudayah Tesalonika Utami, Eva Yuniarti Utomo, Budi Tri Wibowo, Teguh Setiawan Wijaya, Yunan Fauzi Wulandana, Nabila Puspita Yandri, Delfi Yayat Suharyat Yunan Fauzi Wijaya ZA, Saida Zainurossalamia Zanitha, Dinda Amelia