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Identification of Earthquake Prone Zones in Sumatra using Density Based Spatial Clustering of Applications with Noise Sirodj, Dwi Agustin Nuriani; Aidi, Muhammad Nur; Sartono, Bagus; Syafitri, Utami Dyah; Pranata, Bayu
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.36120

Abstract

This study investigates the spatial distribution of earthquakes in Sumatra using the DBSCAN clustering algorithm applied to seismic data spanning 1 January 2000 to 31 December 2023. The analysis identified two distinct seismic clusters: one in the northern region (Aceh and North Sumatra) and another in the southern region (Lampung, Bengkulu, and West Sumatra), while several events in central areas were classified as noise. Cluster validity assessment confirmed that the identified groups are compact and well separated, reflecting meaningful seismotectonic segmentation. Statistical testing further revealed significant differences in earthquake depth and magnitude between the clusters, supporting the robustness of the findings. Notably, the southern cluster corresponds to the Mentawai Fault system, whereas the northern cluster aligns with the subduction zone and the Sumatran Fault. DBSCAN proved particularly effective in this context as it can capture clusters of arbitrary shapes, consistent with the complex geological structures governing seismicity in Sumatra.
Clustering Indonesian Neobanking Users Through Extended UTAUT 3 for Retention Campaign Strategy Rahmatulloh, Febriandi; Sumarwan, Ujang; Hartoyo, Hartoyo; Sartono, Bagus
ETIKONOMI Vol. 24 No. 2 (2025)
Publisher : Faculty of Economic and Business, Universitas Islam Negeri Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/etk.v24i2.42599

Abstract

Research Originality: This study develops a behavior-anchored segmentation framework for Indonesian neobank users by extending the Unified Theory of Acceptance and Use of Technology (UTAUT-3) with trust and marketplace application usage, providing deeper insights into user behavior. Research Objectives: The research aims to identify distinct neobank user segments and key behavioral drivers to support targeted strategies in digital financial services. Research Method: An extended UTAUT-3 model incorporating trust and marketplace usage was validated through Structural Equation Modeling (SEM). Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) clustering was applied to data from 386 active users, with segment validity confirmed using Elbow, Gap, and Silhouette methods. Empirical Results: The results revealed that trust, habit, and marketplace usage emerged as primary drivers of engagement and user recommendations. This study identifies four user segments: transitioning explorers, urban occasionalists, rural digital enthusiasts, and cost-conscious digital natives. Implications: Urban Occasionalists and Rural Digital Enthusiasts show strong potential for long-term growth. Targeted engagement and personalized retention strategies for these segments can enhance customer lifetime value and strengthen user advocacy. JEL Classification: G21, M31, C38
Identifying the Types of Future Skills Needed in The Manufacturing Industry: A Systematic Literature Review Akhilla, Kharismatul Zaenab; Sukmawati, Anggraini; Sartono, Bagus
Jurnal Aplikasi Bisnis dan Manajemen Vol. 11 No. 3 (2025): JABM Vol. 11 No. 3, September 2025
Publisher : School of Business, Bogor Agricultural University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/jabm.11.3.1099

Abstract

Background: The advent of Industrial Revolution 4.0 has led to the need to redesign the jobs and skills required across various industries and markets. As the manufacturing industry has the most significant contribution to GDP, it has not escaped the impact of this revolution. The dynamics of industrial growth, which tend to fluctuate from year to year, are also significant indicators of the need for strategic efforts to enhance the sector's resilience and competitiveness. One step that can be taken is to identify the types of future skills required and relevant to the manufacturing industry to adapt to a changing environment. Purpose: This study aims to identify the types of future skills needed by the manufacturing industry through a systematic literature review approach in order to obtain a comprehensive overview of relevant and strategic skill trends. Design/methodology/approach: This research employed the Systematic Literature Review (SLR) method, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. SLR serves as a systematic approach to identifying, evaluating, and synthesizing relevant previous research results, thereby obtaining a comprehensive understanding of the future skills required in the manufacturing industry. In addition, thematic analysis was used to identify and interpret patterns or themes within a dataset, as well as to develop a conceptual model of the study's results. Findings/Results: 63 types of future skills were categorized into eight categories. The classification of future skills in this study consists of: 1) Interpersonal Skills, 2) Leadership and Management, 3) adaptive and resilient mindsets, 4) Higher-Order Thinking Skills, 5) Entrepreneurial and Business Skills, 6) Learning and Development; Social and Ethical Responsibility; and 8) Personal Effectiveness. Conclusion: This research highlights the importance of the manufacturing industry in adapting to the changing demands brought about by Industrial Revolution 4.0 through the development of future skills. This study identified 63 types of future skills. It classifies them into eight main categories, considering the similarity of concepts, interrelationships in their application in the workplace, and the role of each skill in supporting individual readiness to face future challenges. Originality/value: This study has substantial originality value because it fills a significant research gap related to future skills in the manufacturing industry context. The lack of previous studies that specifically address future skill needs in this sector indicates the need for further exploration to strengthen the scientific foundation while making practical contributions. Therefore, this study is the first step in identifying the types of future skills that are relevant and potentially applicable to the manufacturing industry in Indonesia. Keywords: future skills, manufacturing industry, soft skills, systematic literature review, thematic analysis
Competitive analysis and strategic improvement of polypropylene polytam pf-1000 in indonesia Rahardi, Naufal; Hartoyo, Hartoyo; Sartono, Bagus
JHSS (JOURNAL OF HUMANITIES AND SOCIAL STUDIES) Vol 9, No 1 (2025): Journal of Humanities and Social Studies
Publisher : UNIVERSITAS PAKUAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/jhss.v9i1.11662

Abstract

This research intends to assess the competing capabilities of Polytam PF-1000 with other products available in the market Indonesia and suggest alternative approaches to strengthen its market position. A mixed approach was conducted combining survey with 305 respondents and detailed interviews, then using Analytic Hierarchy Process (AHP) method. Multiple regression results suggest that the Demand Conditions variable is the most determinant in competitiveness (β = 0.990, p < 0.05), then Related and Supporting Industries (β = 0.812), Firm Strategy, Structure, and Rivalry (β = 0.218), and lastly Factor Conditions (β = 0.159). It elaborates the necessity of understanding the market, collaboration in the business industry, formulating business strategy, and resource allocation in enhancing competitiveness of Polytam PF-1000. Further AHP (analytical hierarchy process) analysis using 55 stakeholders managed to rank two other group’s components and their weight: Factor Conditions was prioritized and received the most weight at 0.518, followed by Demand Conditions which was rated by 0.261. From the interviews, technological advancement, supply chain improvement, and expansion of market coverage formed the primary strategies. One of the angles of perspective that was surprising is that the consumers want a quicker response to their needs, while the internal stakeholders want investment in the needed resources and infrastructure. Along with regulatory changes and energy efficiency, these are new alternative strategies that were outside Porter’s Diamond.
A Hybrid Decision Tree and K-Means Approach for Classifying Community Happiness in Bogor Regency Anwar Fajar Rizki; Dwi Fitrianti; Sri Amaliya; Bagus Sartono; Aulia Rizki Firdawanti
Statistika Vol. 25 No. 2 (2025): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v25i2.5590

Abstract

Abstract. Happiness is one of the key indicators for measuring the quality of life in a community. This study aims to classify the level of happiness among residents of Bogor Regency using a hybrid approach that combines Decision Trees and K-means. The research procedure consisted of data preprocessing, clustering using K-Means to form preliminary groups, and further classification through a Decision Tree to interpret the determinants of happiness. The analysis revealed that the residents of Bogor Regency can be categorized into two groups: those who are fairly happy and those who are less happy. The hybrid model achieved its best performance with a balanced accuracy of 84%, an F1-Score of 37%, and a Kappa score of 28%. Socioeconomic factors, such as marital status, family status, occupation, and the number of cigarettes smoked, were identified as the primary determinants influencing happiness levels. The main contribution of this study lies in demonstrating the effectiveness of a hybrid Decision Tree–K-Means approach for happiness classification and providing interpretable insights that are directly useful for policymakers. These findings offer strategic implications for the local government to design more inclusive socioeconomic policies that aim to enhance happiness and overall well-being among the residents of Bogor Regency.
COMPARISON OF RANDOM FOREST AND SUPPORT VECTOR MACHINE CLASSIFICATION METHODS FOR PREDICTING THE ACCURACY LEVEL OF MADRASAH DATA Syarip, Dodi Irawan; Notodiputro, Khairil Anwar; Sartono, Bagus
MEDIA STATISTIKA Vol 18, No 1 (2025): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.18.1.37-48

Abstract

This study aims to identify the most effective classification method for predicting the accuracy level of madrasah data with class imbalance. Two machine learning approaches were employed: Random Forest (RF) and Support Vector Machine (SVM). Based on the AUC values, it was concluded that the RF model had a slightly better performance in predicting the accuracy level of the madrasah data, with an average AUC of 62.82, compared to the SVM model, which had an average AUC of 62.33. Among all models, the highest and consistent performance was achieved by the RF model using ROSE techniques. The results of measuring variable importance showed that the predictor variables with the greatest influence in predicting the accuracy level of the madrasah data are the number of students and the student-to-teacher and staff ratio. This finding suggests that school principals and madrasah administrative staff should prioritize ensuring the completeness of student, teacher, and staff data to improve the overall reliability of madrasah data.
Evaluating Fasttext and Glove Embeddings for Sentiment Analysis of AI-Generated Ghibli-Style Images Sentana Putra, I Gusti Ngurah; Yusran, Muhammad; Sari, Jefita Resti; Suhaeni, Cici; Sartono, Bagus; Dito, Gerry Alfa
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10600

Abstract

The development of text-to-image generation technology based on artificial intelligence has triggered mixed public reactions, especially when applied to iconic visual styles such as Studio Ghibli. This research aims to evaluate public sentiment towards the phenomenon of Ghibli-style AI images by comparing two static word embedding methods, namely FastText and GloVe, on three classification algorithms: Logistic Regression, Random Forest, and Convolutional Neural Network (CNN). Data in the form of Indonesian tweets were collected from Twitter using hashtags such as #ghibli, #ghiblistyle, and #hayaomiyazaki during the period 25 March to 25 April 2025. Each tweet was manually labelled with positive or negative sentiment, then preprocessed and represented using pre-trained FastText and GloVe embeddings. Evaluation was conducted using accuracy, precision, recall, and F1-score metrics, both macro and weighted. Results showed that FastText consistently performed the best on most models, especially in terms of precision and overall accuracy, thanks to its ability to handle sub-word information and spelling variations in social media texts. The combination of CNN with FastText yielded the highest performance with a macro F1-score of 76.56% and accuracy of 84.69%. However, GloVe still showed competitive performance in recall on the Logistic Regression model, making it relevant for contexts that prioritise sentiment detection coverage. This study emphasizes the importance of selecting embeddings and models that are appropriate to the characteristics of the data and the purpose of the analysis in informal social media-based sentiment classification.
COMPARISON OF LOGISTIC MODEL TREE AND RANDOM FOREST ON CLASSIFICATION FOR POVERTY IN INDONESIA Sukarna, Sukarna; Notodiputro, Khairil Anwar; Sartono, Bagus
MEDIA STATISTIKA Vol 16, No 2 (2023): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.16.2.112-123

Abstract

Classification methods are commonly employed to ensure homogeneous data within each group, facilitating the prediction of specific categories. The most frequently used classification models are Logistic Model Tree (LMT) and Random Forest (RF). This study aims to assess the accuracy rate in predicting the poverty status of regencies or towns across Indonesia, utilizing eight independent variables. The entire dataset was obtained from the official Central Bureau of Statistics website. The study investigates the accuracy of various iterations and combinations of training data. The results indicate that RF outperforms LMT in terms of accuracy, achieving a 100% improvement in iterations k=10 and k=500 and a 75% improvement in iteration k=100. Consequently, the RF proves to be more effective than the LMT for analyzing Indonesian poverty data, especially when incorporating all eight independent variables.
The Influence of Marketing Mix, Perceived Risk, and Satisfaction on Word of Mouth in XYZ Clinic Murpraptomo, Saka Haditya; Yuliati, Lilik Noor; Sartono, Bagus
Journal of Consumer Sciences Vol. 4 No. 1 (2019): Journal of Consumer Sciences
Publisher : Department of Family and Consumer Sciences, Faculty of Human Ecology, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jcs.4.1.13-24

Abstract

The increasing need for health services, peoples who lived in the Pekayon, Bekasi City were given the opportunity to choose the right clinic. Word of mouth is a marketing technique that can be used by clinics. This study aims to analyze the effects of the marketing mix, perceived risk, and satisfaction on word of mouth at XYZ clinic. The research is a descriptive method with a survey using questionnaires and 200 respondents as the sample. Furthermore, the data analysis technique is descriptive with SPSS16.0 software and Structural Equation Model (SEM) with LISREL 8.70. Based on the results, it can be concluded that the marketing mix has a positive effect on perceived risk, marketing mix has a positive effect on satisfaction, perceived risk has a negative effect on satisfaction, marketing mix has a positive effect on word of mouth, perceived risk has a negative effect on word of mouth, and satisfaction has a positive effect on word of mouth. Referring to these conclusions, it can be confirmed that the clinical management of doctor XYZ needs to improve employee services, convenience the patient that this clinic has expert doctors, and utilizing the use of social media as a marketing strategy.
The Role of 7P Marketing Mix toward Consumer Satisfaction and Loyalty of XYZ Beauty Clinic Alwinie, Ade Agusti; Nurhayati, Popong; Sartono, Bagus
Journal of Consumer Sciences Vol. 9 No. 1 (2024): Journal of Consumer Sciences
Publisher : Department of Family and Consumer Sciences, Faculty of Human Ecology, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jcs.9.1.40-62

Abstract

The XYZ Beauty Clinic has many branches throughout Indonesia, including the Metropolitan Mall (MM) Bekasi branch, which has been established since 2011. Over time, the XYZ MM Clinic has faced various challenges, such as a decrease in the frequency of customer visits. This study aims to analyze consumer perceptions, factors that affect consumer satisfaction and loyalty, and the level of satisfaction and loyalty of XYZ Beauty Clinic consumers. The study used a cross-sectional design. The sampling technique used purposive sampling involving 152 respondents who were at least 17 years old and had visited at least twice in the last year. Data were processed quantitatively using SEM-PLS, Customer Satisfaction Index (CSI), and Customer Loyalty Index (CLI) to test the hypotheses and measure the level of consumer satisfaction and loyalty. The results indicated that consumer perception with low satisfaction and low loyalty are consumers who work as entrepreneurs, consumers who earn less than 5 million a month, as well as consumers who live in Tangerang and Bogor. The marketing mix that affects consumer satisfaction includes product, promotion, process, people, and physical evidence. Customer satisfaction affects customer loyalty. The level of customer satisfaction shows satisfactory results and the level of customer loyalty shows loyal results. Based on the research results, clinics are advised to prioritize consumer groups with low perceptions of satisfaction
Co-Authors -, Salsabila Aam Alamudi Abdul Aziz Nurussadad Abyan, Muhammad Fatih Achmad Fauzan Achsani, Noer Azham Adi Hadianto Adinna Astrianti Afendi, Farit M Agus M Soleh Agus M Soleh Agus M. Sholeh Agus Mohamad Soleh Agusta, Madania Tetiani Agwil, Winalia Aisyah, Nisa Nur Aji Hamim Wigena Akbar Rizki Akbar Rizki Akhilla, Kharismatul Zaenab Alfa Nugraha Pradana ALFIAN FUTUHUL HADI Alifviansyah, Kevin Alona Dwinata Alwinie, Ade Agusti Amanda, Nabila Tri Amatullah, Fida Fariha Amin, Toufiq Al Amir Abduljabbar Dalimunthe Anang Kurnia Andi Susanto Andrie Agustino Anggraeni, Kartika Novira Anggraini Sukmawati Ani Safitri Anik Djuraidah Anisa Nurizki Annisa Permata Sari, Annisa Permata Annissa Nur Fitria Fathina Anton Ferdiansyah Anwar Fajar Rizki Ardhani, Rizky Ardiansyah, Muhlis Arie Wahyu Wijayanto Arief Daryanto Arief Daryanto Arief Gusnanto Aris Yaman Aris Yaman Aristawidya, Rafika Aruddy Aruddy Aryasa, Komang Budi Asep Rusyana ASEP SAEFUDDIN Asfar Asrirawan, Asrirawan Audina, Delia Fitri Aulia Rizki Firdawanti Aunuddin Aunuddin Auzi Asfarian Ayu Sofia Azlam Nas Bagus Randhyartha Gumilar Bariq, Muhammad Shidqi Abdul Barokaturrizkia Ameliani Bayu Indrayana Bayu Pranata, Bayu Bayu Suseno Beny Mulyana Sukandar Billy Bimandra Adiputra Djaafara Bonar Marulitua Sinaga Budi Susetyo Budi Susetyo Bukhari, Ari Shobri Butar, Rupmana Br Cahya, Septa Dwi Carlya Agmis Aimandiga Cici Suhaeni Cici Suhaeni Cici Suhaeni Cintari, Nanda Putri Citra, Reza Felix Dani Al Mahkya Darwis Darwis Dede Dirgahayu Dede Dirgahayu Defri Ramadhan Ismana Deiby T Salaki Deni Achmad Soeboer Deri Siswara Desi Prabandari Kusuma Ningtyas Dessy Rotua Natalina Siahaan Dewi Margareth Lumbantoruan Dhanu Dhanu Saptowulan Dian Ayuningtyas Dian Handayani Dian Kusumaningrum Dito, Gerry Alfa Dwi Agustin Nuriani Sirodj Dwi Fitrianti Dwi Wahyu Triscowati Eko Ruddy Cahyadi Embay Rohaeti Endriani, Desy Erfiani Erfiani Erira, Salsa Rifda Erliza Noor Erwan Setiawan, Erwan Etis Sunandi EVI RAMADHANI EVITA PURNANINGRUM Fachry Abda El Rahman Fadhila Hijryani FAHREZAL ZUBEDI Fany Apriliani Farit M. Afendi Farit Mochamad Afendi Fauzi, Fatkhurokhman Ferdiansyah, Anton Ferdiansyah, Anton Fitri Mudia Sari Fitrianto, Anwar Frisca Rizki Ananda Galih Hedy Saputra Gerry Alfa Dito Ghiffary, Ghardapaty Ghaly Ginting, Victor Gumilar, Bagus Randhyartha Hanum Rachmawati Nur Hardiana Widyastuti Hari Wijayanto Hari Yanni, Meri Harianto Harianto Hartoyo Hartoyo Hartoyo Hazan Azhari Zainuddin Hendri Wijaya Hendria, Muhammad Herlin Fransiska Herlina Herlina Hidayat, Agus Sofian Eka Hidayat, Muhammad Hilman Dwi Anggana Hiola, Yani Prihantini I Made Sumertajaya I Wayan Mangku Idqan Fahmi Ilma, Hafizah Ilma, Meisyatul Ilmani, Erdanisa Aghnia Iman, Mutiara Nurul IMARA, FADIAH RETNO INA YATUL ULYA Indahwati Indonesian Journal of Statistics and Its Applications IJSA Intan Arassah, Fradha Irene Muflikh Nadhiroh Irfan Syauqi Beik Ismah, Ismah Ita Wulandari Itasia Dina Sulvianti Iwan Kurniawan Jaelani, Raditya Kamila, Sabrina Adnin Khairil Anwar Notodiputro Khairunnajah Khairunnajah Khairunnisa, Adlina Khikmah, Khusnia Nurul Kudang Boro Seminar Kusman Sadik Kusnaeni Kusnaeni, Kusnaeni Kusuma Ningtyas, Desi Prabandari La Surimi, La Laode Ahmad Sabil Leni Anggraini Susanti Lilik Noor Yuliati Limba, Syella Zignora Linda Karlina Sari Lisa Amelia Luky Adrianto Lukytawati Anggraeni M. Yunus Magfirrah, Indah Matualage, Dariani Megawati - Megawati Simanjuntak Meylisah, Eni Mohamad Agus Setiawan Muhammad Hendria Muhammad Ilham Abidin Muhammad Irfan Hanifiandi Kurnia Muhammad Nur Aidi Muhammad Subianto Muhammad Syafiq Muhammad Yusran Mukhamad Najib Murpraptomo, Saka Haditya Musthafa, Hafiz Syaikhul MY, Hadyanti Utami Nimmi Zulbainarni Nofrida Elly Zendrato Novian Tamara Nugraha, Adhiyatma Nur Aulia NUR HASANAH NURADILLA, SITI Nurfadilah, Khalilah Nurrahmaniah, Nurrahmaniah Oktaviani, Rina Pardomuan Robinson Sihombing Parwati Sofan, Parwati Pika Silvianti Popong Nurhayati Pratiwi, Windy Ayu Purnaningrum, Evita Purwanto, Arie Puspita, Novi Putra, I Gusti Ngurah Sentana Putri, Mega Ramatika Qalbi, Asyifah Rachma Fitriati Rahardi, Naufal Rahardiantoro, Septian Rahma Anisa Rahma Anisa Rahma Dany Asyifa Rahman, Gusti Arviana Rahmatulloh, Febriandi Rais Rere Kautsar Resiloy, Unique Desyrre A. Rhendy K P Widiyanto Riantika, Ines Rina Oktaviani Rini, Dyah Setyo Riska Yulianti, Riska Riza Indriani Rakhmalia Rizal Bakri Rizka Rahmaida Rizqi, Tasya Anisah ROCHYATI ROCHYATI Roy Sembel Sachnaz Desta Oktarina salsa bila Saptowulan Sarah Putri Sari, Jefita Resti Sentana Putra, I Gusti Ngurah Seta Baehera Setiabudi, Nur Andi Setiadi Djohar Setyowati, Silfiana Lis Sholeh, Agus M. Siregar, Indra Rivaldi Siskarossa Ika Oktora Sri Amaliya Suantari, Ni Gusti Ayu Putu Puteri Suhaeni, Cici Suhaeri, ⁠Bulan Cahyani Sukarna Sukarna Sunan, Muh. Suprayogi, Muhammad Azis Susanto, Andi Suseno Bayu Syam, Ummul Auliyah Syarip, Dodi Irawan Totong Martono Toufiq Al Amin Toufiq Al Amin Triscowati, Dwi Wahyu Tsabitah, Dhiya Ulayya Tsaqif, Denanda Aufadlan Ujang Sumarwan Ulfia, Ratu Risha Utami Dyah Syafitri Valentika, Nina Vera Maya Santi Virgie, Meriza Immanuela Wahida Ainun Mumtaza Wahyudi Setyo Wahyuni, Silvia Tri Waliulu, Megawati Zein Wawan Saputra Yani Nurhadryani Yanuari, Eka Dicky Darmawan Yenni Angraini Yoga Primanda Yopi Ariesia Ulfa Yudhianto, Rachmat Bintang Yuliani, Leny Zahra, Latifah Zaima Nurrusydah Zulhijrah Zulmi, Muhammad Indra