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All Journal EKSAKTA: Journal of Sciences and Data Analysis Jurnal Fisika Unand Variance : Journal of Statistics and Its Applications Jurnal Ilmiah Matematika International Journal of Electronics and Communications Systems Bulletin of Applied Mathematics and Mathematics Education Southeast Asian Business Review Jurnal Pendidikan MIPA Journal of Social Sciences and Technology for Community Service
Muthoharoh, Luluk
Unknown Affiliation
Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Physics

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Foreign Institutional Ownership and Dividend Policy Muthoharoh, Luluk; Setianto, Rahmat Heru
Southeast Asian Business Review Vol. 1 No. 1 (2023)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/sabr.v1i1.48977

Abstract

Increasing institutional investors in manufacturing companies encourage companies to be more wise in making financial decisions, including dividend policy. Dividend policy related to profits earned by the company will be distributed to shareholders in the form of dividends or saved as retained earnings for reinvestment purposes. This study aims to examine the effect of foreign institutional ownership on dividend policy. This research was conducted on manufacturing companies listed on the Indonesia Stock Exchange (IDX) during 2013-2017, with a total of 466 observations. The Generalized Method of Moment (GMM) logistic regression and dynamic panel data estimation model was used in this study, with the dependent variable being dividend policy and the independent variable being ownership of foreign institutions. The study shows that foreign institutional ownership has a positive effect on dividend policy.
Tour Recommendation System Based On User Interest and Surrounding Facilities in North Sumatera Using Simple Multi-Attribute Rating Technique With Dijkstra's Algorithm Muthoharoh, Luluk; Ahmad Luky Ramdani; Ira Safitri; Muhammad Dhoni Apriyadi
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 6, ISSUE 1, April 2025
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol6.iss1.art3

Abstract

In this study, we collected data on tourist attractions, tourist attractions utilities, on the island of Sumatra, especially in Toba and Samosir districts in North Sumatra Province. In this process, information was collected on 100 tourist destinations with the highest popularity based on Google Maps Review. To determine the interest of tourists, the SMART method is used to obtain the value of tourist interest in each tourist spot based on the weight determined on each criterion. Meanwhile, entropy is used to determine the value of facilities available at tourist attractions. The value represents the interest of tourists and the facilities available around the tourist attractions. The results of this research show that in the aspect of running time Dijkstra's algorithm is fast algorithms
Indonesian Consumer Price Index Forecasting Using Autoregressive Integrated Moving Average Ishak, Shahnaz Salsabila; Abednego, Michael; Sari, Dian Maya; Sabila, Viyonisa Syafa; Khoirunnisa, Khoirunnisa; Alvionita, Mika; Muthoharoh, Luluk
International Journal of Electronics and Communications Systems Vol. 3 No. 1 (2023): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v3i1.18252

Abstract

The Consumer Price Index is one of the indicators used to confirm financial success in inflation management. This study aims to help determine the CPI prediction value in Indonesia for the next twelve periods in a month using the ARIMA (Autoregressive Integrated Moving Average) method using the data from January 2015 to March 2022. The results obtained show that the best model that can be used for forecasting is the ARIMA model (2,1,2) with drift with Akaike's Information Criterion (AIC) values of 2190.84. The results of Indonesia's accurate CPI forecasting can be used to assess inflation management for policymaking in the context of controlling inflation.It can be concluded that Based on the analysis, the optimal ARIMA model for forecasting Indonesia's CPI is ARIMA (2,1,2) with drift, aiding in evaluating inflation management for policymaking
Analysis of Google Stock Prices from 2020 to 2023 using the GARCH Method Athaulloh, M Farhan; Mubarok, Husni Na’fa; Sharov, Sergii; Hati, Berliyana Kesuma; Muthoharoh, Luluk; Alvionita, Mika
International Journal of Electronics and Communications Systems Vol. 3 No. 2 (2023): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v3i2.20899

Abstract

This research focuses on Google's share price movements, considering their significant impact on the financial market, using Google's share price data from 2020 to 2023. The aim is to analyze error variance and forecast and provide valuable information to stockbrokers and investors. The ARMA model has shortcomings in dealing with volatility, so the GARCH model is used to overcome it. Research methods include financial data analysis, preprocessing, and modeling with GARCH. The rolling forecast method describes changes in price patterns over time. Evaluation using MAPE validates the prediction accuracy of the ARIMA model. The best model chosen with the most negligible AIC value criteria was the ARIMA(3,0,2)GARCH(1,1) model. The forecasting results show accurate stock price predictions with an average MAPE value of 20.7 percent. This research provides an essential basis for brokers and investors in making investment decisions based on a deep understanding of the dynamics of Google's share price movements in the above time frame.
GARCH Model IBM Stock Forecasting of Price Volatility Zamzami, Balqis Dwian Fitri; Sihombing, Ericson Chandra; Kartika, Veni Zahara; Biran, Christian Arvianus Nathanael; Muthoharoh, Luluk; Sitinjak, Mika Alvionita
International Journal of Electronics and Communications Systems Vol. 4 No. 1 (2024): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v4i1.22866

Abstract

Risk and volatility are two related factors in research regarding capital markets. Many factors influence the movement of shares and indices. Volatility is common and affects risk assessment. Stock price volatility is an important aspect of understanding market behavior, with high volatility reflecting rapid and unstable price fluctuations. This research investigates the GARCH model in assessing volatility on the IBM Stock Exchange. The method employed was the symmetric GARCH model. It focuses on univariate analysis using the GARCH econometric model. The GARCH model allows modeling stock price variance over time based on the assumption that the variance was influenced by past stock price variance. The stages of this research were (1) data collection, (2) data pre-processing, and (3) forecasting model implementation. The best model obtained was ARMA(4,2)-GARCH(5,6) with an AIC value of 4.1017. A lower AIC value indicates that the model explains the data better or more optimally. A diagnostic test found that the model was adequate because the residual distribution followed a straight line, which means it was normally distributed.
Text Mining Customer Feedback: An Agglomerative Clustering Approach to Service Optimization Muthoharoh, Luluk
International Journal of Electronics and Communications Systems Vol. 5 No. 1 (2025): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v5i1.27188

Abstract

The increasing volume of customer support tickets in the e-commerce industry creates significant challenges in terms of efficiently managing unstructured text data. Traditional manual categorization methods are no longer efficient or scalable in managing well with growing data. This study proposes a text mining framework that integrates Natural Language Processing (NLP) techniques with Agglomerative Hierarchical Clustering (AHC) to automatically group customer support tickets based on their textual content similarity. The framework includes preprocessing (cleaning, tokenization, stopword removal, and lemmatization), followed by feature extraction using Term Frequency–Inverse Document Frequency (TF-IDF), and dimensionality reduction using Principal Component Analysis (PCA). The clustered data is then visualized through dendrograms and evaluated using silhouette scores to determine the optimal number of clusters. Using a real-world dataset of 8.469 support tickets, the framework identified an optimal two-cluster configuration, distinguishing between general inquiries and specific error-related complaints. Unlike previous studies by using K-Means or DBSCAN, this framework leverage the hierarchical structure to capture nuanced textual similarities without requiring cluster number in the beginning. It also introduces integrated for evaluation and visualization pipeline tailored for operational customer use. However, because AHC has high computational complexity, this approach is more suitable for daily clustering batches than for real-time processing. Alternatives such as Mini-Batch K-Means also need to be considered for more efficient implementation. This study contributes to the development of an automated triage system and strategies for improving customer experience in digital platforms
Digital-Based Physics Pocket Book Design with Short Counting Methods for Junior High School Students Yanti, Fitri April; Kristiawan, Muhammad; Riastuti, Reny Dwi; Muthoharoh, Luluk; Noperi, Hendri
Jurnal Pendidikan MIPA Vol 23, No 3 (2022): Jurnal Pendidikan MIPA
Publisher : FKIP Universitas Lampung

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

Abstract

This study aims to design a digital-based physics pocket book with a short calculation method for junior high school students. This type of research and development is used in this study. At the design stage, we selected the ADDIE model. The design phase includes: the analysis phase, the stage design, the stage of development. Research data obtained by reviewing the curriculum, interviews, and validation questionnaires. Class VII, VIII, IX students, as many as 9 people, became the subject of a limited trial in this study. Data analysis was carried out by reviewing curriculum content, descriptive interview results, and quantitative analysis for validation. The results showed that the design of a digital-based physics pocket book with a short calculation method was valid and could be used by Junior high school students.Keywords: digital book, pocket book, short count method, physics learning.DOI: http://dx.doi.org/10.23960/jpmipa/v23i3.pp1030-1039
Penerapan Program Software Matlab Dalam Memecahkan Permasalahan Rangkaian Listrik: Dinamika Sistem Kapasitor Dan Induktor (Prinsip Nilai Dan Vektor Eigen) Muthoharoh, Luluk; Pamungkas, Muhammad Putra; Sari, Reni Permata
Jurnal Fisika Unand Vol 10 No 3 (2021)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jfu.10.3.303-309.2021

Abstract

Matlab software was applied in solving physics cases in electronics using value calculation programs and Eigenvectors. The physics case solved is an moving oscillator circuit consisting of five capacitors and four inductors. The purpose of this program is to determine the value and the Eigenvectors that can be obtained. The method used is to utilize the problem of values and Eigenvectors in the Matlab program. In the case of oscillator motion, each capacitor's size and inductor system have been determined according to the system.. The equation of motion for the capacitor and inductor system is reviewed at each point of the inductor and the function used is  called the ansatz function, then differentiated twice concerning time. By using the Matlab program application, the results obtained show that by using eig (Eigen) command the Matlab program can accurately show the results of running (execution) values and Eigenvector.
ARCH MODEL FOR FORECASTING BCA BANK STOCK PRICE VOLATILITY Surya, Annisa Cahyani; Ariyanto, Adisty Syawalda; Napitupulu, Leonard Andreas; Sihaloho, Ryantoni; S, Mika Alvionita; Muthoharoh, Luluk
VARIANCE: Journal of Statistics and Its Applications Vol 7 No 2 (2025): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol7iss2page147-154

Abstract

This research analyzes the Autoregressive Conditional Heteroskedasticity (ARCH(p) model to predict the BCA Bank share price in the range of January 2013 to November 2023. BCA Bank's share price, as one of the shares traded on the Indonesian Stock Exchange, requires accurate volatility modeling. Researchers use the ARIMA(0,1,2) model as the initial approach, but because of heteroscedasticity, they apply the ARCH(8) model to overcome it. The results show that the ARCH(8) model performs best, with the lowest AIC values for volatility. BCA Bank's daily stock price as of December 1, 2023, showed high volatility, signaling significant risk to investors.
Seasonal Forecasting of Ferry Passenger Demand for Operational Planning: Evidence from Bakauheni Port, Indonesia Abdullah, Khoirul Mizan; Muthoharoh, Luluk; Satria, Eggie; Neliyana, Rahma; Presilia, Presilia; Khoarizmy, Gymnastiar Al; Muslim, Anwar; Safitri, Ira
International Journal of Electronics and Communications Systems Vol. 5 No. 2 (2025): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v5i2.26694

Abstract

Forecasting ferry passenger numbers is essential for efficient port operations and resource planning. This study applies the Seasonal Autoregressive Integrated Moving Average (SARIMA) model to forecast monthly passenger volumes at Bakauheni Port, Lampung. The SARIMA (2,1,1)(0,1,1)₁₂ model was selected for its ability to capture trend and seasonal patterns effectively. Diagnostic checks confirmed the model's adequacy, and validation yielded a MAPE of 11.47 percent, indicating 88.53 percent accuracy. These results show that the SARIMA model offers reliable predictive performance and can support data-driven decisions in scheduling, resource allocation, and service optimization. These results demonstrate that the developed SARIMA model possesses reliable predictive performance and can serve as a practical tool for supporting operational decision-making. The model can help this port authorities and managers optimize service provision, allocate resources more efficiently, and respond proactively to anticipated changes in passenger volume, thereby improving overall port performance and customer satisfaction in the future. Although it does not incorporate external factors, the model provides a solid foundation for future improvements and research.
Co-Authors Abdullah, Khoirul Mizan Abednego, Michael Ahmad Luky Ramdani Alvionita, Mika Ariyanto, Adisty Syawalda Astuti, Rohmi Dyah Athaulloh, M Farhan Bellini, Yustida Biran, Christian Arvianus Nathanael Dian Maya Sari Fitri April Yanti, Fitri April Hati, Berliyana Kesuma Hendri Noperi Ira Safitri Irawati, Febri Dwi Ishak, Shahnaz Salsabila Kartika, Veni Zahara Khoarizmy, Gymnastiar Al Mika Alvionita Sitinjak Mochammad Imron Awalludin Mubarok, Husni Na’fa Muhammad Dhoni Apriyadi Muhammad Kristiawan Muslim, Anwar Nadia Fitri Yani Napitupulu, Leonard Andreas Neliyana, Rahma Nurmadani, Vina Pamungkas, Muhammad Putra Presilia, Presilia Rahmat Heru Setianto Ramdani, Ahmad Luky Randa, Dimas Dwi Reny Dwi Riastuti Sabila, Viyonisa Syafa Sari, Reni Permata Satria, Ardika Satria, Eggie Sharov, Sergii Sihaloho, Ryantoni Sihombing, Ericson Chandra Sitinjak, Mika Alvionita Sukma, Yoga Aji Surya, Annisa Cahyani Tirta Setiawan, Tirta Winardi, Abdy Zamzami, Balqis Dwian Fitri