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All Journal JURNAL SISTEM INFORMASI BISNIS TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Daya Matematis Jurnal Manajemen Teori dan Terapan JOIN (Jurnal Online Informatika) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Equilibrium: Jurnal Ilmiah Ekonomi, Manajemen dan Akuntansi CARADDE: Jurnal Pengabdian Kepada Masyarakat Indonesian Journal of Learning Education and Counseling EDUKATIF : JURNAL ILMU PENDIDIKAN Jurnal Jamu Indonesia MABIS: Manajemen dan Bisnis Celebes Computer Science Journal Journal of Applied Science, Engineering, Technology, and Education Mattawang: Jurnal Pengabdian Masyarakat LOSARI: Jurnal Pengabdian Kepada Masyarakat Jurnal Visi Pengabdian Kepada Masyarakat ARRUS Journal of Social Sciences and Humanities Seminar Nasional Pengabdian Kepada Masyarakat Jurnal Ilmiah Ilmu Terapan Universitas Jambi Literasi: Jurnal Pengabdian Masyarakat dan Inovasi Journal of Artificial Intelligence and Digital Business Seminar Nasional Hasil Penelitian LP2M UNM Maneggio Indonesian Journal of Jamu Indonesian Journal of Statistics and Its Applications
Rizal Bakri
(1) Statistics Research Group, STIEM Bongaya, Jl. Mappaoudang No. 28, Makassar, 90223, Indonesia; (2) Department Of Digital Business, Universitas Negeri Makassar, Jl. Pendidikan No. 1, Makassar, 90222, Indonesia
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KUALITAS LAYANAN DAN BRAND IMAGE TERHADAP LOYALITAS NASABAH DIMEDIASI OLEH KEPUASAAN NASABAH Niken Probondani Astuti; Rizal Bakri; Irish Fiadyanti Indi Syafira
Equilibrium : Jurnal Ilmiah Ekonomi, Manajemen dan Akuntansi Vol 12, No 2 (2023): September
Publisher : Lembaga Penerbitan dan Publikasi Ilmiah (LPPI) Universitas Muhammadiyah Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35906/equili.v12i2.1603

Abstract

AbstrakPersaingan dalam industri perbankan sangat ketat, tidak terkecuali Bank BUMN yang harus berebut market share dengan bank-bank pemain lama dan pendatang baru. Oleh karena itu, mereka harus menekankan pada kualitas layanan sehingga bank dapat menarik calon nasabah untuk loyal. Ketika kualitas pelayanan menjadi prioritas maka bank sudah memenuhi standar pelayanan sehingga tercipta kepuasan nasabah yang akhirnya nasabah akan menjadi loyal. Penelitian ini bertujuan untuk mengetahui pengaruh Kualitas Layanan dan Brand Image terhadap Loyalitas Nasabah yang dimediasi oleh Kepuasan Nasabah pada PT. Bank BRI Kantor Cabang Somba Opu. Pengumpulan data menggunakan data primer yang diperoleh dari kuesioner dengan menggunakan teknik Stratified Sampling. Populasinya adalah seluruh nasabah tabungan Britama sejumlah 243.880 orang, sedangkan sampel yang diambil berjumlah 96 orang. Metode analisis menggunakan teknik analisis jalur. Hasil menunjukkan bahwa hipotesis yang diajukan untuk variabel Kualitas Layanan terhadap Loyalitas Nasabah yang dimediasi oleh Kepuasan Nasabah tidak diterima karena menunjukkan hasil hipotesis yang positif tapi tidak signifikan. Untuk variabel Brand Image terhadap Loyalitas Nasabah yang dimediasi oleh Kepuasan Nasabah diterima karena menunjukkan hasil positif signifikan.Kata Kunci: Kualitas Layanan, Brand Image, Loyalitas Nasabah, Kepuasan NasabahAbstractCompetition in the banking industry is very tight, including state-owned banks, which have to compete for market share with old and newcomer banks. Therefore, they must emphasize service quality so that banks can attract potential customers to be loyal. When service quality is a priority, the bank meets service standards so that customer satisfaction is created, which in turn customers will become loyal. This study aims to determine the effect of Service Quality and Brand Image on Customer Loyalty which is mediated by Customer Satisfaction at PT. Bank BRI Somba Opu Branch Office. Data collection uses primary data obtained from questionnaires using Stratified Sampling techniques. The population is all Britama savings customers totaling 243,880 people, while the sample taken is 96 people. The method of analysis uses path analysis techniques. The results show that the hypothesis proposed for the variable Service Quality on Customer Loyalty which is mediated by Customer Satisfaction is not accepted because it shows a positive but not significant hypothesis. The Brand Image variable on Customer Loyalty which is mediated by Customer Satisfaction is accepted because it shows significant positive results.Keywords: Service Quality, Brand Image, Customer Loyalty, Customer Satisfaction
The Role of Dividend and Debt Policy in Increasing Firm Value in the Food and Beverage Subsector: An Empirical Analysis on the Indonesia Stock Exchange Probondani Astuti, Niken; Nurkhalifa, Nurkhalifa; Bakri, Rizal
Maneggio Vol. 1 No. 3 (2024): Maneggio-Juni
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/qjs8pn22

Abstract

This study was conducted to determine how debt decisions and dividend policies impact the value of companies in the food & beverage industry listed on the Indonesia Stock Exchange. The sample selection used a purposive sampling method with the criteria of 35 companies in the food & beverage sub-sector that distributed cash dividends from 2018 - 2022. To perform this analysis, Eviews 12 was used. This includes estimating panel data regression equation models, classical assumption testing, statistical analysis, and hypothesis testing. This study finds that debt policy has a negative and significant impact on company value, while dividend policy has a positive and significant impact
Pelatihan dan Pendampingan Penyusunan Tugas Akhir menggunakan Berbagai Tools AI Bakri, Rizal; Hasbiyadi, Hasbiyadi; Astuti, Niken Probondani
CARADDE: Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 1 (2024): Agustus
Publisher : Ilin Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31960/caradde.v7i1.2519

Abstract

This activity aims to develop and implement a training and mentoring program for students to prepare their final assignments by utilizing various artificial intelligence (AI) tools. The AI tools used include ChatGPT for data analysis, Perplexity for compiling text, Mendeley for references, Spinner.id for paraphrasing, and Turnitin for checking plagiarism. Implementation methods include offline workshops and individual consultation sessions. Students are introduced to various AI tools through intensive training sessions that include compaction of usage, practical exercises, and direct assistance in applying these tools to their final assignments. The results of the activities showed a significant increase in the quality of students' final assignments. The use of AI tools facilitates the processes of data analysis, text preparation, reference management, content paraphrasing, and plagiarism checking. Students can complete final assignments more efficiently and reduce stress levels. Therefore, the use of AI in preparing final assignments offers an effective solution to overcome various obstacles faced by students. This training and mentoring program is highly recommended for acceptance by higher education institutions to support students in completing their final assignments with better quality.
Evaluating Random Forest Algorithm in Educational Data Mining: Optimizing Graduation on-time prediction using Imbalance Methods Rizal Bakri; Niken Probondani Astuti; Ansari Saleh Ahmar
ARRUS Journal of Social Sciences and Humanities Vol. 4 No. 1 (2024)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/soshum2449

Abstract

The study aims to evaluate the performance of Random Forest algorithms in data mining education by optimizing graduation on-time (GOT) predictions using imbalanced data methods. Methods used to handle imbalanced data include random under-sampling (RUS), random over-sampling (ROS), hybrids of RUS and ROS, synthetic minority over-sampling techniques for nominal classes (SMOTE-NC), and hybrids of SMOTE-NC and RUS. After applying these methods, studies analyze their performance on training and testing data. The research findings show that on training data, the RUS-ROS hybrid showed the best performance compared to other methods, while the SMOTENC and RUS hybrid techniques showed the best performance on testing data based on AUC values. The research showed that the use of an imbalanced data method significantly improved the ability of Random Forest algorithms to predict graduation on time (GOT) in the context of educational data. We discuss the implications for educational data mining applications and provide suggestions for future research.
Optimalisasi Pemahaman Akuntansi Perbankan bagi Mahasiswa Slow Learner melalui Role-Playing dengan Bantuan Software Bank Simulator Astuti, Niken Probondani; Wiyana, Anim; Bakri, Rizal
EDUKATIF : JURNAL ILMU PENDIDIKAN Vol 6, No 6 (2024): December
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/edukatif.v6i6.7776

Abstract

Pembelajaran akuntansi perbankan, khususnya bagi mahasiswa slow learner, memerlukan pendekatan yang mampu menjembatani kesenjangan pemahaman konsep dan keterampilan praktis. Penelitian ini bertujuan untuk mengevaluasi efektivitas model pembelajaran berbasis role-playing yang dikombinasikan dengan penggunaan software bank simulator dalam meningkatkan hasil belajar praktikum akuntansi perbankan. Penelitian dilakukan menggunakan metode kuasi-eksperimen dengan desain pretest-posttest pada 23 mahasiswa slow learner di STIEM Bongaya. Instrumen yang digunakan meliputi tes tertulis untuk mengukur pemahaman konseptual dan rubrik penilaian praktikum untuk mengevaluasi keterampilan operasional. Hasil penelitian menunjukkan peningkatan signifikan pada skor rata-rata pretest (55,4) menjadi posttest (78,3) dengan uji paired t-test menghasilkan nilai t=−12,34t = -12,34t=−12,34 dan p<0,001p < 0,001p<0,001. Analisis kuesioner kepuasan mahasiswa menunjukkan rata-rata skor tinggi pada aspek keterlibatan (4,5) dan relevansi materi (4,6), yang mengindikasikan metode ini relevan dan mendukung proses pembelajaran secara aktif. Temuan ini menunjukkan bahwa integrasi role-playing dan bank simulator tidak hanya meningkatkan pemahaman teoritis, tetapi juga keterampilan praktis yang relevan dengan dunia kerja. Penelitian ini memberikan kontribusi pada pengembangan metode pembelajaran praktikum yang inklusif untuk mahasiswa dengan kebutuhan khusus. Implementasi model serupa di mata kuliah lain dan optimalisasi perangkat lunak untuk mendukung interaksi lebih lanjut direkomendasikan untuk penelitian lanjutan.
Empowering the Manimbahoi Village Community through Digital Marketing Training: Pemberdayaan Masyarakat Desa Manimbahoi melalui Pelatihan Digital Marketing Ahmar, Ansari Saleh; Rais, Zulkifli; Bakri, Rizal; Asmar, Asmar
Mattawang: Jurnal Pengabdian Masyarakat Vol. 5 No. 3 (2024)
Publisher : Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.mattawang3049

Abstract

This training was held in the Manimbahoi Village Meeting Room, Parigi District, Gowa Regency, South Sulawesi Province on August 31, 2023. Participants in this training were young people from Karang Taruna, with the aim that the community, especially young people in Manimbahoi Village, could understand the importance of digital marketing as an effort to market Manimbahoi coffee products not only in the Parigi District area but also to the National area. This community service activity went smoothly and as expected. The results of this service show that there has been an increase in the abilities and knowledge of the village community from not knowing to knowing about digital marketing for coffee marketing. Abstrak Pelatihan ini dilaksanakan di Ruang Pertemuan Desa Manimbahoi, Kecamatan Parigi, Kabupaten Gowa, Provinsi Sulawesi Selatan pada tanggal 31 Agustus 2023. Peserta dari pelatihan ini adalah pemuda karang taruna, dengan tujuan warga masyarakat khususnya pemuda di Desa Manimbahoi dapat memahami tentang pentingnya digital marketing sebagai upaya untuk memasarkan produk kopi Manimbahoi bukan hanya di daerah Kecamatan Parigi tetapi bisa ke kawasan Nasional. Kegiatan pengabdian ini berjalan lancar dan sesuai dengan yang diharapkan. Hasil dari pengabdian ini, terlihat bahwa terjadi peningkatan kemampuan dan pengetahuan masyarakat desa dari tidak tahu menjadi tahu tentang digital marketing untuk pemasaran kopi.
STUDY ON EMD METHOD FOR PREDICTING THE PRICE OF CURLY RED CHILI IN INDONESIA Zilrahmi Zilrahmi; Hari Wijayanto; Farit M Afendi; Rizal Bakri
Indonesian Journal of Statistics and Applications Vol 4 No 2 (2020)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v4i2.600

Abstract

The fluctuations of curly red chili price affect the inflation rate in Indonesia. So that, the basic characteristics of price movement and correctly prediction for curly red chili price become concern in various studies. Empirical Mode Decomposition (EMD) method helps to examine behavioral characteristics of curly red chili prices in Indonesia easily. Ensemble EMD (EEMD) and modified EEMD are the decomposition method of time series which is development of EMD method. The decomposed data with EMD methods can also used for price forecast. The forecasting with ARIMA and trend polynomial performed to assess the effect of decomposition with EMD methods for forecast stability of curly red chili price in Indonesia under various conditions. The results show the most influence factor for price fluctuation of curly red chili in Indonesia is season and growing season. In this case, the ability of a decomposition method to produce the actual components that describe the pattern of data signals affect the accuracy of the predicted value obtained using the model. The predicted value using the decomposed data by modified EEMD always better than EEMD on the overall condition.
A New Framework for Dynamic Educational Marketing Segmentation in Student Recruitment: Optimizing Fuzzy C-Means with Metaheuristic Techniques Bakri, Rizal; Sobirov, Bobur; Astuti, Niken Probondani; Ahmar, Ansari Saleh; Singh, Pawan Kumar
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 3 (2025): June 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i3.6515

Abstract

An effective educational marketing strategy requires accurate school segmentation to enhance new student recruitment. Traditional segmentation methods such as K-means are often used, but they have limitations in capturing the flexibility of school characteristics. Fuzzy C-Means (FCM) offers a more adaptive approach by allowing each school to simultaneously have a degree of membership in several clusters. However, the performance of FCM highly depends on determining parameters such as the number of clusters (k) and the level of fuzziness (m), which are not always optimal when determined manually. This study develops a new framework for dynamic educational marketing segmentation in student recruitment by optimizing FCM using three metaheuristic techniques: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Differential Evolution (DE). Performance was evaluated using the Fuzzy Silhouette Index (FSI). The experimental results showed that DE yielded the best results with the highest FSI value (0.8023), producing eight main clusters based on the Recency, Frequency, and Monetary (RFM) model. Based on the clustering results, a personalized and adaptive marketing strategy was designed to enhance the effectiveness of student recruitment. The proposed framework enhances segmentation accuracy and supports the implementation of dynamic data-driven marketing in the context of higher education. This study also opens new directions for educational data mining research and machine-learning-based marketing strategies.
Optimizing Machine Learning Models for Graduation on Time Prediction: A Comparative Study with Resampling and Hyperparameter Tuning Bakri, Rizal; Alam, Syamsu; Astuti, Niken Probondani; Bakhtiar, Muhammad Ilham
JOIN (Jurnal Online Informatika) Vol 10 No 2 (2025)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v10i2.1590

Abstract

Timely graduation prediction is a crucial issue in higher education, especially when academic, demographic, and behavioral factors interact in complex ways. However, many previous studies rely on default machine learning (ML) parameters and fail to consider the class imbalance problem, leading to suboptimal predictions. This study aims to build a comprehensive framework to evaluate the effectiveness of seven ML algorithms, which are AdaBoost, K-Nearest Neighbors, Naïve Bayes, Neural Network, Random Forest, SVM-RBF, and XGBoost, for predicting graduation on time by incorporating five resampling techniques and hyperparameter tuning. Resampling methods include Random Undersampling (RUS), Random Oversampling (ROS), SMOTENC, and two hybrid approaches (RUS-ROS and SMOTENC-RUS). Hyperparameter tuning was conducted using Grid Search, and model performance was evaluated through cross-validation and hold-out methods. The results show that Random Forest combined with RUS-ROS achieved the best performance, with an average metric score of 0.948. Statistical analysis using PERMANOVA (p = 0.009) and Bonferroni's post-hoc pairwise tests confirmed significant differences between certain models. This study contributes to the educational data mining literature by demonstrating that combining resampling and hyperparameter tuning improves classification performance in imbalanced educational datasets.
THE IMPACT OF DISTANCE ON WILLINGNESS TO EAT OUT: EVIDENCE FROM SAMARKAND, UZBEKISTAN Makhmadieva, Charos; Turdibekov, Khasan; Amiriddinova, Muslima; Toyirova, Shokhista; Yuldosheva, Latofat; Mahmudova, Zarrina; Abdukhamidov, Sarvar; Makhmudova, Aziza; Rofeeva, Rukhshona; Vafokulova, Mekhruza; Bakri, Rizal; Sobirov, Bobur
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 9 No. 4 (2025): Volume 9, Nomor 4, December 2025
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v9i4.43200

Abstract

This study investigates the determinants influencing participation in gastronomic tourism in Samarkand, Uzbekistan, focusing on the role of distance, price satisfaction, and demographic characteristics. Using data collected from 303 respondents, logistic regression and decision tree analyses were applied to assess key behavioral predictors of culinary travel. The results reveal that distance is the most significant factor influencing willingness to engage in gastronomic tourism—individuals willing to travel farther are substantially more likely to seek authentic food experiences. In contrast, satisfaction with food prices and demographic factors such as age, gender, and expenditure levels were found to be statistically insignificant. These findings highlight that logistical accessibility outweighs demographic variables in shaping tourism participation. The study contributes to the literature by providing empirical evidence from an emerging destination, emphasizing the importance of mobility and access in gastronomic decision-making. Practical implications include the need for policymakers to improve transportation infrastructure, enhance culinary destination visibility, and promote authentic local food experiences. By strengthening these elements, Uzbekistan can better position itself as a prominent culinary tourism destination in Central Asia. The research also opens opportunities for future studies to explore psychological, cultural, and digital factors influencing food tourism behavior.
Co-Authors Abdukhamidov, Sarvar Ahmar, Ansari Saleh Amiriddinova, Muslima Andika Saputra Andika Saputra ANDIKA SAPUTRA Ardiansyah Halim Asfar Asmar Asmar, Asmar Astuti, Niken Probondani Bagus Sartono Data, Umar Farit M Afendi Farit Mochamad Afendi Fauzi, Muhammad Fitroh Halim, Ardiansyah Hamzah, Muh. Qardawi Hari Wijayanto Hari Wijayanto Hari Wijayanto Hartoto Hartoto Hartoto Hartoto Hasbiyadi, Hasbiyadi Hasyim Mochtar Hazan Azhari Zainuddin Irish Fiadyanti Indi Syafira Islamiah, Farida Laode Ahmad Sabil Mahmudova, Zarrina Makhmadieva, Charos Makhmudova, Aziza Muhammad Ilham Bakhtiar Muhammad Nusrang Nabila Putri Fiamanila Niken Probondani Astuti Niken Probondani Astuti Niken Probondani Astuti Niken Probondani Astuti Trisutomo Nur Salam Nurjakia Nurjakia Nurkhalifa, Nurkhalifa Nurlaely Razak Probondani Astuti, Niken Radja, Muh. Jusuf Rahmatullah Ramlan Mahmud Razak, Nurlaely Rofeeva, Rukhshona Singh, Pawan Kumar Sobirov, Bobur Syam, Agus SYAMSU ALAM Tafsir, Muhammad Toyirova, Shokhista Turdibekov, Khasan Umar Data Vafokulova, Mekhruza Valentino Aris, Valentino Wiyana, Anim Yuldosheva, Latofat Zilrahmi, Zilrahmi Zulkifli Rais