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All Journal Jurnal Matematika BIMASTER Proceedings of Annual International Conference Syiah Kuala University - Life Sciences & Engineering Chapter Epsilon: Jurnal Matematika Murni dan Terapan Jurnal Statistika Universitas Muhammadiyah Semarang Agrointek BAREKENG: Jurnal Ilmu Matematika dan Terapan Jambura Journal of Mathematics GERVASI: Jurnal Pengabdian kepada Masyarakat Sarwahita : Jurnal Pengabdian Kepada Masyarakat M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Variance : Journal of Statistics and Its Applications Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat Insan Cita Jurnal Pengabdian Kepada Masyarakat BERNAS: Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian kepada Masyarakat Nusantara Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Jurnal Forum Analisis Statistik Pattimura International Journal of Mathematics (PIJMath) Jurnal Pelayanan dan Pemberdayaan Masyarakat STATISTIKA Equiva Jurnal Pengabdian pada Masyarakat
Hendra Perdana
Universitas Tanjungpura
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PENERAPAN METODE ENTROPY DAN ELECTRE DALAM MENDUKUNG KEPUTUSAN PEMILIHAN INVESTASI SAHAM SYARIAH TERBAIK Fadhila, Aisya Raihan; Martha, Shantika; Perdana, Hendra
BIMASTER : Buletin Ilmiah Matematika, Statistika dan Terapannya Vol. 15 No. 1 (2026): Bimaster : Buletin Ilmiah Matematika, Statistika dan Terapannya
Publisher : Faculty of Mathematics and Natural Sciences Tanjungpura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/bbimst.v15i1.105964

Abstract

Investasi pada instrumen pasar modal syariah di Indonesia terus mengalami perkembangan yang signifikan seiring dengan meningkatnya jumlah saham syariah dan partisipasi investor setiap tahunnya. Salah satu tantangan utama dalam investasi saham syariah adalah menentukan alternatif saham yang tidak hanya sesuai dengan prinsip syariah, tetapi juga memiliki kinerja keuangan yang optimal. Penelitian ini bertujuan untuk menentukan saham syariah terbaik dengan menerapkan metode Multi-Criteria Decision Making (MCDM) berbasis Entropy dan ELECTRE. Data penelitian menggunakan 30 saham yang tergabung dalam Jakarta Islamic Index (JII) dengan tujuh kriteria penilaian berupa rasio keuangan, yaitu price to earnings ratio (PER), price to book value (PBV), earnings per share (EPS), return on equity (ROE), dividend yield (DY), debt to equity ratio (DER), dan current ratio (CR) berdasarkan laporan keuangan tahun 2024. Keberadaan outlier pada data asli mendorong dilakukannya preprocessing melalui standarisasi Z-Score dan transformasi nilai negatif ke positif untuk memenuhi prasyarat metode Entropy, dengan konsekuensi berkurangnya pengaruh outlier terhadap persebaran probabilitas kriteria. Metode Entropy digunakan untuk memperoleh bobot objektif kriteria berdasarkan distribusi informasi, sedangkan metode ELECTRE digunakan untuk melakukan proses perangkingan alternatif saham. Hasil penelitian menunjukkan urutan bobot kriteria dari tertinggi hingga terendah yaitu DER (0,2396), DY (0,2183), CR (0,2108), ROE (0,1384), EPS (0,1250), PBV (0,0366), dan PER (0,0346). Berdasarkan hasil perangkingan ELECTRE, saham TLKM memperoleh peringkat terbaik. Temuan ini menunjukkan bahwa kombinasi metode Entropy dan ELECTRE mampu memberikan dasar pengambilan keputusan yang sistematis dan objektif dalam pemilihan saham syariah.
EFEKTIVITAS PELATIHAN POWER BI DALAM MENINGKATKAN LITERASI DATA ADMIN SATU DATA KALIMANTAN BARAT Neva Satyahadewi; Evy Sulistianingsih; Shantika Martha; Nurfitri Imro'ah; Hendra Perdana; Wirda Andani; Ray Tamtama; Yuyun Eka Pratiwi; Muhammad Fikri; Pitriani; Annisa Auliarahmi; Nazwa Nursyifa; Yohanna Gabriel Richsita; Louis Putra Jaya; Jessica Audrey Valeria
Dianmas Bhakti: Jurnal Pengabdian pada Masyarakat Vol 3 No 1 (2026): Dianmas Bhakti: Jurnal Pengabdian pada Masyarakat
Publisher : LPPM Universitas Panca Bhakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54035/dianmas.v3i1.626

Abstract

This Community Service Program (PKM) aimed to enhance data literacy and information visualization skills among Satu Data administrators of local government agencies (OPD) through Microsoft Power BI training at the West Kalimantan Provincial Communication and Information Agency (Diskominfo). The program was implemented through preparation, face-to-face training, and evaluation stages using pre-test and post-test instruments. The training covered fundamental concepts of data analysis, data visualization techniques, and hands-on dashboard development using regional sectoral data. The results of the paired sample t-test analysis indicated a statistically significant improvement between participants’ pre-test and post-test scores, demonstrating the effectiveness of the training. Furthermore, analysis using Partial Least Squares Structural Equation Modeling (PLS-SEM) revealed that training material quality had a positive and significant effect on participants’ learning outcomes, while other supporting factors such as training duration, facilitator performance, and technical aspects did not show significant effects. These findings highlight that well-structured and relevant training materials play a critical role in improving participants’ competencies. Overall, the program contributed to strengthening analytical skills and supporting the implementation of the Satu Data Indonesia policy toward transparent and evidence-based data governance
ANALISIS RISIKO DAN RETURN SAHAM MENGGUNAKAN DOWNSIDE CAPITAL ASSET PRICING MODEL (DCAPM) PADA SAHAM IDX30 Hazwani Dhiya' Atiq Viatmaja; Hendra Perdana; Evy Sulistianingsih
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 20, No 1 (2026)
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/epsilon.v20i1.18510

Abstract

The Indonesian capital market, as an emerging market is characterized by high volatility and an asymmetric return distribution, making the Capital Asset Pricing Model (CAPM) less representative for measuring stock risk and return. This study aims to analyze the relationship between risk and return of IDX30 stocks using the Downside Capital Asset Pricing Model (DCAPM), which focuses on measuring risk from the downside perspective through the estimation of downside beta. The data used consist of daily stock closing prices, the market index, and the risk free rate (BI Rate) from January 2023 to September 2025. A total of 20 stocks that consistently remained in the IDX30 index throughout the observation period were selected as the sample and grouped into portfolios based on their downside beta levels, which were subsequently evaluated using the Omega Ratio. Downside beta was estimated by dividing the asset semicovariance by the market semivariance. The results indicate considerable variation in downside risk among IDX30 stocks. From a financial perspective, a higher downside beta is associated with a higher expected return as compensation for greater downside risk. Moreover, portfolios with higher downside beta can still exhibit relatively good performance, provided that they generate returns exceeding the target return. These findings suggest that the DCAPM and Omega Ratio can serve as effective tools for evaluating stock portfolio risk and performance under asymmetric market conditions.
OPTIMASI PORTOFOLIO SAHAM IDX30 MENGGUNAKAN HIERARCHICAL CLUSTERING METODE WARD DENGAN PEMBOBOTAN ALGORITMA GENETIKA Maria Artameivia Putri; Hendra Perdana; Evy Sulistianingsih
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 20, No 1 (2026)
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/epsilon.v20i1.18469

Abstract

Stock portfolio is an investment consisting of stocks from different companies with the expectation that if the price of one stock decreases, the price of another stock may increase. To optimize returns and minimize risks, an investment strategy through portfolio optimization is required. This study aims to analyze the implementation of hierarchical clustering using the Ward method with genetic algorithm weighting in optimizing the IDX30 stock portfolio. The Ward method is used to group stocks based on similarities in financial ratios, while the genetic algorithm is used to determine optimal investment weights. The data used consist of 28 stocks included in the IDX30 index during the period from February 2024 to January 2025, with 6 stocks meeting the criteria of having positive expected returns and positive financial ratios. The financial ratio variables used in this analysis are Earnings per Share (EPS), Return on Equity (ROE), Debt to Equity Ratio (DER), and Price Earnings Ratio (PER). Based on the analysis results, the optimal IDX30 stock portfolio consists of PT Charoen Pokphand Indonesia Tbk (CPIN), PT Indofood Sukses Makmur Tbk (INDF), PT Perusahaan Gas Negara Tbk (PGAS), PT Bukit Asam Tbk (PTBA), and PT United Tractors Tbk (UNTR), with investment allocations of 0.23% for CPIN, 50.37% for INDF, 49.16% for PGAS, 0.12% for PTBA, and 0.13% for UNTR. The portfolio produces an expected return of 0.00112 and a portfolio risk of 0.01340. However, this study does not perform sensitivity analysis on the genetic algorithm parameters; therefore, future research may evaluate solution stability through parameter sensitivity testing.
Application of Classification Data Mining Technique for Pattern Analysis of Student Graduation Data with Emerging Pattern Method Aditya Handayani; Neva Satyahadewi; Hendra Perdana
Pattimura International Journal of Mathematics (PIJMath) Vol 2 No 1 (2023): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol2iss1pp01-06

Abstract

Data mining has been applied in various fields of life because it is very helpful in extracting information from large data sets. Student graduation data is one example of data that can be extracted for information and become a recommendation. This study used a classification data mining technique to extract information from the student graduation data. The classification technique used was the Emerging Pattern method to search for patterns in the student graduation data. The data in this study were graduation data for students of the Statistics Study Program, Faculty of Mathematics and Natural Sciences, Tanjungpura University, from 2013-2018. The sample data used amounted to 186 records. Attributes used in this study include as many as four attributes, including gender, batch, GPA, and TUTEP scores. This research began by finding the class and frequency values obtained. It was continued by calculating each item set's support, growth rate, and confidence values. This study obtained the highest confidence value among all the attributes owned, namely 91% in the 2013 batch itemized list and the 2018 batch. Female students dominated the class attribute. TUTEP dominated the TUTEP value attribute with a score of 425, and the GPA attribute of 3.51-4.00 dominated the class with a confidence value of 60%.
Comparison of Adaboost Application to C4.5 and C5.0 Algorithms in Student Graduation Classification Yuveinsiana Crismayella; Neva Satyahadewi; Hendra Perdana
Pattimura International Journal of Mathematics (PIJMath) Vol 2 No 1 (2023): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol2iss1pp07-16

Abstract

Students become a benchmark used to assess quality and evaluate college learning plans. Therefore, students who graduate not on time can have an effect on accreditation assessment. The characteristics of students who graduate on time or not on time in determining student graduation can be analyzed using classification techniques in data mining, namely the C4.5 and C5.0 algorithms. The purpose of this study is to compare the application of the Adaboost Algorithm to the C4.5 and C5.0 Algorithms in the classification of student graduation. The data used is the graduation data of students of the Statistics Study Program at Tanjungpura University Period I of the 2017/2018 Academic Year to Period II of the 2022/2023 Academic Year. The analysis begins by calculating the entropy, gain and gain ratio values. After that, each data was given the same initial weight and iterated 100 times. Based on the classification results using the C5.0 Algorithm, the attribute that has the highest gain ratio value is school accreditation, meaning that the school accreditation attribute has the most influence in the classification of student graduation. The application of the Adaboost Algorithm to the C5.0 Algorithm is better than the C4.5 Algorithm in classifying the graduation of students of the Untan Statistics Study Program. The Adaboost algorithm was able to increase the accuracy of the C5.0 Algorithm by 12.14%. While in the C4.5 Algorithm, the Adaboost Algorithm increases accuracy by 10.71%.
Determination of the Annual Pension Fund Premium for Joint-Life Status Using the Aggregate Cost Method Syuradi syuradi; Neva Satyahadewi; Hendra Perdana
Pattimura International Journal of Mathematics (PIJMath) Vol 2 No 2 (2023): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol2iss2pp71-78

Abstract

A pension fund is one of the responsibilities of an institution or company for all employees during their working life. In pension fund insurance, several agreements must be agreed upon by the insured and the insurer for the agreement, namely the premium. The premium to be paid by the insured (employee) of the pension fund insurance must adjust to the income earned, so that the premium to pay does not burden the insured. This study aims to determine the annual pension fund premium amount that must pay use the Aggregate Cost method in the joint-life case. The case study uses information from a husband and wife as civil servants with a husband class III B and wife III A participating in a pension program with a retirement age limit of 58 years (r = 58). The husband (insured x) was 28 years old, and the wife (insured y) was 24 when they started working and joined the pension program. The result of calculating the value of the annual pension fund insurance premium that must pay use the Aggregate Cost method is Rp.41,440,163. If the husband's age is lower than the wife's (x=24, y=28), then the value of the premium paid is more significant than when the husband's age is higher than the wife's (x=28, y=24), which is IDR 41,594,217. That is because the husband's working period is more extended than the wife's, while the chance of death for men is higher than for women. Meanwhile, premiums producing if the husband and wife are of the same age, which is cheaper than when the husband and wife are of different ages
PENGELOMPOKAN PROVINSI DI INDONESIA BERDASARKAN FAKTOR PENYEBAB STUNTING DENGAN VALIDASI KORELASI COPHENETIC Andini, Syarifah; Perdana, Hendra; Imro'ah, Nurfitri
BIMASTER : Buletin Ilmiah Matematika, Statistika dan Terapannya Vol. 15 No. 2 (2026): Bimaster : Buletin Ilmiah Matematika, Statistika dan Terapannya
Publisher : Faculty of Mathematics and Natural Sciences Tanjungpura University

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

Abstract

Stunting merupakan gangguan pertumbuhan pada anak balita yang dipicu oleh defisiensi gizi yang tercermin dari panjang atau tinggi badan anak yang tidak sesuai dengan standar usianya. Hingga saat ini, stunting masih menjadi permasalahan kesehatan yang serius di Indonesia dengan karakteristik penyebab yang beragam antarwilayah. Penelitian ini bertujuan untuk mengelompokkan provinsi di Indonesia berdasarkan faktor penyebab stunting serta memvalidasi hasil pengelompokan menggunakan koefisien korelasi Cophenetic. Data yang digunakan merupakan data sekunder yang bersumber dari publikasi Survei Status Gizi Indonesia (SSGI) tahun 2024 dengan sepuluh variabel faktor penyebab stunting, meliputi akses air minum layak, akses sanitasi layak, kelengkapan imunisasi dasar, berat badan lahir rendah (<2500 gram), ASI eksklusif, prevalensi ISPA balita, ANC K4, konsumsi tablet tambah darah (≥90 tablet), bayi segera disusui kurang dari 60 menit setelah lahir, dan keragaman pangan minimal. Metode analisis yang digunakan adalah analisis klaster hierarki dengan metode Ward dan jarak Squared Euclidean. Hasil validasi menggunakan koefisien korelasi Cophenetic menghasilkan nilai sebesar 0,509, yang menunjukkan bahwa dendrogram cukup merepresentasikan jarak antarprovinsi pada data asli. Hasil analisis menghasilkan empat klaster provinsi dengan karakteristik yang berbeda. Klaster 1 merupakan wilayah dengan kondisi paling ideal dalam pencegahan stunting, klaster 2 mencerminkan wilayah dengan kondisi menengah, klaster 3 merupakan wilayah yang tergolong rentan dalam upaya pencegahan stunting, dan klaster 4 menunjukkan wilayah dengan kondisi paling kompleks dan paling rentan terhadap permasalahan stunting.
PERAMALAN INDEKS HARGA SAHAM GABUNGAN (IHSG) MENGGUNAKAN METODE ARIMAX-EGARCH Felisya, Tasya; Imro'ah, Nurfitri; Perdana, Hendra
BIMASTER : Buletin Ilmiah Matematika, Statistika dan Terapannya Vol. 15 No. 2 (2026): Bimaster : Buletin Ilmiah Matematika, Statistika dan Terapannya
Publisher : Faculty of Mathematics and Natural Sciences Tanjungpura University

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

Abstract

Indeks Harga Saham Gabungan (IHSG) merupakan gabungan beberapa saham di Indonesia yang dapat digunakan untuk mengetahui rata-rata pergerakan saham di Indonesia. Dibandingkan dengan indeks LQ45 dan IDX30 yang hanya mencakup saham tertentu, IHSG memiliki cakupan yang lebih luas dan mampu menggambarkan kondisi pasar saham. Namun, IHSG tidak menyajikan informasi harga saham secara individual. Pergerakan IHSG dipengaruhi oleh berbagai faktor, yaitu faktor internal dan eksternal. Salah satu faktor eksternalnya adalah harga minyak mentah Brent, yang digunakan sebagai salah satu acuan penetapan harga bahan bakar yang berlaku di Indonesia. Fluktuasi harga minyak dapat berdampak pada biaya operasional perusahaan, sehingga memengaruhi pergerakan IHSG. Oleh karena itu, diperlukan model yang mampu mempertimbangkan pengaruh faktor eksternal. Model ARIMAX digunakan untuk mengidentifikasi pengaruh harga minyak mentah Brent terhadap IHSG. Untuk mengatasi masalah varians yang tidak konstan digunakan model GARCH. Namun, karena GARCH belum mampu menangkap efek asimetris pada data, maka digunakan model EGARCH sebagai pengembangan yang lebih sesuai. Analisis volatilitas IHSG penting dilakukan karena dapat membantu investor dalam pengambilan keputusan serta pengelolaan risiko investasi. Penelitian ini bertujuan untuk memodelkan dan meramalkan harga IHSG menggunakan model ARIMAX-EGARCH. Data yang digunakan berupa harga penutupan harian IHSG dengan harga minyak mentah Brent sebagai variabel eksogen pada periode 2 Januari 2020 hingga 29 September 2025. Pemilihan model terbaik dipilih berdasarkan nilai AIC terkecil, dan akurasi peramalan dievaluasi menggunakan nilai MAPE. Hasil analisis menunjukkan bahwa model ARIMAX (5,0,5)-EGARCH (2,2) merupakan model terbaik karena nilai MAPE sebesar 0,77% yang menunjukkan bahwa model ini sangat baik untuk melakukan peramalan.
Co-Authors Adinda, Dian Tri Aditya Handayani Al Amin Alatin, Isam Aldien, Royan Gustio Alex Sander Almazmar, Giatul Khodijah Hodijah Andani, Wirda Andi Hairil Alimuddin Andini, Syarifah Anggi Putri Dewi Anggi, Muhamad Anis Fakhrunnisa Annisa Auliarahmi Annisa Fitri Antoni, Frans Xavier Natalius Apriliyani, Techa Aprizkiyandari, Siti Ariady Zulkarnain Arsyi, Fritzgerald Muhammad Assa Trissia Rizal Atikasari, Awang Atlantic, Virginnia Aulia Puteri Amari Azura, Tina Calissta, Leanna Belva Cesoria, Yola Zerlinda Dadan Kusnandar Dadan Kusnandar Dadan Kusnandar Dadan Zaliluddin Debataraja, Naomi Nessyana Dedi Rosadi Deni Wardani Dinda Lestari Dwi Nining Indrasari Dzakirah, Nasya Rabbi Eka Rizki Wahyuni Elga Fitaloka Endah Saraswi Ersawahyuni, Aisna Evi Noviani Evy Sulistianingsih Fadhila, Aisya Raihan Faizah, Putri Alya Nur Fajar, Arif Nur Fallah, Khalishah Ghina Febriani, Nindy Febriani, Rani Febriyanto, Ferdy Felisya, Tasya Fery Prastio Fidianty, Fadilla Firhan Januardi Firman Saputra Firnanda, Firnanda Fortuna, Nia Fitriana Gilang Habibie Gunawan, Sucipto Hafifah, Nanda Hapipah, Liza Darojatul Hariadi, Wahyudio Shaney Fikri Harnanta, Nabila Izza Hasanah, Kutsiatul Hasanuddin Hasanuddin Hazwani Dhiya&#039; Atiq Viatmaja Helmi Helmi Hidayat, Rani Lestari HUDA, NUR’AINUL MIFTAHUL Huriyah, Syifa Khansa Iman Sanjaya Imanni, Rahmania Andarini Hatti Imro'ah, Nurfitri IMRO’AH, NURFITRI Imtiyaz, Widad Indriani, Maria Meilinda Ira Mona Irwanto, Dicky Ismi Adam Jajad Sudrajat Jawani Jawani Jessica Audrey Valeria Juniarti, Leni Khabib Mustofa Laksono Trisnantoro Lilit Tamara Dinta Lisa Lestari Louis Putra Jaya M. Deny Hafizzul Muttaqin Ma’ruf, Ikhwan Maisarah Maisarah Margaretha, Ledy Claudia Maria Artameivia Putri Mariana Yopi Mariatul Kiftiah Martha, Shantika Marwalida Rachmadiar Maulida Amanasari Mega Tri Junika Mida Mida Millennia Taraly Misrawi Misrawi Muhamad Ikbal Muhammad Ahyar Muhammad fauzan Muhammad Fikri Muhardi Muhtadi, Radhi Mursyidah, Lailatul Mutiara Nurisma Rahmadhani Nabilah, Niken Aushaf Nanda Ayuni Nanda Shalsadilla Naomi Nessyana Debataraja Naomi Nessyana Debataraja Nazwa Nursyifa Neva Satyahadewi Novita, Irene Nugrahaeni, Indah Nur Asiska Nur Azmi Nurfitri Imro'ah Nurfitri Imro’ah Nurhanifa, Nurhanifa Nurin Hafizah Nurmaulia Ningsih Nurul Huda Padilah, Ariski Paisal Paisal Pinasari, Repi Pitriani Pitriani Pitriani Pranata Anggi Puji Ardiningsih Puspita, Risma Putri, Vinna Septyara Qalbi Aliklas Rafika Aufa Hasibuan Rahman, Tri Wanda Rahmania Andarini Hatti Imanni Rahmasari, Yulia Ramadhan, Nanda Ratna Nursariyani Ratna Sari Dewi Reni Unaeni Retnani, Hani Dwi Ria Fuji Astuti Rina Rina Risa Nofiani Risko, Risko Rivaldo, Rendi Rizki, Setyo Wira Robbiati, Dian Roeswandi, Irine Fajrin Rofatunnisa, Sifa Sadikin, Utin Azwa Sayhani Salsabila, Hana Samson Samson Santika Santika Sasqia Aklysta Antaristi Sesilisvana, Nevil Setyo Wir Rizki Setyo Wira Rizki Setyo Wira Rizki Setyo Wira Rizki Shantika Martha Shantika Martha Shantika Martha Silvia Andriany Sinaga, Steven Jansen Sindia, Eri Sintia Margun Siti Julaeha, Siti Siti Septiani Rahayu Putri Solly Aryza Suci Angriani Suhardi Suprianto, Okto Syuradi syuradi Tamtama, Ray Taraly, Inggriani Millennia Thariq Thariq Tiara, Dinda Titania Aurellia Trifaiza, Fadhela Wafiq Nurhaliza Wahyu Diyan Ramadana Wilda Ariani Wira Fujiyanto Enizar Wirda Andani Wirdha Eryani Yogi, Vinsensius Yohane, Novi Yohanna Gabriel Richsita Yonatan, Yulianus Yopi Saputra Yudhi Yumna Siska Fitriyani Yundari, Yundari Yundari, Yundari Yustosio, Darwis Yuveinsiana Crismayella Yuyun Eka Pratiwi Zahidah, Zahra