Article Per Year (5 Year)
p-Index From 2019 - 2024
1.733
P-Index
This Author published in this journals
All Journal J@TI (TEKNIK INDUSTRI) Jurnal Optimasi Sistem Industri PSYMPATHIC Komunikologi: Jurnal Pengembangan Ilmu Komunikasi dan Sosial Jurnal Statistika dan Matematika (Statmat) Jurnal Riset Statistika Bandung Conference Series: Statistics Schema: Journal of Psychological Research STATISTIKA
Dwi Agustin Nuriani Sirodj
Program Studi Statistika, FMIPA, Universitas Islam Bandung
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Social Sciences Other

Published : 16 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 16 Documents
Search

 1   2 
Vaksinasi Covid-19 di Media Sosial Twitter; Tinjauan Content dan Social Network Analysis Vici Sofianna Putera; Dwi Agustin Nuriani Sirodj; Rizka Hadian Permana
Komunikologi: Jurnal Pengembangan Ilmu Komunikasi dan Sosial Vol 5, No 2 (2021)
Publisher : Fakultas Ilmu Sosial UIN Sumatera Utara Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/komunikologi.v5i2.9771

Abstract

Abstrak Tujuan dari penelitian ini diantaranya untuk mengetahui narasi yang dibangun dalam percakapan di media sosial; mengetahui efektivitas penyebaran informasi yang dilakukan berdasarkan tagar yang #vaksin; dan memetakan polarisasi sikap masyarakat terhadap vaksin COVID-19. Metode yang digunakan adalah content analysis dan juga social network analysis dari data percakapan di media sosial Twitter dari tanggal 12 Januari 2021 sampai dengan 3 Februari 2021. Narasi yang dibangun dalam percakapan di media sosial Twitter terkait dengan tagar #vaksin adalah 1) Penggunaan tokoh sebagai role model perilaku untuk mengikuti program vaksin; 2) Tata cara pendaftaran vaksin; 3) Urgensi vaksinasi di tengah pandemi oleh tokoh agama; 4) Narasi vaksin berbayar. Efektivitas pesan yang disampaikan dalam percakapan di media sosial berdasarkan analisis jaringan menunjukkan bahwa penyebaran pesan tidak terlalu luas. Gencarnya kampanye vaksin menunjukkan perubahan sikap yang lebih positif terhadap vaksin itu sendiri.AbstractThe aims of this research are to find out the narrative that is built in conversations on social media; find out the effectiveness of information dissemination based on the #vaccine hashtag; and polarization of public attitudes towards the COVID-19 vaccine. The method used is content analysis and also social network analysis from conversation data on Twitter from January 12,to February 3, 2021. The narrative related to the hashtag #vaccin is 1) The use of characters as roles behavioral models for following a vaccine program; 2) Vaccine registration procedures; 3) The urgency of vaccination in the midst of a pandemic by religious leaders; 4) Paid vaccine narrative. The effectiveness of messages conveyed in conversations on social media based on network analysis shows that the spread of messages is not too wide. The incessant vaccine campaign shows a more positive attitude towards the vaccine itself.AbstrakTujuan dari penelitian ini diantaranya untuk mengetahui narasi yang dibangun dalam percakapan di media sosial; mengetahui efektivitas penyebaran informasi yang dilakukan berdasarkan tagar yang #vaksin; dan memetakan polarisasi sikap masyarakat terhadap vaksin COVID-19. Metode yang digunakan adalah content analysis dan juga social network analysis dari data percakapan di media sosial Twitter dari tanggal 12 Januari 2021 sampai dengan 3 Februari 2021. Narasi yang dibangun dalam percakapan di media sosial Twitter terkait dengan tagar #vaksin adalah 1) Penggunaan tokoh sebagai role model perilaku untuk mengikuti program vaksin; 2) Tata cara pendaftaran vaksin; 3) Urgensi vaksinasi di tengah pandemi oleh tokoh agama; 4) Narasi vaksin berbayar. Efektivitas pesan yang disampaikan dalam percakapan di media sosial berdasarkan analisis jaringan menunjukkan bahwa penyebaran pesan tidak terlalu luas. Gencarnya kampanye vaksin menunjukkan perubahan sikap yang lebih positif terhadap vaksin itu sendiri.
Recycling Solid Waste of Coconut Oil Industry: A Response Surface-Goal Programming Approach Dwi Agustin Nuriani Sirodj; Ivan Gunawan
Jurnal Optimasi Sistem Industri Vol. 19 No. 2 (2020): Published in November 2020
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (702.862 KB) | DOI: 10.25077/josi.v19.n2.p111-121.2020

Abstract

Waste minimization is a key success factor to achieve sustainability, including in the edible oil industry. One type of solid waste produced substantially in this industry is spent bleaching earth (SBE), which comes from a mixture of bleaching earth (BE) and activated carbon (CA) used in the edible oil refining process. SBE that is recycled through a heating process is known as heat regenerated SBE (HRSBE). The process is influenced by two factors as stated in previous studies: temperature and time. In the current study, we report the results of experiments to find the optimal combination of temperature and time in restoring the absorbent quality of SBE by observing four quality parameters: colors (red and yellow), Free Fatty Acid (FFA), and Peroxide Value (PV). The current study uses Response Surface Methodology (RSM) to design the experiments and to find the equations of the relationship between the factors for each response; as well as Goal Programming (GP) to find the most optimal combination of factors in order to achieve aggregated quality targets. The findings show that 3.414 hours of heating at a temperature of 151.64oC allow HRSBE to produce coconut oil in accordance with the expected quality targets.
Pengaruh Pelatihan Otonomi terhadap Tingkat Otonomi Siswa Sekolah Menengah Atas di Bandung Sulisworo Kusdiyati; Yuli Aslamawati; Dwi Agustin Nuraini Sirodj
Psympathic : Jurnal Ilmiah Psikologi Vol 5, No 2 (2018): PSYMPATHIC
Publisher : Fakultas Psikologi, Universitas Islam Negeri (UIN) Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/psy.v5i2.3299

Abstract

High school students in the city of Bandung appeared to have moderate or even low learning engagement. This low level of learning engagement was caused by low sense of autonomy. Therefore, to increase learning engagement, an autonomy training program is needed for these students. This study aimed to find out whether the autonomy training program increases the autonomy level of students. The design of the study was quasi-experimental with the one-group before-after design. The research subjects were collected using random sampling technique, with a total of 37 students from two high schools in Bandung. The Autonomy instrument was collected using a questionnaire compiled by researchers based on Ryan and Deci’s Self-determination theory. Based on the validity and reliability test, the instrument was valid and reliable. The results showed that autonomy training is effective in enhancing students' sense of autonomy.
Gambaran Negative Automatic Thoughts pada Remaja Korban Bullying di Sekolah Menengah Pertama Kota Bandung Andhita Nurul Khasanah; Temi Damayanti; Dwi Agustin Nuriani Sirodj
Psympathic : Jurnal Ilmiah Psikologi Vol 4, No 2 (2017): PSYMPATHIC
Publisher : Fakultas Psikologi, Universitas Islam Negeri (UIN) Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/psy.v4i2.1698

Abstract

This research aimed to obtain a description explanation about negative automatic thoughts that appear on Bandung junior high school students who are bullied. The research also described the automatic negative thoughts that was based on factors affected by bullying (from CATS questionnaire). The research involved 1261 samples of the students of  5 junior high school in Bandung. Data were analyzed using descriptive statistic analysis. The results showed as many as 48 students belonging to students who experience the action of bullying with high frequency and as many as 333 students experience the act of bullying in the medium frequency. Then, based on the results of CATS questionnaires, about 8.3% of students, show that they had higher frequency the occurrence of negative automatic thoughts. It means they had a negative beliefs scheme and often experience helplessness in their daily lives. The factor analysis showed that social threat was the most contributive factor in generating negative automatic thoughts.
Klasifikasi Penipuan Transaksi Kartu Kredit Menggunakan Metode Random Forest Tiara Suci Lestari; Dwi Agustin Nuriani Sirodj
Jurnal Riset Statistika Volume 1, No. 2, Desember 2021, Jurnal Riset Statistika (JRS)
Publisher : UPT Publikasi Ilmiah Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (498.679 KB) | DOI: 10.29313/jrs.v1i2.525

Abstract

Abstract. In today's technological developments, the use of credit cards is a very easy and practical way for customers to make transactions. However, with the increasing use of credit cards, it will lead to financial fraud, namely fraudulent credit card transactions that can harm customers and the bank or company. One technique that can overcome this problem is data mining techniques, namely the classification used to predict fraudulent actions in credit card transactions. The method used is the random forest method, which is an ensemble method by applying bootstrap aggregating (bagging) and random feature selection, which combines several decision trees to form a forest, then to get the results of the final classification prediction through a voting process. The data used is credit card transaction fraud data for 2019-2020. The purpose of the results of this study is to apply the random forest method to the classification of credit card transaction fraud based on the evaluation of classification accuracy such as confusion matrix, accuracy, sensitivity, precision, f-measure and AUC value. The results of the study showed that the application of the random forest method gave very good classification results in classifying fraudulent credit card transactions. Abstrak. Pada perkembangan teknologi saat ini, penggunaan kartu kredit merupakan cara yang sangat mudah dan praktis digunakan pelanggan dalam melakukan transaksi. Tetapi dengan meningkatnya penggunaaan kartu kredit maka akan menimbulkan kecurangan finansial yaitu penipuan transaksi kartu kredit yang dapat merugikan nasabah maupun pihak bank atau perusahaan. Salah satu teknik yang dapat mengatasi masalah tersebut yaitu teknik data mining yaitu klasifikasi yang digunakan untuk memprediksi tindakan penipuan pada transaksi kartu kredit. Metode yang digunakan yaitu metode random forest yang merupakan metode ensemble dengan menerapkan bootstrap aggregating (bagging) dan random feature selection yaitu menggabungkan beberapa pohon keputusan sehingga membentuk hutan (forest), kemudian untuk mendapatkan hasil dugaan klasifikasi akhir melalui proses voting. Data yang digunakan yaitu data penipuan transaksi kartu kredit tahun 2019-2020. Tujuan hasil dari penelitian ini yaitu menerapkan metode random forest pada klasifikasi penipuan transaksi kartu kredit berdasarkan evaluasi ketepatan klasifikasi seperti seperti confusion matrix, akurasi, sensitivitas, presisi, f-measure dan nilai AUC. Hasil dari penelitian didapatkan bahwa penerapan metode random forest memberikan hasil klasifikasi yang sangat baik dalam mengklasifikasikan penipuan transaksi kartu kredit.
Diagram Kontrol U dan Diagram Kontrol DOB dalam Pengendalian Kualitas Produksi Tepung Anwar Musadad Rosidin; Dwi Agustin Nuriani Sirodj
Jurnal Riset Statistika Volume 2, No. 1, Juli 2022, Jurnal Riset Statistika (JRS)
Publisher : UPT Publikasi Ilmiah Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (177.051 KB) | DOI: 10.29313/jrs.vi.722

Abstract

Abstract. To maintain and improve the quality of the resulting production is to use statistical quality control. One of the methods used in statistical quality control is control diagram u and control diagram Decision On Belief (DOB). The u control chart and DOB control chart are attribute diagrams that are used to see if a production process is statistically controlled or not by looking at the points that are out of the control limits that have been determined by the existing formula. The DOB control chart which was first introduced by Nezhab (2010) is used to analyze and classify the state of the quality control system using univariate attribute data. This study discusses the quality control of tapioca flour production at PT. X with u and DOB control chart method. The data used in this study is the data on the number of defects in tapioca flour production at PT. X during the period in daily. By looking at the points that are out of control on each control chart. The result of this research is the DOB control chart shows a better performance than the u control chart in controlling the production quality of tapioca flour products at PT. X. Abstrak. Untuk menjaga dan meningkatkan kualitas produksi yang dihasilkan adalah dengan menggunakan pengendalian kualitas statistik. Salah satu metode yang digunakan dalam pengendalian kualitas statistik adalah diagram kontrol u dan diagram kontrol Decision On Belief (DOB). Diagram kontrol u dan diagram kontrol DOB merupakan diagram atribut yang digunakan untuk melihat proses suatu produksi sudah terkendali secara statistik atau belum dengan melihat titik-titik yang keluar dari batas kendali yang telah ditentukan dengan rumus yang sudah ada. Diagram kontrol DOB yang pertama kali diperkenalkan oleh Nezhab (2010) digunakan untuk menganalisis dan mengklasifikasikan keadaan sistem pengendalian kualitas dengan menggunakan data univariat atribut. Dalam penelitian ini dibahas pengendalian kualitas produksi tepung tapioka di PT. X dengan metode diagram kontrol u dan DOB. Data yang digunakan dalam penelitian ini adalah data jumlah cacat produksi tepung tapioka di PT. X selama periode dalam harian. Dengan melihat titik-titik yang out of control pada setiap diagram kontrol. Hasil dari penelitian ini adalah diagram kontrol DOB menunjukkan kinerja yang lebih baik daripada diagram kontrol u dalam pengendalian kualitas produksi produk tepung tapioka di PT. X.
ONLINE PRICING FOR SMALL MEDIUM ENTERPRISES’ PRODUCTS IN THE EX-LOCALIZATION OF DOLLY SURABAYA Ig. Jaka Mulyana; Ivan Gunawan; Dian Trihastuti; Yehezkiel Prakoso Putra Yunen; Dwi Agustin Nuriani Sirodj
J@ti Undip: Jurnal Teknik Industri Vol 16, No 3 (2021): September 2021
Publisher : Departemen Teknik Industri, Fakultas Teknik, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (522.85 KB) | DOI: 10.14710/jati.16.3.169-176

Abstract

Numerous Small and Medium Enterprises (SMEs) do not have a basic method in pricing decisions. Many times, this decision comes up based on an intuitive probe instead of a detailed analysis. This could lead to marketing problems, which may result in disruptions of financial liquidity. This also applies to SMEs wishing to sell products through the online channel. They need a proper pricing strategy, considering its different marketing strategies. Sales made through both offline channels (conventional stores) and online channels are known as Dual-Channel Supply Chain (DCSC). It is argued that the pricing decision at DCSC needs to consider consumer preferences in selecting the sales channel. One assumption commonly adopted in the DCSC pricing model is that the lost value if consumers purchase products through online channels. Therefore, the pricing decision for the online channel should be cheaper than the price on the offline channel. This study aims to assist SMEs in the ex-localization of Dolly in Surabaya in determining the price of products to be sold through online channels. Three types of products: batik, chips, and leather shoes were selected as research samples to represent the product groups: craft, fashion, and processed food. This study proposes an optimal online price strategy through experiments with a mathematical model. Model parameters, namely consumer preferences in choosing sales channels, are obtained through surveys. Apart from that, surveys are also used to reveal which platforms consumers are interested in shopping online. Shopee and Instagram were chosen by respondents as the most popular marketplaces and social media for online shopping. Finally, the online prices proposed for the batik product are IDR 82,500-IDR 66,000; chips Rp7,620-Rp6,336; and leather shoes Rp.103,800-Rp82,200.
Analisis Hubungan Harga Saham Bank Central Asia, Inflasi, Kurs (IDR/USD) dan BI Rate dengan Metode Vector Error Correction Model (VECM) Moh. Wigi Destriansyah; Dwi Agustin Nuriani Sirodj
Bandung Conference Series: Statistics Vol. 2 No. 2 (2022): Bandung Conference Series: Statistics
Publisher : UNISBA Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (225.822 KB) | DOI: 10.29313/bcss.v2i2.4057

Abstract

Abstract. One method of multivariate time series analysis is VECM. VECM is used to overcome the existence of data forms that are not stationary in the average but there is cointegration in the variables. VECM is often used in long-term econometric cases such as forecasting the movement of a stock price. The movement of a company's stock price level can be influenced by factors such as inflation, exchange Rates and the BI Rate or interest Rates in the short and long term. The banking sector is one sector that is often targeted by investors, such as shares of Bank BCA Tbk because it has a high reputation, large market capitalization, positive company performance and routine dividend distribution. This study aims to analyze the effect of the variable inflation, exchange Rate (IDR/USD) and the BI Rate on the stock price of Bank Central Asia, as well as to see the long-term relationship between these variables and predict the stock price of BBCA. The variables used in this study are Inflation, Exchange Rate (IDR/USD), BI Rate to BBCA's Stock Price from August 2016 to September 2021. The model obtained is VECM(4) with 1 rank cointegration. Inflation and Exchange Rate (IDR/USD) variables have a significant effect on changes in the value of BBCA's Stock Price in the long term. While the BI Rate variable has no significant effect on changes in the value of the BBCA Share Price in the long term. Abstrak. Salah satu metode analisis deret waktu multivariat adalah VECM. VECM ini digunakan untuk mengatasi keberadaan bentuk data yang tidak stasioner dalam rata-rata narnun terdapat kointegrasi dalam variabelnya. VECM sering digunakan dalam kasus-kasus ekonometrika jangka panjang seperti meramalkan pergerakan suatu harga saham. Pergerakan level harga saham suatu perusahaan bisa dipengaruhi oleh faktor-faktor seperti Inflasi, Kurs dan BI Rate atau suku bunga dalam jangka waktu pendek maupun panjang. Sektor perbankan menjadi salah satu sektor yang sering diincar oleh para investor, seperti saham Bank BCA Tbk sebab memiliki reputasi tinggi, kapitalisasi pasar yang besar, kinerja perusahaan yang positif dan rutin melakukan pembagian dividen. Penelitian ini bertujuan untuk menganalisis pengaruh dari variabel Inflasi, Kurs (IDR/USD) dan BI Rate terhadap Harga Saham Bank Central Asia, serta untuk melihat hubungan jangka panjang antara variable tersebut dan meramalkan harga saham BBCA. Variabel yang digunakan dalam penelitian ini adalah Inflasi, Kurs (IDR/USD), BI Rate terhadap Harga Saham BBCA dari bulan Agustus 2016 hingga September 2021. Model yang didapatkan adalah VECM(4) dengan 1 rank kointegrasi. Variabel Inflasi dan Kurs (IDR/USD) berpengaruh secara signifikan terhadap perubahan nilai Harga Saham BBCA dalam jangka panjang. Sedangkan variabel BI Rate tidak berpengaruh secara signifikan terhadap perubahan nilai Harga Saham BBCA dalam jangka panjang.
Pemodelan Geographically Weighted Regression dengan Fungsi Pembobot Fixed Gaussian Kernel untuk Kasus Tingkat Partisipasi Angkatan Kerja Wanita di Provinsi Aceh Ainun Hayat Damayanti; Dwi Agustin Nuriani Sirodj
Bandung Conference Series: Statistics Vol. 2 No. 2 (2022): Bandung Conference Series: Statistics
Publisher : UNISBA Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (198.149 KB) | DOI: 10.29313/bcss.v2i2.4071

Abstract

Abstract. The female labor force participation rate (TPAK) is an indicator that shows the large percentage of the working-age female population who are economically active in an area. The TPAK value of women in Aceh Province in 2021 was 48,36%. This value shows that the TPAK of Acehnese women is still 31,04% lower than the male TPAK of 79,40%. The data shows that there are resources that are underutilized properly and are not in line with one of the Sustainable Development Goals (SDGs) regarding gender equality in work. The problem regarding the number of female TPAK which is still below the male TPAK figure can be solved by the Geographically Weighted Regression (GWR) method because it has a different TPAK between in cities and villages due to different geographical factors there are also natural resources, human resources, availability of employment, availability of health facilities and others that vary. It can be seen from the smallest AIC values and the largest R2 that compared to the global regression model, the GWR model with Fixed Gaussian Kernel weighting function is the best model for modeling female TPAK data in Aceh Province with an AIC value of 116.5576 and R2 of 90.78%. The GWR model using the kernel fixed gaussian weighting function only produces 1 group of significant variables, namely, the housewife percentage variable. So the factor that affects the low TPAK of women in Aceh Province is the percentage of housewives Abstrak. Tingkat partisipasi angkatan kerja (TPAK) wanita merupakan indikator yang menunjukkan besarnya persentase penduduk wanita usia kerja yang aktif secara ekonomi di suatu daerah. Nilai TPAK wanita di Provinsi Aceh tahun 2021 adalah sebesar 48,36%. Nilai ini menunjukkan bahwa TPAK wanita Aceh masih 31,04% lebih rendah dari TPAK pria yang sebesar 79,40%. Data tersebut menunjukan adanya sumber daya yang kurang dimanfaatkan dengan baik dan tidak selaras dengan salah tujuan Sustainable Development Goals (SDGs) perihal kesetaraan gender dalam pekerjaan. Permasalahan mengenai angka TPAK wanita yang masih berada dibawah angka TPAK pria ini dapat diselesaikan dengan metode Geographically Weighted Regression (GWR) karena memiliki TPAK yang berbeda antara di kota dan di desa akibat faktor geografis yang berbeda juga terdapat sumber daya alam, sumber daya manusia, ketersediaan lapangan kerja, ketersediaan fasilitas kesehatan dan lain-lain yang bervariasi. Terlihat dari nilai AIC terkecil dan R2 terbesar diketahui bahwa dibandingkan model regresi global, model GWR dengan fungsi pembobot Fixed Gaussian Kernel adalah model terbaik untuk memodelkan data TPAK wanita di Provinsi Aceh dengan nilai AIC sebesar 116.5576 dan R2 sebesar 90,78%. Model GWR dengan menggunakan fungsi pembobot Fixed Gaussian Kernel hanya menghasilkan 1 kelompok variabel signifikan yakni, variabel persentase ibu rumah tangga. Maka faktor yang mempengaruhi rendahnya TPAK wanita di Provinsi Aceh adalah persentase ibu rumah tangga.
PERBANDINGAN UKURAN JARAK PADA ALGORITMA K-NEAREST NEIGHBOR DALAM ANALISIS SENTIMEN Alfiari Firdaus; Dwi Agustin Nuriani Sirodj
STATMAT : JURNAL STATISTIKA DAN MATEMATIKA Vol 4, No 2 (2022)
Publisher : Math Program, Math and Science faculty, Pamulang University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/sm.v4i2.27059

Abstract

K-Nearest Neighbor (KNN) merupakan salah satu algoritma klasifikasi yang paling banyak digunakan dalam metode machine learning. Klasifikasi KNN merupakan metode klasifikasi non-parametrik konvensional yang telah digunakan sebagai pengklasifikasi dasar dalam banyak masalah klasifikasi pola. Teknik pencarian KNN yang digunakan dalam penelitian ini dengan menggunakan rumus jarak euclidean, minkowski, manhattan dan linear least square. Keuntungan dari metode ini adalah efektif terhadap data noise dan efektif ketika data training berukuran besar. Namun metode ini masih memiliki kekurangan yaitu masalah tingkat akurasi metode yang digunakan untuk mengukur kemiripan antar objek yang dibandingkan. Tujuan dari penelitian ini adalah untuk mengetahui ukuran jarak terbaik dalam metode KNN pada analisis sentimen. Data yang digunakan adalah data tweet sebanyak 12.951 yang diambil dari twitter dengan menggunakan hastag #OmicronVariant dan #Covid19. Hasil penelitian menunjukkan bahwa parameter nilai k terbaik adalah 15 sedangkan jarak terbaik adalah jarak euclidean yang diukur melalui nilai akurasi, recall, dan presisi yang baik, kemudian hasil prediksi diperoleh nilai kategori positif lebih tinggi dibandingkan nilai kategori netral dan nilai kategori negatif. Dapat disimpulkan bahwa persepsi masyarakat terhadap Covid-19 Omicron adalah positif, artinya mereka percaya dengan adanya virus covid-19 jenis omicron.
Co-Authors Ainun Hayat Damayanti Alfiari Firdaus Anang Kurnia Anwar Musadad Rosidin Dian Trihastuti I Made Sumertajaya Ig. Jaka Mulyana Ihsana Sabriani Borualogo Ivan Gunawan Khasanah, Andhita Nurul Miki Amrilya Wardati Moh. Wigi Destriansyah Muhamad Nurhikmat Zain Muhamad Nurhikmat Zain Permana, Rizka Hadian Rizka Hadian Permana Sulisworo Kusdiyati Susandari Susandari Temi Damayanti Djamhoer Tiara Suci Lestari Vici Sofianna Putera Yehezkiel Prakoso Putra Yunen Yuli Aslamawati, Yuli