Claim Missing Document
Check
Articles

Found 6 Documents
Search

PENGARUH PERBEDAAN KONSETRASI CLIMBAZOLE DALAM SEDIAAN SAMPO ANTIKETOMBE TERHADAP STABILITAS FISIK DAN AKTIFITAS ANTIJAMUR CANDIDA ALBICANS ayu sulastri siagian; Herman Widjaja
Parapemikir : Jurnal Ilmiah Farmasi Vol 11, No 1 (2022): Parapemikir : Jurnal Ilmiah Farmasi
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/pjif.v11i1.2971

Abstract

Climbazole diklasifikasikan dalam hal perawatan rambut yaitu sebagai sampo antiketombe, konsetrasi untuk climbazole menurut literatur sebagai sampo antiketombe adalah 0,5% - 2,0%. Konsentrasi maksimal climbazole yang dianggap aman untuk kesehatan manusia adalah 2,0%. Mengetahui pengaruh perbedaan konsetrasi Climbazole pada stabilistas fisik dan aktivitas antijamur Candida Albicans. Natrium lauril sulfat dicampur dalam aquadest tambahkan Na2EDTA, tambah BHT, tambah NaCl hinggal terbentuk massa sampo, tambah PQ 10, tambah Climbazole dengan konsetrasi yang berbeda (1,0%, 1,5% dan 2,0%) tambah asam sitrat, tambahkan parfum dan kemudian tambahkan sisa aquades digerus sampai larut, lalu masukkan dalam botol pelastik. Dilakukan uji homegenitas dan organoleptis (bau, warna dan citra sentuhan) dengan secara deskriptif, uji stabilias fisik pada uji pH, Viskositas dan uji aktifitas antijamur Candida Albicans menggunakan SPSS 25. Semakin meningkat perbedaan konsetrasi Climbazole dalam sampo antiketombe maka akan meningkatkan pH dan Viskositas sediaan sampo antiketombe, uji stabilitas fisik pada uji homogenitas dan organoleptis tidak mengalami perubahan baik pada warna, bau dan citra sentuhan tidak ada terjadi perubahan selama empat minggu penyimpanan. Semakin meningkat perbedaan konsentrasi Climbazole semakin meningkat pula aktifitas antijamur candida albicans, semakin lama  di incubasi maka aktifitas antijamur semakin meningkat.Kata kunci: Sampo Antiketobe, konsetrasi Climbazole, Candida Albicans
Optimasi Kombinasi Cetyl Stearyl Alcohol Dan Stearic Acid Sebagai Emulgator Pada Lotion Pemutih Mengandung Alpha Arbutin Widjaja, Herman; Ratih Dewi ButarButar , Alma Sonang
Jurnal Syntax Fusion Vol 2 No 08 (2022): Jurnal Syntax Fusion: Jurnal Nasional Indonesia
Publisher : CV RIFAINSTITUT

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54543/fusion.v2i08.215

Abstract

Alpha arbutin merupakan bahan aktif pemutih kulit yang memiliki mekanisme kerja dengan menghambat kerja enzim tirosinase pada proses melagonesis. Alpha arbutin umumnya digunakan sebagai bahan kosmetika yang efektif dalam mengatasi bintik-bintik atau pencoklatan pada kulit akibat paparan sinar matahari. Tujuan dari penelitian ini yaitu untuk mendapatkan formula optimumdengan kombinasi Cetyl stearyl alcohol dan stearic acid sebagai pengemulsi pada lotion alphaarbutin dan untuk mengetahui pengaruh peningkatan konsentrasi kombinasi Cetyl stearyl alcohol dan stearic acid sebagai pengemulsi lotion alpha arbutin dengan menggunakan metodesimplex lattice design. Konsentrasi kombinasi dari Cetyl stearyl alcohol dan Stearic acid ditentukan dengan metode simplex lattice design dan diambil sebanyak 5 formula. Hasil perbandingan kombinasi Cetyl stearyl alcohol dan stearic acid yang didapat dari software Design Expert versi 13 (trial) adalah sebagai berikut ; 1 : 0,25; 0,25 : 0,75; 1 : 0; 0,75 : 0,75; 0 : 1. Setiap formula dilakukan uji pH dan uji viskositas sebagai respon untuk mendapatkan formula optimum dari ke[1]5 formula tersebut. Verifikasi pada formula optimum dilakukan dengan metode One Sample T-Test dengan taraf kepercayaan 95%. Penelitian ini menghasilkanformulasi optimum dengan perbandingan Cetyl stearyl alcohol dan stearic acid sebesar 6%: 4%, hasil uji pH sebesar 6,10 dan uji viskositas sebesar10500 cps. Hasil dari verifikasi formula optimum menunjukkan nilai percobaan dengan nilai prediksi tidak terjadi perbedaan sehingga menghasilkan lotion Alpha Arbutin yang baik.
Digital Marketing: A Case Study of Social Media Marketing of Indonesia Real Estate Companies Widjaja, Herman; Santoso, Handri
Business Economic, Communication, and Social Sciences Journal (BECOSS) Vol. 6 No. 2 (2024): BECOSS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/becossjournal.v6i2.11794

Abstract

Real Estate industry, like other industries, is also heavily influenced by digital marketing especially the social media. Websites, Facebook, Instagram and YouTube become necessity in modern marketing of real estate. Indonesia’s real estate industry is a dynamic industry considering the country’s economy growth, population size and growth. Although several research has been conducted in this area, the topic focusing on Indonesia’s real estate Social Media Management System (SMMS) is still very limited. The qualitative comparative study is intended to explore and compare social media marketing strategy among top developers in Indonesia, and how they utilize the platforms to distribute marketing content and company’s other information. The data are collected from observation of the companies’ official websites and 138 accounts in YouTube, Facebook and Instagram. The study shows that each company has different strategy, depends on project locations, product / project size, project / product lifetime, target audience (prospects, affiliates, public in general, community etc), project’s ownership structure (fully owned, joint venture, franchise), sales / recurring / operational, management of social media team. Among the surveyed platforms, Instagram has been the most popular to distribute sales information for either recurring products, sales products group of products and even corporate or general public information.
Transforming Real Estate: Leveraging TOGAF ADM for Digital Optimization in Enterprise Architecture Widjaja, Herman; Indrajit, Richardus Eko; Dazki, Erick
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 1 (2025): Research Article, January 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.14219

Abstract

In this research paper, we propose an Enterprise Architecture (EA) design for PT XYZ, a middle up class real estate development company in Indonesia, leveraging the TOGAF ADM framework. The study centers on optimizing five key business processes—commercial leasing, residential sales, hotel banquet rentals, waterpark ticket sales, and parking fee collection—to enhance operational efficiency and support digital transformation. Using ArchiMate modeling for clear visualization, this architecture spans from the Preliminary Phase, Phase A Architecture Vision, Phase B Business Layer, Phase C Information System Architecture (Application Layer) to the Phase D Technology Architecture. It provides a strategic blueprint to address common challenges like data fragmentation, reliance on manual processes and human resources readiness. By implementing this EA, PT XYZ can expect improvements in scalability, flexibility, and overall agility. This approach aims to position PT XYZ as a modern, digitally-driven entity, aligning technology investments with business objectives for long-term success. Future research is recommended to explore later phases of TOGAF ADM (Phase E – Phase H) and potentially integrate additional business areas for a holistic digital transformation.
Sosialisasi Kegiatan Webinar: Sediaan Farmasi Bentuk Sirup untuk Mengatasi Penyakit Maag Widjaja, Herman; Aryanilo, Aryanilo; Andini, Fazri; Pramesti, Junaida; Abdurohim WK, M. Ihsan; Khoiriza, Syifa Nur
Nuras : Jurnal Pengabdian Kepada Masyarakat Vol. 5 No. 4 (2025): October
Publisher : Lembaga Pendidikan, Penelitian, dan Pengabdian Kamandanu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/nuras.v5i4.644

Abstract

Ulcer or gastritis is an inflammation of the stomach caused by increased stomach acid or mucosal irritation which is generally triggered by irregular diet, stress, smoking habits, and alcohol consumption. This activity aims to increase public understanding of the use of syrup-form pharmaceutical preparations in gastritis therapy. The webinar was held online through Zoom Meeting with a total of 32 participants, consisting of 24 women and 8 men who are students of the University of August 17, 1945 Jakarta, as well as the general public. Evaluation was carried out through pre-test and post-test using five multiple-choice questions that measured understanding of the advantages of syrup preparations, the function of active substances (antacids and sucralfates), the selection of preparations in dysphagia patients, the mechanism of action, and the components of the formulation. The results of the post-test showed an increase in participants' understanding, including 100% of participants answered correctly about the advantages of syrup preparations over tablets, 88% understood the function of antacids, 92% knew the mechanism of action of sucralfate, and 76% understood the selection of preparations in dysphagia patients. Thus, this activity has proven to be effective in increasing participants' knowledge about the use of syrup preparations for the treatment of gastritis. Emphasis is needed on the aspect of preparing preparation for dysphagia patients and an understanding of the components of the formulation.
Predicting Resale Prices using Random Forests with Fine-Tuning Hyperparameters Widjaja, Herman; Perdana, Nanda; Wasito, Ito
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 19, No 4 (2025): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.103967

Abstract

The accurate prediction of housing prices is essential for informed decision-making by purchasers, sellers, and policymakers in dynamic real estate markets. This study investigates the application of machine learning models—Random Forest, XGBoost, Decision Tree, and LightGBM—to predict resale flat prices in Singapore. It provides valuable insights into the use of machine learning in housing markets, particularly for datasets with similar size, complexity, and data types. The objectives are to develop predictive regression models for property prices and to analyze and compare the performance of these models. Key contributions include the development of tools to objectively estimate suitable property prices and the advancement of price prediction research through an extensive comparison of machine learning models. While previous studies have demonstrated the predictive capabilities of these models, this research focuses on the impact of hyperparameter tuning on the performance of the Random Forest model. By systematically optimizing parameters such as max_depth, n_estimators, and n_jobs, computation time was reduced by over 93% (from 865 seconds to 50 seconds) with minimal loss in accuracy. With proper hyperparameter tuning, Random Forest achieved the best performance in terms of MAE score (26.555), outperforming XGBoost (27.552), Decision Tree (28.832), and LightGBM (29.752).