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MODELLING INGREDIENT OF JAMU TO PREDICT ITS EFFICACY Afendi, Farit Mochamad; ., Sulistiyani; Hirai, Aki; ., Md. Altaf-Ul-Amin; Takahashi, Hiroki; Nakamura, Kensuke; Kanaya, Shigehiko
FORUM STATISTIKA DAN KOMPUTASI Vol. 15 No. 2 (2010)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (555.672 KB)

Abstract

Jamu is an Indonesian herbal medicine made from a mixture of several plants.  Nowadays, many jamu are  produced commercially by many industries in Indonesia.  Each producer may have their own jamu formula. However, one is certain; the efficacy of jamu is determined by the composition of the plants used.  Thus, it is interesting to model the ingredient of jamu which consist of plants and use it to predict efficacy of jamu.  In this analysis, Partial Least Squares Discriminant Analysis (PLSDA) is used in modeling jamu ingredients to predict  the  efficacy.  It  is  obtained  that  utilizing the prediction of  y ij obtained  from  PLSDA  directly  rather  than  use  it  to calculate probability of jamu i belong to efficacy j and then use the probability to predict efficacy produces lower False Positive Rate (FPR) in predicting efficacy group.  Keywords: Jamu, PLSDA
PENERAPAN SYNTHETIC MINORITY OVERSAMPLING TECHNIQUE (SMOTE) TERHADAP DATA TIDAK SEIMBANG PADA PEMBUATAN MODEL KOMPOSISI JAMU Barro, Rossi Azmatul; Sulvianti, Itasia Dina; Afendi, Farit Mochamad
Xplore: Journal of Statistics Vol. 1 No. 1 (2013)
Publisher : Departemen Statistika IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (243.353 KB) | DOI: 10.29244/xplore.v1i1.12424

Abstract

As the times many people use herbal remedies(jamu) to address health issues. Herbal medicines are madefrom plants with a specific composition to produce certainproperties, so a model is needed to be made in order tofind the right formula to make herbal medicine with certainproperties. In this study, the response being investigated is apotent herbal medicine in treating mood and behavior disorder.In this analysis, the model is developed using logistic regression.The accuracy of the model can be seen from the Area UnderCurve (AUC). Imbalanced data on the response variable cancause the value of AUC become low. One of the ways tosolve it is using Synthetic Minority Oversampling Technique(SMOTE). From this analysis, Nagelkerke R2 values generatedby the model with SMOTE 3.2% lower than model withoutSMOTE. Nonetheless, the model with SMOTE is more accuratethan model without SMOTE because has higher AUC value.The resulting AUC is equal to 0.976 for the model with SMOTEand 0.908 for model without SMOTE. The results show thatSMOTE can increase the accuracy of the model for imbalanceddata.Keywords-imbalance data, logistic regression, SMOTE
Simultaneous clustering analysis with molecular docking in network pharmacology for type 2 antidiabetic compounds Rifai, Nur Azizah Komara; Afendi, Farit Mochamad; Sumertajaya, I Made
Indonesian Journal of Biotechnology Vol 22, No 1 (2017)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (655.479 KB) | DOI: 10.22146/ijbiotech.27334

Abstract

The database of drug compounds and human proteins plays a very important role in identifying the protein target and the compound in drug discovery. Recently, a network pharmacology approach was established by updating the research paradigm from the current “one disease-one target-one drug” to a new “drug-target-disease network”. Ligand-protein interactions can be analyzed quantitatively using simultaneous clustering and molecular docking. The docking method offers the ability to quickly and cheaply predict the ligand-protein binding free energy (DG) in structure-based virtual screening. Meanwhile, simultaneous clustering was used to find subgroups of compounds that exhibit a high correlation with subgroups of target proteins. This study is focused on the interaction between the 306 compounds from medicinal plants (brotowali Tinospora crispa, ginger Zingiber officinale, pare Momordica charantia, sembung Blumea balsamifera, synthetic drugs (FDA-approved) and the 21 significant human proteins associated with type 2 diabetes. We found that brotowali (B018), sembung (S031), pare (P231), and ginger (J036, J033) were close to the synthetic drugs and can possibly be developed as antidiabetic drug candidates. Likewise, the proteins AKT1, WFS1, APOE, EP300, PTH, GCG, and UBC which assemble each other and which have a high association with INS can be seen as target proteins that play a role in type 2 diabetes.
PENGARUH SPIRITUALITAS KERJA TERHADAP KETERLEKATAN KARYAWAN MELALUI KEPUASAN KERJA PADA UKM KOTA BOGOR Jannah, Nur; Sukmawati, Anggraini; Afendi, Farit Mochamad
Jurnal Manajemen dan Organisasi Vol. 8 No. 2 (2017): Jurnal Manajemen dan Organisasi
Publisher : IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jmo.v8i2.19990

Abstract

The Quality human resources are needed in global economic competition. Spirituality in work becomes a solution developed by companies, because it can be created a conducive environment for employees to work as good as possible. The purpose of this study is to analyze the influence of work spirituality on employee engagement through job satisfaction in Small and Medium Enterprises cluster of food and beverages in the city of Bogor. This research used Structural Equation Modeling PLS for data analysis. Samples are SMEs that have at least 5 employees and have been registered in the Department of Industry and Trade (Disperindag) and the Department of Cooperatives and SMEs Bogor City. So that 25 SMEs are eligible, consisting of 65 people consisting of employees and owners of SMEs. Sampling method using purposive sampling. The results showed that the spirituality of work has a positive effect directly on employee engagement and indirectly influence through job satisfaction on employee engagement to the organization. Meanwhile, job satisfaction has a direct positive effect on employees'  engagement to the organization. Therefore, increased employee engagement to SMEs is suggested through several supporting activities such as: communicating and facilitating the need for spirituality in the workplace.
IDENTIFICATION OF SIGNIFICANT PROTEINS ASSOCIATED WITH DIABETES MELLITUS USING NETWORK ANALYSIS OF PROTEIN-PROTEIN INTERACTIONS Usman, Muhammad Syafiuddin; Kusuma, Wisnu Ananta; Afendi, Farit Mochamad; Heryanto, Rudi
Computer Engineering and Applications Journal Vol 8 No 1 (2019)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (492.82 KB) | DOI: 10.18495/comengapp.v8i1.283

Abstract

Computation approach to identify significance of proteins related with disease was proposed as one of the solutions from the problem of experimental method application which is generally high cost and time consuming. The case of study was conducted on Diabetes Melitus (DM) type 2 diseases. Identification of significant proteins was conducted by constructing protein-protein interactions network and then analyzing the network topology. Dataset was obtained from Online Mendelian Inheritance in Man (OMIM) and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) which provided protein data related with a disease and Protein-Protein Interaction (PPI), respectively. The results of topology analysis towards Protein-Protein Interaction (PPI) showed that there were 21 significant protein associated with DM where INS as a network center protein and AKTI, TCF7L2, KCNJ11, PPARG, GCG, INSR, IAPP, SOCS3 were proteins that had close relation directly with INS.
Liquid Chromatography Mass Spectrometry (LC-MS) Fingerprint Combined with Chemometrics for Identification of Metabolites Content and Biological Activities of Curcuma aeruginosa Septaningsih, Dewi Anggraini; Darusman, Latifah Kosim; Afendi, Farit Mochamad; Heryanto, Rudi
Indonesian Journal of Chemistry Vol 18, No 1 (2018)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (525.361 KB) | DOI: 10.22146/ijc.25456

Abstract

Curcuma aeruginosa is known as one of the components of herbal medicine with various biological activities. This research aims to identify the metabolites content of C. aeruginosa related to their biological activities using LC-MS fingerprint combined with chemometrics. C. aeruginosa from 3 areas in Java were collected and macerated with ethanol and then analyzed with LC-MS. Along with this analysis, the antioxidant activity of all samples was determined using CUPRAC method, and the toxicity was determined using Brine Shrimp Lethality Test (BSLT), and chemometric method was used Principle Component Analysis (PCA) and Partial Least square (PLS). Metabolites profiles showed 175 predicted compounds, in which the dominant compounds are from the sesquiterpene of Curcuma genus. The PCA metabolites profiles can separate the samples by their location of origin. Interpretation of the correlation between metabolites profiles and their bioactivities was determined using PLS technique. The results showed that the toxicity of samples was exerted by compounds with ion mass of 312.28 and 248.15, which have the highest antioxidant and toxicity potentials. Compounds with ion mass of 248.15 were predicted to be 9-Oxo-neoprocurcumenol, 7α,11α,-Epoxy-5β-hydroxy-9-guaiaen-8-one, Curcumenolactone A, or Curcumenolactone B. While compound with ion mass of 312.28 was predicted to tetrahydro-bisdemethoxycurcumin.
Efek Sinergis Bahan Aktif Tanaman Obat Berbasiskan Jejaring Dengan Protein Target Syahrir, Nur Hilal A.; Afendi, Farit Mochamad; Susetyo, Budi
Jurnal Jamu Indonesia Vol 1 No 1 (2016): Jurnal Jamu Indonesia
Publisher : Pusat Studi Biofarmaka Tropika LPPM IPB; Tropical Biopharmaca Research Center - Bogor Agricultural University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1489.882 KB) | DOI: 10.29244/jji.v1i1.6

Abstract

Medicinal plants contain inherently active ingredients. Such ingredients are beneficial to prevent and cure diseases, as well as to perform specific biological functions. In contrast to synthetic drugs, which is based on one single chemicals, medicinal plants exert their beneficial effects through the additive or synergistic action of several chemical compounds. Those chemical compound act on single or multiple targets (multicomponent therapeutic) associated with a physiological process. Active ingredients combinations show a synergistic effect. This means that the combinational effect of several active ingredients is greater than that of individual one acting separately. A network target can be used to identify synergistic effects of plants active ingredients. The method of NIMS (Network target-based Identification of Multicomponent Synergy) is a computational approach to identify the potential synergistics effect of active ingredients. It also assessess synergistic strength of any active ingradients at the molecular level by synergy scores. We investigate these synergistic on a Jamu formula for diabetes mellitus type 2.  The Jamu formula is composed of four medicinal plants, namely Tinospora crispa , Zingiber officinale, Momordica charantia, and Blumea balsamivera. Our work succesfully demonstrates that the highest synergy scores on medicinal plants synergy can be seen in pairs of several active ingredients in Zingiber officinale. On the other hand, the synergy of pairs of active ingredients in Momordica charantia and Zingiber officinale posseses a relatively high score. The same occurs in Tinospora crispa and Zingiber officinale.
Analisis Gerombol Simultan dan Jejaring Farmakologi antara Senyawa dengan Protein Target pada Penentuan Senyawa Aktif Jamu Anti Diabetes Tipe 2 Qomariasih, Nurul; Susetyo, Budi; Afendi, Farit Mochamad
Jurnal Jamu Indonesia Vol 1 No 2 (2016): Jurnal Jamu Indonesia
Publisher : Pusat Studi Biofarmaka Tropika LPPM IPB; Tropical Biopharmaca Research Center - Bogor Agricultural University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1519.787 KB) | DOI: 10.29244/jji.v1i2.16

Abstract

Selama ini pembuatan obat untuk menyembuhkan suatu penyakit masih menargetkan hanya satu protein khusus yang menjadi penyebab penyakit tersebut, yang tentu hanya menggunakan satu senyawa aktif. Padahal selain menimbulkan efek samping, penanganan suatu penyakit perlu menyasar banyak protein sekaligus. Sehingga, baru-baru ini terjadi perubahan paradigma dari “one drug, one target” menjadi “multi-components, network target”. Paradigma baru ini telah melahirkan beberapa penelitian untuk menghasilkan formulasi jamu, hal ini dikarenakan konsep formulasi jamu memerlukan beberapa senyawa aktif yang terlibat. Formula jamu yang diteliti sebagai upaya menyembuhkan penyakit Diabetes Melitus (DM) tipe 2 terdiri dari 4 tanaman yaitu Pare (Momordica charantia), Sembung (Blumea balsamifera), bratawali (Tinospora crispa), dan jahe (Zingiber officinale) berdasarkan hasil penelitian Nurishmaya tahun 2014 serta berdasarkan ramuan jamu yang sedang dikembangkan di Pusat Studi Biofarmaka, Bogor. Evaluasi senyawa yang berkaitan dengan DM tipe 2 dilakukan dengan terlebih dahulu menambahkan 19 obat sintetis yang ditujukan untuk DM tipe 2 dari basis data Drug Bank. Sehingga terdapat total sebanyak 74 senyawa aktif yang terdiri dari 55 senyawa alami dari tanaman dan 19 senyawa sintetis obat. Sebanyak 100 protein yang berkaitan erat dengan masing-masing senyawa diperoleh melalui hasil skor konkordan DrugCHIPER. Skor konkordan tersebut kemudian digunakan dalam analisis gerombol simultan antara senyawa dan protein target. Plot komponen utama dan submatrix penggerombolan simultan menunjukkan 2 dari 3 senyawa dari bratawali sangat dekat dengan kelompok sintetis. Selain itu, ada 11 dari 44 senyawa dari Jahe terkumpul bersama dengan senyawa sintetis tetapi dalam jarak yang jauh. Sedangkan berdasarkan jejaring kemiripan, lebih spesifik lagi terdapat 17 dari 19 senyawa obat sintetis yang memiliki kemiripan berdasarkan protein target dengan 2 senyawa tanaman Bratawali dan 5 senyawa tanaman Jahe.
Prediksi Senyawa Aktif Pada Tanaman Obat Berdasarkan Kemiripan Struktur Kimiawi untuk Penyakit Diabetes Tipe II Bakri, Rizal; Wijayanto, Hari; Afendi, Farit Mochamad
Jurnal Jamu Indonesia Vol 1 No 3 (2016): Jurnal Jamu Indonesia
Publisher : Pusat Studi Biofarmaka Tropika LPPM IPB; Tropical Biopharmaca Research Center - Bogor Agricultural University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (839 KB) | DOI: 10.29244/jji.v1i3.18

Abstract

Diabetes melitus merupakan penyakit metabolik yang dicirikan oleh tingginya kadar glukosa dalam darah. Di Indonesia jumlah penderita diabetes menempati urutan keempat di dunia setelah Amerika Serikat, India, dan Cina dengan jumlah penderita mencapai lebih dari 12 juta jiwa. Salah satu upaya yang dilakukan untuk mengatasi diabetes adalah mengkonsumsi obat herbal berupa jamu sebagai alternatif obat sintetik. Pusat Studi Biofarmaka Bogor sedang mengembangkan ramuan jamu untuk penyakit Diabetes Melitus Tipe II yang terdiri dari empat tanaman obat yaitu pare (Momordica charantia), sembung (Blumea balsamifera), bratawali (Tinospora crispa), dan jahe (Zingiber officinale). Kandungan senyawa keempat tanaman diduga memiliki aktivitas biologis yang mirip dengan senyawa sintetik. Pada prinsipnya, diasumsikan bahwa senyawa yang struktur kimiawinya mirip memiliki sifat biologis yang mirip. Kemiripan senyawa diukur menggunakan koefisien Modifikasi Tanimoto dengan sidik jari molekuler KR. Hasil penelitian menunjukkan bahwa tanaman Bratawali merupakan tanaman utama pada ramuan jamu untuk penyakit diabetes berdasarkan jumlah kandungan senyawa yang dominan mirip dengan senyawa sintetik yaitu senyawa N-trans-feruloyltyramine (B015) dan N-formylanonaine (B018). Selanjutnya, Senyawa-senyawa yang memiliki nilai kemiripan tinggi dengan senyawa sintetik diperoleh pula pada senyawa karaviloside I (P195) dari tanaman pare, senyawa xanthoxylin (S002) dari tanaman sembung, senyawa borneol (J207) dan (-)- isoborneol (J226) dari tanaman Jahe.
Penguraian Mekanisme Kerja Jamu Berdasarkan Jejaring Bahan Aktif-Protein Target-Gene Ontology Handayani, Vitri Aprilla; Afendi, Farit Mochamad; Kusuma, Wisnu Ananta
Jurnal Jamu Indonesia Vol 1 No 3 (2016): Jurnal Jamu Indonesia
Publisher : Pusat Studi Biofarmaka Tropika LPPM IPB; Tropical Biopharmaca Research Center - Bogor Agricultural University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1168.201 KB) | DOI: 10.29244/jji.v1i3.21

Abstract

Jamu merupakan obat tradisional Indonesia. Pada dasarnya obat herbal yang dibuat dari bahan-bahan alami yang diambil dari beberapa bagian dari tanaman obat yang mengandung beberapa zat dan senyawa yang penting dan bermanfaat bagi tubuh. Sejauh ini, khasiat untuk beberapa jenis jamu secara empiris telah terbukti. Dalam peneitian ini, kami bermaksud untuk menguraikan mekanisme kerja jamu menggunakan pendekatan komputasi. Penelitian ini berfokus pada ramuan jamu type 2 diabetesyang terdiri dari empat tanaman, yaitu: jahe, bratawali, sembung, dan pare. Kerangka analisis awal dengan membentuk 3 komponen jejaring yang terdiri dari: (1) bahan aktif tanaman (diperoleh dari Knapsack: 58 senyawa aktif), (2) protein target (diperoeh dari database pubchem: 416 protein target), dan (3) gene ontoogy(diperoeh dari database DAVID: 3104 GO). Selanjutnya, kami menerapkan analisis klaster-klasterdengan menggunakan konsep graf tri-partite. Graf tri-partite digunakan untuk mengelompokkan komponen-komponen penyusun jejaring dari empat tanaman yang disebutkandiatas, sehingga diperoleh system bagian-bagian penyusun ramuan jamu. Hal ini dilakukan untuk mengungkapkan mekanisme kerja jamu. Menggunakan metode fuzzy clustering pada data jejaring, kami memperoleh 15 senyawa aktif yang diduga potensial sebagai antidiabetes berada dalam kelompok berbeda. Pada 15 senyawa aktif memiliki nilai peluang cukup tinggi terbagi dalam kelompok yang berbeda, setiap kelompok terdiri dari pasangan bahan aktif yang memiliki efek sinergis tinggi. Berdasarkan koneksi antara klaster-klasterprotein dan GO-BP, penelitianini memperoleh informasi protein-protein yang menyebabkan T2D dan mekanisme proses biologis yang terkait. T2D bukan hanya disebabkan oleh protein kelainan sekresi insulin (insulin-merendahkan enzim isoform 1) saja, tetapi juga disebabkan oleh protein lain yang terlibat dalam penghambatan insulin di pankreas.