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Pemetaan quantitative trait loci untuk sifat berskala kategorik Afendi, Farit Mochamad
Jurnal Ilmu Pertanian Indonesia Vol 12, No 1 (2007): Jurnal Ilmu Pertanian Indonesia
Publisher : Institut Pertanian Bogor

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Abstract

Genes or regions on chromosome underlying a quantitative trait are called quantitative trait loci (QTL). Characterizing genes controlling quantitative trait on their position in chromosome and their effect on trait is through a process called QTL mapping. In estimating the QTL position and its effect, QTL mapping utilizes the association between QTL and DNA makers. However, many important traits are obtained in categorical scale, such as resistance from certain disease. From a theoritical point of view, QTL mapping method assuming continuous trait could not be applied to categorical trait. This research was facusing on the assessment of the performance of maximum likehood (ML) and regression (REG) approach employed in QTL mapping for binary trait by means of simulation study. The simulation study to evaluate the performance of ML and REG approach was conducted by taking into accounte several factors that may affecting the performance of both approaches. The factors are (1) maker density, (2) QTL effect, (3) sample size, and (4) shape of phenotypic distribution. Form simulation study, it was obtained that the two approaches showing comparable performance. Hence, QTL analysis could be performed using these two approaches due to their similar performance.
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

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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
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 | 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.
Pemetaan quantitative trait loci untuk sifat berskala kategorik Afendi, Farit Mochamad
Jurnal Ilmu Pertanian Indonesia Vol 12, No 1 (2007): Jurnal Ilmu Pertanian Indonesia
Publisher : Institut Pertanian Bogor

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

Abstract

Genes or regions on chromosome underlying a quantitative trait are called quantitative trait loci (QTL). Characterizing genes controlling quantitative trait on their position in chromosome and their effect on trait is through a process called QTL mapping. In estimating the QTL position and its effect, QTL mapping utilizes the association between QTL and DNA makers. However, many important traits are obtained in categorical scale, such as resistance from certain disease. From a theoritical point of view, QTL mapping method assuming continuous trait could not be applied to categorical trait. This research was facusing on the assessment of the performance of maximum likehood (ML) and regression (REG) approach employed in QTL mapping for binary trait by means of simulation study. The simulation study to evaluate the performance of ML and REG approach was conducted by taking into accounte several factors that may affecting the performance of both approaches. The factors are (1) maker density, (2) QTL effect, (3) sample size, and (4) shape of phenotypic distribution. Form simulation study, it was obtained that the two approaches showing comparable performance. Hence, QTL analysis could be performed using these two approaches due to their similar performance.
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 | 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
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 : Institut Pertanian Bogor

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.
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.
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

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
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.