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All Journal Jurnal Ilmu Pertanian Indonesia Jurnal Manajemen dan Organisasi FORUM STATISTIKA DAN KOMPUTASI ComEngApp : Computer Engineering and Applications Journal Perfecting a Video Game with Game Metrics Indonesian Journal of Biotechnology Scientific Journal of Informatics BAREKENG: Jurnal Ilmu Matematika dan Terapan Indonesian Journal of Chemistry Indonesian Journal of Statistics and Its Applications Jurnal Jamu Indonesia Journal of Enterprise and Development (JED) Xplore: Journal of Statistics

Farit Mochamad Afendi

Departemen Statistika, Institut Pertanian Bogor, Indonesia

Author-ID : 3379329

Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Immunology & microbiology Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Transportation Other

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Pemetaan quantitative trait loci untuk sifat berskala kategorik Farit Mochamad Afendi
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 | Full PDF (546.809 KB)

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.

Algorithm for Predicting Compound Protein Interaction Using Tanimoto Similarity and Klekota-roth Fingerprint Isnan Mulia; Wisnu Ananta Kusuma; Farit Mochamad Afendi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 4: August 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i4.5916

This research aimed to develop a method for predicting interaction between chemical compounds contained in herbs and proteins related to particular disease. The algorithm of this method is based on binary local models algorithm, with protein similarity section is omitted. Klekota-Roth fingerprint is used for the compound's representation. In the development process of the method, three similarity functions are compared: Tanimoto, Cosine, and Dice. Youden’s index is used to evaluate optimum threshold value. The result showed that Tanimoto similarity function yielded higher similarity values and higher AUC value than those of the other two functions. Moreover, the optimum threshold value obtained is 0.65. Therefore, Tanimoto similarity function and threshold value 0.65 are selected to be used on the prediction method. The average evaluation accuracy of the developed algorithm is only about 50%. The low accuracy value is allegedly caused by the only use of compound similarity on the prediction method, without including the protein similarity.

Pengaruh Spiritualitas Kerja terhadap Keterlekatan Karyawan melalui Kepuasan Kerja pada UKM Kota Bogor Nur Janah; Anggraini Sukmawati; Farit Mochamad Afendi
Jurnal Manajemen dan Organisasi Vol. 8 No. 2 (2017): Jurnal Manajemen dan Organisasi
Publisher : IPB University

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.

MODELLING INGREDIENT OF JAMU TO PREDICT ITS EFFICACY Farit Mochamad Afendi; Sulistiyani .; Aki Hirai; Md. Altaf-Ul-Amin .; Hiroki Takahashi; Kensuke Nakamura; Shigehiko Kanaya
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)

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

Simultaneous clustering analysis with molecular docking in network pharmacology for type 2 antidiabetic compounds Nur Azizah Komara Rifai; Farit Mochamad Afendi; I Made Sumertajaya
Indonesian Journal of Biotechnology Vol 22, No 1 (2017)
Publisher : Universitas Gadjah Mada

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.

Identification of Significant Proteins Associated with Diabetes Mellitus Using Network Analysis of Protein-Protein Interactions Muhammad Syafiuddin Usman; Wisnu Ananta Kusuma; Farit Mochamad Afendi; Rudi Heryanto
Computer Engineering and Applications Journal Vol 8 No 1 (2019)
Publisher : Universitas Sriwijaya

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.

ANALISIS PENGARUH DAERAH PEMASOK TERHADAP HARGA CABAI MERAH DI DKI JAKARTA MENGGUNAKAN VECTOR ERROR CORRECTION MODEL (VECM) Erwandi Erwandi; Farit Mochamad Afendi; Budi Waryanto
Indonesian Journal of Statistics and Applications Vol 3 No 3 (2019)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

This study aims to analyze the effect of red chili price and production in the supplier area on its prices in DKI Jakarta using the Vector Error Correction Model (VECM). The data used in this study are red chili price and average expenditure per month per capita in DKI Jakarta and red chili price and production in East Java, West Java, and Banten in the period January 2012 to July 2018. The model obtained was VECM (1) the price of red chili in DKI Jakarta. It showed that there was a long-term relationship (cointegration) on the first difference. The results the Forecast Error Variance Decomposition (FEVD) analysis showed that the contributions of the red chili price in DKI Jakarta and West Java, average monthly expense for red chili in DKI Jakarta, red chili production (West Java and Banten) are significant in explaining the behaviour of the red chili price change in DKI Jakarta. The results of the Impulse Response Function (IRF) analysis showed that the shock of the price of chili in DKI Jakarta and West Java in the previous month will increase the price of red chili in DKI Jakarta in the following month. Conversely, the shock of the average monthly expenditure of red chili in DKI Jakarta and red chili production (West Java and Banten) from the previous month will reduce the price of red chili in DKI Jakarta in the following month.

PENINGKATAN AKURASI KLASIFIKASI INTERAKSI FARMAKODINAMIK OBAT BERBASIS SELEKSI PASANGAN OBAT TAKBERINTERAKSI Hilma Mutiara Winata; Farit Mochamad Afendi; Anwar Fitrianto
Indonesian Journal of Statistics and Applications Vol 3 No 3 (2019)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Identifying the pharmacodynamics drug-drug interaction (PD DDI) is needed since it can cause side effects to patients. There are two measurements of drug interaction performance, namely the golden standard positive (GSP) which is the drug pairs that interact pharmacodynamics and golden standard negative (GSN), which is a drug pairs that do not interact. The selection of GSN in the previous which studies were only selected randomly from a list of drug pairs that do not interact. The random selection is feared to contain drug pairs that actually interact but have not been recorded. Therefore, in this study the determination of GSN was carried out by, first, grouping drug pairs included in the GSP using the DP-Clus algorithm with certain values of density and cluster properties. Then the drugs in different group would be paired and only the drug pairs in the GSN list are selected. It was found that our new proposed classification method increases the AUC value compared to the results obtained by random selection of GSN.

PERBANDINGAN BEBERAPA METODE KLASIFIKASI DALAM MEMPREDIKSI INTERAKSI FARMAKODINAMIK Hasnita Hasnita; Farit Mochamad Afendi; Anwar Fitrianto
Indonesian Journal of Statistics and Applications Vol 4 No 1 (2020)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

One mechanism for Drug-Drug Interaction (DDI) is pharmacodynamic (PD) interactions. They are interactions by which the effects of a drug are changed by other drugs at the site of receptor. The interactions can be predicted based on Side Effects Similarity (SES), Chemical Similarity (CS) and Target Protein Connectedness (TPC). This study aims to find the best classification technique by first applying the scaling process, variable interaction, discretization and resampling technique. We used Random Forest, Support Vector Machines (SVM) and Binary Logistic Regression for the classification. Out the three classification methods, we found the SVM classification method produces the highest Area Under Cover (AUC) value compared to the other, which is 67.91%.

METODE ANALISIS DISKRIMINAN KUADRAT TERKECIL PARSIAL UNTUK KLASIFIKASI SEGMEN LOYALITAS KONSUMEN SUSU PERTUMBUHAN Herdina Kuswari; Farit Mochamad Afendi; Khairil Anwar Notodiputro
Indonesian Journal of Statistics and Applications Vol 4 No 2 (2020)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v4i2.586

Consumer segmentation is the process of dividing consumers into different segments based on consumer characteristics, making it easier for companies to develop marketing strategies. The segmentation is carried out based on consumer loyalty using the RFM (Recency, Frequency, Monetary) approach a number of 7753 members of a nutritional product loyalty program is considered in the analysis. Partial least square discriminant analysis classification modeling is built using the results of consumer segmentation being the a response variable. The model is not good enough based on the AUC (Area Under Curve) value of the ROC (Relative Operating Characteristic) curve that quite low for each segment. The explanatory variables that have high contribution to the model is X5, X9, and X2 with VIP (Variable Importance in the Projection) values more than 1.

Co-Authors Aam Alamudi Abd. Rasyid Syamsuri Akbar Rizki Aki Hirai Anggraini Sukmawati Bagus Sartono Budi Susetyo Budi Waryanto Budi Waryanto Dian Ayuningtyas Erwandi Erwandi Fitrianto, Anwar Handayani, Vitri Aprilla Hari Wijayanto Hasnita Hasnita Herdina Kuswari Hilma Mutiara Winata Hiroki Takahashi I Made Sumertajaya Isnan Mulia Itasia Dina Sulvianti K A Notodiputro Kensuke Nakamura Kusman Sadik Latifah Kosim Darusman Maysarah Sabariah Kudadiri Md. Altaf-Ul-Amin . Mochamad Ridwan Muchlishah Rosyadah Muhammad Ali Umar Muhammad Syafiuddin Usman Mukhamad Najib Nadhif Nursyahban Novi Puspita Nur Janah Nur Jannah Nurul Qomariasih Pika Silvianti Rizal Bakri Rossi Azmatul Barro Rudi Heryanto Septaningsih, Dewi Anggraini Shigehiko Kanaya Siti Nurfajar Octaviani Sulistiyani . Syahrir, Nur Hilal A. Wisnu Ananta Kusuma

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