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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Kelautan dan Perikanan Terapan (JKPT)
Titin Siswantining
Universitas Indonesia
Agriculture, Biological Sciences & Forestry Computer Science & IT Engineering

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Performance of multivariate mutual information and autocorrelation encoding methods for the prediction of protein-protein interactions Alhadi Bustamam; Mohamad Irlin Sunggawa; Titin Siswantining
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i2.pp773-786

Abstract

Protein interactions play an essential role in the study of how an organism can be infected with a disease and also its effects. One of the challenges in computational methods in the prediction of protein-protein interactions is how to represent a sequence of amino acids in a vector so that it can be used in machine learning to create a model that can predict whether or not an interaction occurs in a protein pair. This paper examined the qualitative feature encoding methods of amino acid sequence, namely, multivariate mutual information (MMI), and the quantitative feature encoding methods, namely, autocorrelation. We develop the new design for MMI and autocorrelation feature encoding methods which give better results than the previous research. There are four ways to build the MMI method and six ways to build the autocorrelation method that we tested. We also built four types of MMI-autocorrelation (mixed) method and look for the best form of each type of MMI, autocorrelation, and mixed-method. We combine these feature encoding methods with support vector machine (SVM) as machine learning methods. We also test the encoding methods we propose to several machine learning classifier methods, such as random forest (RF), k-nearest neighbor (KNN), and gradient boosting.
PARAMETER POPULASI DAN TINGKAT PEMANFAATAN IKAN KUNIRAN (Upeneus sulphureus, Cuvier 1829) DI PERAIRAN SELAT MALAKA Nurulludin Nurulludin; Titin Siswantining; Muhammad Taufik; Rudy Masuswo Purwoko
Jurnal Kelautan dan Perikanan Terapan (JKPT) Vol 3, No 1 (2020): JKPT Juni 2020
Publisher : Politeknik Ahli Usaha Perikanan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (66.856 KB) | DOI: 10.15578/jkpt.v3i1.8299

Abstract

Sumberdaya ikan kuniran (Upeneus sulphureus) di Selat Malaka telah dieksploitasi sejak lama dengan alat tangkap pukat tarik, terutama sebelum adanya moratorium pelarangan alat tangkap trawl dan sejenisnya. Penelitian dilaksanakan pada bulan Januari - November 2014 di Perairan Selat Malaka. Pengukuran panjang cagak ikan kuniran diambil secara acak terhadap 2.694 sampel yang dilakukan di PPS Belawan. Tujuan penelitian ini adalah untuk menganalisis beberapa parameter pertumbuhan populasi ikan kuniran (Upeneus sulphureus) di Selat Malaka. Analisis data parameter populasi dianalisis menggunakan FAO-ICLARM Stock Assessement Tools (FISAT). Hasil analisis diperoleh beberapa parameter populasi ikan kuniran dengan koefisien pertumbuhan (K) sebesar 0,80 per tahun, (L∞) 21,0 cm, (M) 1,73 per tahun (F) 2,51 per tahun, dan E 0,59 per tahun. Penambahan baru individu ke dalam populasi berlangsung sepanjang tahun dan mencapai puncaknya terjadi pada akhir musim timur (Juni – Agustus) sampai musim peralihan II (September – Nopember). Pemanfaatan ikan kuniran di perairan Selat Malaka sebelum moratorium pelarangan pukat tarik dalam kondisi jenuh (Fully exploited).
Co-Authors Bustamam, Alhadi Kaloka, Tesdiq Prigel Mohamad Irlin Sunggawa Muhammad Taufik Nurulludin Nurulludin Rudy Masuswo Purwoko