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All Journal BIOTROPIA - The Southeast Asian Journal of Tropical Biology Jurnal Teknologi Informasi Cyberku
Suprapedi Suprapedi
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Veterinary

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Lipid Accumulation by Flavodon flavus ATH using Palm Oil Mill Effluent as Substrate I Made Sudiana; Atit Kanti; Helbert Helbert; Senlie Octaviana; Suprapedi Suprapedi
BIOTROPIA - The Southeast Asian Journal of Tropical Biology Vol. 21 No. 2 (2014)
Publisher : SEAMEO BIOTROP

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (415.989 KB) | DOI: 10.11598/btb.2014.21.2.388

Abstract

Large amount of palm mill effluent is generated annually. The waste would be potential for production of single cell oils (SCOs). The objective of study was to evaluate the lipid accumulation by fungi using palm mill effluent as substrate. To obtain most potential strains for lipid accumulation, seven filamentous fungi isolated from various biomes were evaluated for their ability to produce endoglucanase, and its lipid accumulation. Fungal hypae grown on palm oil mill effluent accumulated lipid of 34,3-87,5 of their dry cell mass. The profile of transesterified SCOs revealed a high content of saturated and monounsaturated fatty acids i.e., palmitic (C16:0), stearic (C18:0) and oleic (C18:1) acids similar to conventional vegetable oils used for biodiesel production. The strain was able to use organic substrates in POME implies that they are promising strain for biofuel feed stock as well as for meeting effluent quality for wastewater discharge.
PREDIKSI KELULUSAN MAHASISWA TEPAT WAKTU BERDASARKAN USIA, JENIS KELAMIN, DAN INDEKS PRESTASI MENGGUNAKAN ALGORITMA DECISION TREE Agus Romadhona; Suprapedi Suprapedi; Heribertus Himawan
Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 13 No 1 (2017): Jurnal Teknologi Informasi CyberKU Vol. 13, no 1
Publisher : Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (275.642 KB)

Abstract

Prediction of the study period in college is needed in determine the accuracy of the students study period according to the specified time so that wisdom of prevention related to the study period is no ton time could be done. This research aims to find patterns to predict the timely graduation of students usingdata mining techniques and models to predict long period of study was Decision tree algorithm C4.5 to compare with ID3 and CHAID algorithms using test data to determine the percentage of precision, recall and accuracy is obtained that the algorithm Decision Tree C4.5 has a better performance compared with other algorithms. From this research it was found that the prediction of the students study period are affected by incoming students age, gender, GPA semesters 1 through 4 semesters GPA and the most influential is the 4th semester GPA of students graduate on time with a value of 0.340 gain of all attributes. Decision tree algorithm C4.5 reaches the highest accuracy on the amount of data 389 with 91.51% accuracy values for k-fold=3, 90.75 for k-fold = 5 and 90.77 with k-fold = 10, While ID3 and CHAID algorithms achieving a low accuracy value. So thus the value accuracy of Decision Tree algorithm C4.5 is better than the ID3 and CHAID algorithm. In this research, training data are used as much as 389. To see better performance in the accuracy of the results of each algorithm, thus for furthermore research the number of data records used training process should be improved.
PROTOTYPE LAMPU LALU LINTAS ADAPTIF BERBASIS MULTI AGENT MANGGUNAKAN LOGIKA FUZZY YANG TERTANAM PADA MICROCONTROLLER Adrin T; Heribertus Himawan; Suprapedi Suprapedi
Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 12 No 2 (2016): Jurnal Teknologi Informasi CyberKU Vol. 12, no 2
Publisher : Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (506.172 KB)

Abstract

Traffic light is a very important tool for urban life in regulating the smooth flow of traffic on the highway. The use of traffic lights are now much more applied using static timing system or a traffic light system which does not know the condition of the crossing are many vehicles or fewer. Timing pattern that is applied from one segment to another segment is set in rotation. In the study conducted to design a traffic light prototype based on multi- agent using fuzzy logic which is planted on the microcontroller. There are two parts and types of microcontrollers are used to design the prototype. The first part, the Slave microcontroller Atmega 32 and the second type, the type of Master mikontroler Atmega 128. Traffic light system which can adapt to the environment made the crossing. If there is a deviation of the queue of vehicles which have very much, then the green light time longer than the deviation that only have a little queue of vehicles. Thus, the traffic light is more adaptive to the dynamic vehicle that will cross the intersection. Traffic lights can also communicate with traffic lights nearest neighbors in both directions. Communication is done through mutual give information about the number of vehicles that left deviation towards each junction nearest neighbors. Results of this study found that the performance of fuzzy logic embedded in the microcontroller can control traffic lights with dynamic adaptive to existing vehicles on Line 1, Line 2 and Line 3. Prototype designed traffic lights represent the environmental conditions that have multiple intersections and each intersection has four traffic lights that can communicate with Multi Agent another intersection nearest neighbors.
METODE SAMPLE BOOSTRAPING PADA K-NEAREST NEIGHBOR UNTUK KLASIFIKASI STATUS DESA Eko Siswanto; Suprapedi Suprapedi; Purwanto Purwanto
Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 14 No 1 (2018): Jurnal Teknologi Informasi CyberKU Vol.14 no 1 2018
Publisher : Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro

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Abstract

The Ministry of Rural Area, Remote Area Development and Transmigration divides village itself into five villages, such as, Independent Village, Advance Village, Developing Village, Remote Village and Very Extremely Remote Village. The data are based on Village Potency (Podes) in 2014 by the Ministry of Rural Area, Remote Area Development and Transmigration. It is necessary to know that the data of The Ministry of Rural Area, Remote Area Development and Transmigration can be used to predict the relationship between village development indicators and the status of villages. In this case, it means whether the indicators, which are built, can influence the status of villages or not and whether they can make the status of villages become better than before. k-Nearest Neighbor (k-NN) algorithm is a method which is used to classify toward new object based on k as the nearest neighbor. k-Nearest Neighbor (k-NN) algorithm has the strength as the effective and simple algorithm and it has been used by many problem classifications. However, it has weakness if it is used for the big dataset. It can happen because it needs higher computation time. In this research, Bootstrapping Sample method is proposed to increase the optimalization of computation accuracy and time on Boostraping Sample method. Based on this research, by using the integration of k-Nearest Neighbor (k-NN) algorithm with Bootstrapping Sample method on IPD dataset on Jepara in 2014, apparently it can increase the accuracy until 5.41 % (91.89%-97.30%) than using standard k-NN algorithm. The last, from the result of this research it can be inferred that by using the integration of K-Nearest Neighbor (k-NN) algorithm with Boostraping Sample method shows the better accuracy than using standard k-NN algorithm
KOMPARASI SIMPLE ADDITIVE WEIGHTING DAN ANALYTICAL HIERARCHY PROCESS TERHADAP PENENTUAN PENGELOMPOKAN DESA Adityo Putro Wicaksono; Abdul Syukur; Suprapedi Suprapedi
Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 15 No 1 (2019): Jurnal Teknologi Informasi CyberKU Vol. 15, no 1
Publisher : Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (630.411 KB)

Abstract

Penilaian Indeks Pembangunan Desa (IPD) yang masih bersifat subyektif dan belum adanya identifikasi faktor-faktor yang mempengaruhi sebuha desa berkembang menjadi masalah yang dihadapi pemerintah sekarang. Untuk menentukan nilai Indeks Pembangunan Desa yang baik, dibutuhkan metode pendukung keputusan yang bertindak dalam pengambilan keputusan untuk penentuan nilai IPD secara baik dan akurat. Dengan menggunakan pendekatan metode lain, yaitu metode dalam sistem pendukung keputusan seperti Simple Additive Weighting (SAW), Analytical Hierarchy Process (AHP), dan Decision Tree, diharapkan metode ini dapat menggantikan metode perhitungan dalam Indeks Pembangunan Desa yang sekarang digunakan, dengan hasil yang lebih baik dan akurat. Dengan menerapkan metode ini, diharapkan dapat membantu dalam penentuan penilaian IPD dan Pengelompokan desa guna untuk mengetahui daerah desa mana saja yang harus ditangani terlebih dahulu dan kriteria apa sajakah yang harus diperbaiki pada desa yang harus ditangani tersebut dengan hasil yang lebih baik.Pada penelitian ini, diperoleh hasil bahwa penerapan metode AHP dan SAW dengan Expert Judgement dan Decision Tree terhadap penentuan kelompok desa dan pembentukan Decision Tree, hasil dari metode SAW untuk pembentukan tree 3 kelompok memiliki hasil akurasi tertinggi, yaitu 94,02% jika dibandingkan dengan metode AHP dengan hasil untuk 3 kelompok sebesar 81,76%.
Co-Authors Abdul Syukur Adityo Putro Wicaksono Adrin T Agus Romadhona Atit Kanti Eko Siswanto Helbert Helbert Heribertus Himawan I Made Sudiana Purwanto Purwanto Senlie Octaviana