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All Journal Perfecting a Video Game with Game Metrics SCHOOL EDUCATION JOURNAL PGSD FIP UNIMED Jurnal Sistem Informasi Kaputama (JSIK) KLIK: Kajian Ilmiah Informatika dan Komputer Deli Sains Informatika
Melly Br Bangun
Bogor Agricultural University
Computer Science & IT Languange, Linguistic, Communication & Media

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Morphological Feature Extraction of Jabon’s Leaf Seedling Pathogen using Microscopic Image Melly Br Bangun; Yeni Herdiyeni; Elis Nina Herliyana
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 1: March 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i1.2486

Abstract

This research aims to analyze morphological techniques for feature extraction of Jabon’s leaf seedling pathogen using digital microscopic image. The kinds of the pathogen were Curvularia sp., Colletotrichum sp., and Fusarium sp.. Pathogens or causes of disease were identified manually based on macroscopic and microscopic observation of morphological characters. Morphological characters describe the characteristics of shape, color and size of a pathogen structure. We focused on shape feature by using the morphological techniques to feature extraction. The morphology features extraction used were area, perimeter, convex area, convex perimeter, compactness, solidity, convexity, and roundness. The methodologies were acquisition, preprocessing, features extraction and data analysis for derivative features. With features extraction, we got the pattern that described each pathogen for pathogen identification. From the experimental result showed that compactness and roundness feature were able to differentiate each pathogen due to that the characteristics of each pathogen class were separated.
IDENTIFIKASI HAMA PADA TANAMAN KEDELAI DENGAN MENGGUNAKAN METODE FUZZY Fuzy Yustika Manik; Melly Br Bangun
JSIK (Jurnal Sistem Informasi Kaputama) Vol 1, No 1 (2017)
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.1234/jsik.v1i1.23

Abstract

Kedelai adalah komoditas pangan utama di Indonesia selain padi dan jagung. Permintaan akan kedelai semakinmeningkat karena kedelai mampu menjadi alternatif bagi masyarakat yang berminat pada makanan berprotein nabatirendah kolestrol. Namun bila dilihat dari hasil produksinya masih belum memuaskan. Hal ini disebabkan olehberbagai faktor, salah satunya gangguan hama dan penyakit. Dalam mengidentifikasi hama, petani mengalamikesulitan. Gejala-gejala serangan yang terlihat juga memperlihatkan kesamaan bahkan gejala antara hama denganpenyakit yang hampir sama. Morfologi yang sama dari beberapa jenis hama yang berbeda juga mempengaruhiproses identifikasi. Metode yang digunakan adalah fuzzy, hal ini dilakukan karena parameter-parameter yangdigunakan dalam penelitian ini (morfologi hama, gejala dan tingkat kerusakan) adalah variable kualitatif yaituvariable yang menunjukkan suatu intensitas yang sulit diukur memiliki sifat ambiguitas (tidak crips). Hasilnyametode fuzzy dapat mengidintifikasi hama pada tanaman kedelai dengan tingkat akurasi 77.78 %.
INDONESIAN ELEMENTARY SCHOOLS TEACHERS’ ATTITUDE TOWARDS VIDEO CONFERENCING PLATFORM IMPLEMENTATION DURING COVID-19 PANDEMIC Muhammad Takwin Machmud; Noer Risky Ramadhani; Rini Juliani Sipahutar; Nurhudayah Manjani; Natalia Silalahi; Nina Afria Damayanti; Syahrial Syahrial; Melly Br Bangun
SCHOOL EDUCATION JOURNAL PGSD FIP UNIMED Vol 12, No 4 (2022): SHOOL EDUCATION JOURNAL PGSD FIP UNIMED
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/sejpgsd.v12i4.40420

Abstract

This study is identifying elementary schools teacher attitudes towards video conferencing platform implementation during Covid-19 pandemic. The research aims include (1) to identify teachers’ attitude towards implementing video conferencing platforms for learning (2) to identify teachers' challenges encountered during implementing video conferencing and how to overcome that challenge. The 103 elementary schools teachers were included. The teacher selected by simple random sampling techniques. The questionnaire's content is based on teachers' attitudes toward using video conferencing in the classroom during the COVID-19 epidemic, as measured by the following indicators: efficiency, effectiveness, motivation, and variety of obstacles. The elementary schools teachers’ attitude shows positive responses to video conferencing in learning such as providing various learning activities, providing flexibility in teaching process, easiness to access learning materials, and ease in assessing and monitoring students' learning progress. Furthermore, the result reveals the majority of the elementary schools teachers faced technical issues and availability as obstacles in implementing a video conferencing platform. The majority of elementary schools teachers were able to resolve these technological difficulties by exploring other teaching strategies and seeking professional advice.
Integrasi data Protein-Protein Interactions dan Pathway untuk Menentukan Score pada pathway Menggunakan Analisis Graf Lailan Sahrina Hasibuan; Ahmad Fariqi; Lilik Prayitno; Melly Br Bangun
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 3 No. 6 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v3i6.932

Abstract

The development of molecular biology technology produces large amounts of omics data. Integration of omics data is useful for the analysis of biological processes at the molecular level, such as protein expression, drug mechanisms against diseases, and mechanisms of inheritance. This study aims to integrate protein molecular biology data through protein-protein interactions (PPIs), pathways, modules and orthology, to calculate pathway scores. The score calculation uses the degree calculation on the graph concept. Proteins, pathways, modules and orthologs act as nodes, while the interactions between them act as edges. Furthermore, according to the concept of a graph, nodes with a high degree represent nodes that have an important role in a graph. Based on this concept, the most important pathway related to a protein is the pathway with the highest degree in a multipartite graph formed by PPIs, modules, orthologs and pathways. The output of this study is a package in the R language to integrate data on molecular biology of proteins, pathways, modules and orthology, then displays the pathways that have the most role in protein based on the order of the highest score. This package was tested using protein Insulin (INS) and Xanthine dehydrogenase (XDH) inputs. The results of calculating the score on the pathway for INS produced the pathway with the highest score, namely MAPK signaling pathway (0.18) lane 1, Pathways in cancer (0.137) lane 2, Ubiquitin mediated proteolysis (0.28) lane 3. XDH protein input produces Purine metabolism pathway (0.67) lane 1, Metabolic pathways (0.48) lane 2 and Purine metabolism (0.23) lane 3. These results can be used for enrichment analysis regarding the relationship between proteins and pathways.
COMPARATION BETWEEN FEED FORWARD NEURAL NETWORK (FFNN) AND SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (SARIMA) IN FORECASTING SEASONAL TIME SERIES DATA Dian Septiana; Melly Br Bangun Melly Br Bangun
Deli Sains Informatika Vol. 2 No. 2 (2023): Artikel Riset Juni 2023
Publisher : LPPM Universitas Deli Sumatera

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

Abstract

Seasonal patterns in time series data are periodic and recurring patterns caused by certain factors such as weather, holidays, repetition of promotions, or changes in the economic climate. Good data forecasting is very important for making decisions in the business sector, such as retail prices, marketing, production and other business sectors. There are several approaches that can be taken to analyze time series data that has a seasonal or trending pattern. Among them is the classical approach which decomposes seasonal and non-seasonal factors, then forecasts with certain assumptions. Then there is also an approach using artificial intelligence, in this case a more flexible feed-forward neural network is used as a tool for forecasting time series data. In this study the data used is data with a regular seasonal pattern 12. For data with a pattern like this SARIMA (1,1,1)(0,1,1)12 with a MAPE of 1.775% gives better results than FFNN 12-10-1 which produces a MAPE value of 7.5226%.
Co-Authors Ahmad Fariqi Dian Septiana Elis Nina Herliyana Fuzy Yustika Manik Hasibuan, Lailan Sahrina Lilik Prayitno Muhammad Takwin Machmud Natalia Silalahi Nina Afria Damayanti Noer Risky Ramadhani Nurhudayah Manjani Rini Juliani Sipahutar Syahrial Syahrial