Daniel Oranova Siahaan

Development of a conceptual model of E-commerce adoption for SMEs in Indonesia

E-commerce adoption provides many benefits for small and medium enterprises. In Indonesia, adoption of e-commerce by SMEs is still in low level because they meet such several problems to adopt e-commerce as difficulty to learn and use e-commerce, to understand the role of e-commerce, etc. Based on the literature review, a conceptual model that is capable of measuring the adoption level of e-commerce is proposed. The model-that consists of both functional and non-functional requirements of an e-commerce-can be used as a framework for raising their e-commerce adoption level.

A Maturity Model for E-Commerce Adoption By Small And Medium Enterprises In Indonesia

E-commerce provides several advantages for Small and Medium Enterprises SMEs. E-commerce adoption by Indonesian SMEs is still very low. This study conducts a research to establish a maturity model of e-commerce adoption by Indonesia SMEs. It was carried out in two phases from 2014 until 2015. The result of the first phase recommends four levels of maturity model and 13 e-commerce benefits, 51 functionalities, and 9 non-functionalities that an e-commerce solution must have. The result of the second phase presents a maturity model of e-commerce adoption for SMEs in Indonesia.

A new model of students participation measurement in e-learning systems based on meaningful learning characteristics: An initial investigation

E-learning systems have been used widely in an education system. A lot of research works have been carried out to improve their features functionalities, such as students behavior observation, e-learning platform enhancement, and other related factors. This paper presents an initial investigation of a new model to measure students participation during their activities inside an e-learning system. The measurement of students participation is piloted by calculating the semantic score of relationships that may exist between e-learning activities and meaningful learning characteristics. The proposed model is expected to provide some benefits on measuring the level of students engagement with meaningful learning characteristics in order to produce better e-learning systems.

Aplikasi Web Manajemen Penjualan Air Galon Menggunakan Metode Just In Time

Perkembangan teknologi dijaman ini sudah sangat pesat. Banyaknya inovasi-inovasi baru yang muncul menyebabkan setiap orang harus mengikuti perkembangan jaman. Perkembangan teknologi ini banyak dimanfaatkan oleh perusahaan-perusahaan besar untuk mengembangkan bisnis yang dijalaninya. Oleh sebab itu banyak perusahaan-perusahaan dan startup-startup lokal kalah bersaing di daerah nya sendiri. Hampir sebagian besar perusahaan-perusahaan lokal belum menerapkan teknologi yang baik di dalam sistem kerjanya terkhusus di bagian perusahaan air minum. Sehingga dibutuhkan sebuah aplikasi yang optimal untuk menjadi solusi dalam menyelesaikan masalah ini. Tujuan dibangunnya aplikasi ini adalah untuk menerapkan metode Just In Time dalam sebuah perusahaan air minum untuk melihat bagaimana pengaruh metode ini terhadap perusahaan air minum. Metode Just In Time merupakan sebuah metode yang memproduksi sesuai dengan jumlah pemesanan. Dalam penelitian ini menggunakan sistem kerja Enterprise Resource Planning (ERP) dengan menerapkan empat modul yaitu Pengeluaran, Pendapatan, Penjualan dan Produksi. Metode forecasting digunakan dalam model Penjualan untuk memprediksi pesanan pelanggan kedepannya. Metode forecasting yang digunakan adalah Simple Moving Average yaitu menghitung rata-rata data dengan menambahkan harga penutupan dari data yang ada kemudian di bagi dengan jumlah periode waktu. Aplikasi ini diujicobakan pada perusahaan air minum bernama Bioneuro Water. Dalam pengujian aplikasi ini didapatkan hasil bahwa perusahaan Bioneuro Water cocok menggunakan metode Just In Time terbukti dengan menggunakan metode ini dapat mengurangi jumlah stock di gudang.

Rancang Bangun Kakas Bantu Deteksi Ketidaksesuaian Kode Sumber terhadap Diagram Urutan

Pada daur hidup perangkat lunak sendiri terdapat beberapa tahapan-tahapan yang harus dilalui yaitu pengumpulan kebutuhan, desain, implementasi, testing, perawatan. Dalam fokus tugas akhir ini, tugas akhir dititik beratkan pada tahap terakhir daur hidup perangkat lunak, yaitu tahap perawatan perangkat lunak. Dalam daur hidup tahap perawatan sangat rentan untuk mengubah kode sumber sesuai dengan kebutuhan atau keperluan fitur pada sebuah perangkat lunak yang mengakibatkan tidak sesuainya kode sumber terhadap desain awal. Tujuan tugas akhir ini yaitu untuk membuat sebuah kakas bantu untuk membantu analis sistem dalam mendeteksi ketidaksesuaian kode sumber tersebut terhadap desain, dalam hal ini desain yang menjadi pembanding adalah diagram urutan, hal ini dikarenakan diagram urutan menggambarkan alur sebuah fitur atau sistem. Dalam tugas akhir ini kakas bantu akan dibentuk menggunakan bahasa pemrograman java. Diagram urutan dengan format xmi dan kode sumber dengan format xml merupakan input yang diperlukan untuk kakas bantu. Dalam tugas akhir ini pendeteksian ketidaksesuaian dilakukan menggunakan string matching dan word similarity. Kakas bantu ini nanti menghasilkan berupa sebuah alur dari diagram urutan yang ditunjukkan pada tanda benar dan salah. Setiap alur digambarkan menjadi sebuah triplet. Triplet meliputi subyek,predikat,dan obyek. Dalam program ini nanti akan diuji dengan data uji sebanyak 10 buah dataset yang berasal dari 5 buah kasus diagram urutan.Hasil program menunjukkan 95% kesepakatan terhadap analisis ahli rekayassa perangkat lunak

A new strategy for developing scientific community model based on scientific article publication

The study was a literature review to develop a new strategy to clustering data. This study is part of our ongoing main project to develop scientific community model based on scientific article publication. The concept of this strategy is utilizing scientific article metadata elements that has been published electronically to map scientists community respect to the topics that are developing. This paper introduces TermRank approach that is adopted from PageRank to determine the strength value of a node and implements clustering technique to limit the number of computation in the topic modeling. Based on preliminary results, it is shown that in the stage of article data extraction, it turns out that it must be readjusted by adding the number of process to solve the problems on inconsistency inputting metadata elements, the use of two languages in abstract, and non-standard references format.

A new approach for modeling researcher community based on scientific article metadata using natural language processing

The Ministry of Research, Technology, and Higher Education of Indonesia has requirements to answer five main questions, i.e. what are the most popular research topics; which research topics tend to diminish; what are the trending research topics; who are the most influential researchers in a specific research topic, and; who are leading researchers in a specific topic. This study is a part of our ongoing main project to develop a scientific community model based on scientific article publication. This paper introduces a new approach to model a virtual researcher network using metadata of articles. We modified PageRank to develop a term graph and author-term graph for this purpose. Based on the preliminary results, the model could answer the five aforementioned questions.

Mapping requirements into e-commerce adoption level: A case study Indonesia SMEs

Requirements engineering provide an appropriate mechanism for understanding what the customer wants. Small and Medium Enterprises (SMEs) need to improve their ability to face a global market. This study proposed a framework of e-commerce adoption that provided functional requirements of each level. Mapping of functional requirements into level was identified using The Delphi method. The questionnaires were distributed to academicians, researchers and information technology practitioners. The questionnaires were sent to 15 respondents. This framework can be used as a guideline for SMEs in order to implement e-commerce. The future work would be evaluating the e-commerce adoption framework on larger number of SMEs in Indonesia

Software feature extraction using infrequent feature extraction

Evolution and maintenance processes are important but time consuming and expensive. It is very important to make the processes effective and efficient. A software developer can use resource like user opinion data to get information, such as user request, bug report, and user experience. It represents user needs and can be used to help allocate the necessary effort of software evolution and maintenance. The amount of user opinion data is very large and is difficult manually process them. A Recent study has tried to implement collocation finding method to extract software features from user opinion data. However, it is not able to extract non-frequently mentioned features. In this paper, we proposed an improvement for software feature extraction from user opinion data. Linguistic rules were used to complement collocation finding method. Feature pruning was also added to eliminate irrelevant features. The result shows that the proposed method is able to extract more features than collocation finding method.

Using Semantic Similarity for Identifying Relevant Page Numbers for Indexed Term of Textual Book

Back-of-book index page is one of navigation tools for reader. It helps reader to immediately jump to a page that contains relevant information regarding a specific term. It helps reader to retrieve information about specific topics in mind without having to read the complete book. Indexed terms are usually determined by author based on one’s subjective preference on what indications should be used to decide whether a term should be indexed and what pages are relevant. Therefore, indexing a book inherits subjectivity of author side. The book size is proportional to the indexing effort and consistency. This leads to the fact that page numbers are not always referred to relevant pages. This paper proposes an approach to identify relevancy of a page that contains an indexed term. This approach measures the semantic relation between indexed term with the respective sentence in the page. To measure the semantic relation, the approach utilizes semantic distance algorithm that based on Wordnet thesaurus. We measure the reliability of our system by measuring its degree of agreement with the book indexer using kappa statistics. The experimental result shows that the proposed approach are considered as good as the domain expert, given average kappa value 0.6034.