Fruit ripeness is an important thing in agriculture because it determines the fruit's quality. Determining the ripeness of the fruit that was done manually poses several weaknesses, such as takes a relatively long time, requires a lot of labor, and can cause inconsistencies. The agricultural sector is one of the important sectors of the economy in Indonesia. However, sometimes the process of determining fruit ripeness is still done by using the manual method. The development of computer vision and machine learning technologies can be used to classify fruit ripeness automatically. This study applies the Convolutional Neural Network to classify the ripeness of the banana. The banana's ripeness is divided into four classes: unripe/green, yellowish-green, mid-ripen, and overripe. Two pre-trained models are used, which are MobileNet V2 and NASNetMobile. The experiment was conducted using Google Colab and several libraries such as OpenCV, Tensorflow, and scikit-learn. The result shows that MobileNet V2 achieves higher accuracy and faster execution time than the NASNetMobile. The highest accuracy achieved is 96.18%.

Bioinformatics and Biological Data Mining TS-01Alignment Recovery for General Integer Scoring .

Heritage tourism is a trip traveling in certain areas that have historical value and ancestral heritage, such as temples, museums, palaces, etc. Indonesia is a country that has diverse historical heritages that have the potential to be developed be-cause there are historical sites and are considered as tourism potential. Technolo-gy plays a vital role in the development of heritage tourism to facilitate the deliv-ery of information to tourists, one of which is a mobile application. The proposed application design is a mobile application design with a gamification approach to facilitate tourists to obtain information and travel experiences to explore exciting tourist attractions. The gamification approach is used as a unique attraction where tourists are wrongly venturing for the concept of the game in conveying infor-mation using element games. This research was conducted in 3 temples, namely Gedongsongo temple, Prambanan temple, and Borobudur temple. The prototype design test was conducted on 100 tourists who visited 3 of the temple's tourist at-tractions. The results showed 86% of users agreed with the proposed prototype design. Based on the 95% confidence scale, shows that this research was suc-cessful in designing a prototype of a heritage tourism mobile application to ex-plore temple tourism. This application design is suitable for users based on four variables: Usefulness, Ease of Use, Ease of Learning, and Satisfaction.

Preservation of regional languages is very important in the current globalization era. The longer the erosion of regional languages will make the younger genera-tion do not know the language inherited from their ancestors. The fewer the speakers and interest in learning will make the Regional Language endangered. The purpose of this study is to design the learning of regional languages, espe-cially for children aged 9-10 years with the principles of pedagogy. The method of gamification uses a mobile-based application in the form of video, quiz games, and visual images. This regional language learning design is called Enggang Ka-nayatn Quiz (EKQ). The lesson material will be given first, then continued with a quiz. The material in the form of daily sentences and the introduction of cultural wisdom. The result is a mobile-based application that can be used by children for the learning of regional languages with the pedagogy principle. The collected points will get an attractive reward. The contribution made through this paper is to motivate children to learn regional languages so that they will maintain cultural wisdom and regional language dances, especially Dayak Kanayatn.

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Autism Spectrum Disorder (ASD) is a brain development disorder that affects the ability to communicate and interact socially. There have been many studies using machine learning methods to classify autism including support vector machines, decision trees, naïve Bayes, random forests, logistic regression, K-nearest Neighbors and others. In this study provides a review on autism spectrum disorder by using a machine learning algorithm that is supervised learning. The initial study of the article was collected from a website provided articles were in according with this study, after going through the process of selecting articles 11 articles were eligible in this study. Based on the results obtained, that the most widely used algorithm in the literature study in this study is support vector machine (SVM) of 63.63%, with the application of machine learning in the case of ASD expected to be able to accelerate and improve accuracy in determining a diagnosis.

Recommender systems are widely used in many fields. These systems work by recommending a personalized list of items to users based on their interests and thus helping users to overcome excessive information offered to them. For users such as students, selecting the right courses is a very challenging task while joining a new academic level. Picking the wrong courses may affect a student’s academic life as well as their future career. This paper aims at exploring the use of recommender systems to assist students in selecting courses that correspond to their abilities and interests. The results from this review showed that the Hybrid recommendation approach/system could be the best method to help students to choose the right courses in preparation for their future careers.

Tourism villages in the disruptive era inevitably have to adapt to technological advancements and the needs of millennials. The speed and clarity of information is a demand for the development of tourism villages today in addition to the innovation and uniqueness of tourist attractions. Efforts to build a model that is in line with these demands have begun to involve relevant stakeholders, i.e., village tourism managers, local governments, and tourists. Nevertheless, more in-depth studies are needed regarding the local wisdom of rural communities who are key actors in the development of tourism villages. This paper aims to explain the initial research in formulating a development model of smart tourism village based on information and communication technology. The case taken is tourism villages in Sleman district. A sampling of study cases in the form of tourism villages following the categories that have been determined by the Sleman Regency tourism office Initial search results show that there is no integration between village potential, systematic management, and meeting the needs of balanced tourists. This finding is the first step to formulate an ICT-based intelligent tourism village development model that is effective and efficient while still based on local wisdom in the effort to preserve nature and culture as a determining factor for the sustainability of tourism villages.